Publications by Yu Liu
- 2024
-
Percolative supercurrent in superconductor-ferromagnetic insulator
bilayers -
Abstract
- We report tunneling spectroscopy and transport measurements in superconducting Al and ferromagnetic-insulator EuS bilayers. The samples display remanent spin-splitting, roughly half the superconducting gap, and supercurrent transport above the average paramagnetic limit. We interpret this behavior as arising from the interplay between two characteristic length scales: the superconducting coherence length, $\xi$, and the magnetic domain size, $d$. By comparing experimental results to a theoretical model, we find $\xi/d \approx 10$. In this regime, spin-averaging across the micromagnetic configuration can locally suppress superconductivity, resulting in percolative supercurrent flow.
A. Maiani, A. C. C. Drachmann, L. Galletti, C. Schrade, Y. Liu, R. Seoane Souto, S. Vaitiekėnas [pdf]
-
Percolative supercurrent in superconductor-ferromagnetic insulator
bilayers -
Abstract
- 2023
-
Gate-tunable superconductivity in hybrid InSb–Pb nanowires -
Abstract
- We present a report on hybrid InSb-Pb nanowires that combine high spin-orbit coupling with a high critical field and a large superconducting gap. Material characterization indicates the Pb layer of high crystal quality on the nanowire side facets. Hard induced superconducting gaps and gate-tunable supercurrent are observed in the hybrid nanowires. These results showcase the promising potential of this material combination for a diverse range of applications in hybrid quantum transport devices.
Yan Chen, David van Driel, Charalampos Lampadaris, Sabbir A Khan, Khalifah Alattallah, Lunjie Zeng, Eva Olsson, Tom Dvir, Peter Krogstrup, Yu Liu Journal reference: Appl. Phys. Lett. 123, 082601 (2023) [pdf] DOI: 10.1063/5.0155663
-
Supercurrent reversal in ferromagnetic hybrid nanowire Josephson junctions -
Abstract
- We report supercurrent transport measurements in hybrid Josephson junctions comprised of semiconducting InAs nanowires with epitaxial ferromagnetic insulator EuS and superconducting Al coatings. The wires display a hysteretic superconducting window close to the coercivity, away from zero external magnetic field. Using a multi-interferometer setup, we measure the current-phase relation of multiple magnetic junctions and find an abrupt switch between $\pi$ and 0 phases within the superconducting window. We attribute the 0-$\pi$ transition to the discrete flipping of the EuS domains and provide a qualitative theory showing that a sizable exchange field can polarize the junction and lead to the supercurrent reversal. Both $0$ and $\pi$ phases can be realized at zero external field by demagnetizing the wire.
D. Razmadze, R. Seoane Souto, L. Galletti, A. Maiani, Y. Liu, P. Krogstrup, C. Schrade, A. Gyenis, C. M. Marcus, S. Vaitiekėnas [pdf] DOI: 10.1103/PhysRevB.107.L081301 2204.03202v3 [pdf]
-
Gate-tunable superconductivity in hybrid InSb–Pb nanowires -
Abstract
- 2022
-
Evidence for spin-polarized bound states in semiconductor–superconductor–ferromagnetic-insulator islands -
Abstract
- We report Coulomb blockade transport studies of semiconducting InAs nanowires grown with epitaxial superconducting Al and ferromagnetic insulator EuS on overlapping facets. Comparing experiment to a theoretical model, we associate cotunneling features in even-odd bias spectra with spin-polarized Andreev levels. Results are consistent with zero-field spin splitting exceeding the induced superconducting gap. Energies of subgap states are tunable on either side of zero via electrostatic gates.
S. Vaitiekėnas, R. Seoane Souto, Y. Liu, P. Krogstrup, K. Flensberg, M. Leijnse, C. M. Marcus Journal reference: Phys. Rev. B 105, L041304 (2022) [pdf] DOI: 10.1103/PhysRevB.105.L041304
-
Evidence for spin-polarized bound states in semiconductor–superconductor–ferromagnetic-insulator islands -
Abstract
- 2021
-
Characteristic interaction potential of black hole molecules from the
microscopic interpretation of Ruppeiner geometry -
Abstract
- Ruppeiner geometry has been found to be a novel promising approach to uncover the microstructure of fluid systems and black holes. In this work, combining with the micro model of the Van der Waals fluid, we shall propose a first microscopic interpretation for the empirical observation of Ruppeiner geometry. Then employing the microscopic interpretation, we disclose the potential microstructure for the anti-de Sitter black hole systems. Of particular interest, we obtain the microscopic interaction potentials for the underlying black hole molecules. This significantly strengthens the study towards to the black hole nature from the viewpoint of the thermodynamics.
Shao-Wen Wei, Yu-Xiao Liu, Robert B. Mann [pdf]
-
Bridging Unsupervised and Supervised Depth from Focus via All-in-Focus
Supervision -
Abstract
- Depth estimation is a long-lasting yet important task in computer vision. Most of the previous works try to estimate depth from input images and assume images are all-in-focus (AiF), which is less common in real-world applications. On the other hand, a few works take defocus blur into account and consider it as another cue for depth estimation. In this paper, we propose a method to estimate not only a depth map but an AiF image from a set of images with different focus positions (known as a focal stack). We design a shared architecture to exploit the relationship between depth and AiF estimation. As a result, the proposed method can be trained either supervisedly with ground truth depth, or \emph{unsupervisedly} with AiF images as supervisory signals. We show in various experiments that our method outperforms the state-of-the-art methods both quantitatively and qualitatively, and also has higher efficiency in inference time.
Ning-Hsu Wang, Ren Wang, Yu-Lun Liu, Yu-Hao Huang, Yu-Lin Chang, Chia-Ping Chen, Kevin Jou [pdf]
-
Hybrid Neural Fusion for Full-frame Video Stabilization -
Abstract
- Existing video stabilization methods often generate visible distortion or require aggressive cropping of frame boundaries, resulting in smaller field of views. In this work, we present a frame synthesis algorithm to achieve full-frame video stabilization. We first estimate dense warp fields from neighboring frames and then synthesize the stabilized frame by fusing the warped contents. Our core technical novelty lies in the learning-based hybrid-space fusion that alleviates artifacts caused by optical flow inaccuracy and fast-moving objects. We validate the effectiveness of our method on the NUS, selfie, and DeepStab video datasets. Extensive experiment results demonstrate the merits of our approach over prior video stabilization methods.
Yu-Lun Liu, Wei-Sheng Lai, Ming-Hsuan Yang, Yung-Yu Chuang, Jia-Bin Huang [pdf]
-
Gluing n-tilting and n-cotilting subcategories -
Abstract
- Recently, Wang, Wei and Zhang define the recollement of extriangulated categories, which is a generalization of both recollement of abelian categories and recollement of triangulated categories. For a recollement $(\mathcal A ,\mathcal B,\mathcal C)$ of extriangulated categories, we show that $n$-tilting (resp. $n$-cotilting) subcategories in $\mathcal A$ and $\mathcal C$ can be glued to get $n$-tilting (resp. $n$-cotilting) subcategories in $\mathcal B$ under certain conditions.
Yu Liu, Panyue Zhou [pdf]
-
Silting reduction in extriangulated categories -
Abstract
- We introduce pre-silting and silting subcategories in extriangulated categories and generalize the silting theory in triangulated categories. We prove that the silting reduction $\mathcal B/({\rm thick}\mathcal W)$ of an extriangulated category $\mathcal B$ with respect to a pre-silting subcategory $\mathcal W$ can be realized as a certain subfactor category of $\mathcal B$. This generalizes the result by Iyama-Yang. In particular, for a Gorenstein algebra, we get the relative version of the description of the singularity category due to Happel and Chen-Zhang by this reduction.
Yu Liu, Panyue Zhou, Yu Zhou, Bin Zhu [pdf]
-
The newly observed state $D_{s0}(2590)^{+}$ and width of $D^*(2007)^0$ -
Abstract
- We choose the Reduction Formula, PCAC and Low Energy Theory to reduce the $S$ matrix of a OZI allowed two-body strong decay involving a light pseudoscalar, the covariant transition amplitude formula with relativistic wave functions as input is derived. After confirm this method by the decay $D^*(2010)\to D\pi$, we study the state $D^*(2007)$, and the full width $\Gamma_{\rm{th}}(D^*(2007))=53.8\pm0.7$ keV is obtained. Supposing the newly observed $D_{s0}(2590)^{+}$ to be the state $D_s(2^1S_0)^+$, we find its decay width $\Gamma$ is highly sensitive to the $D_{s0}(2590)^{+}$ mass, which result in the meaningless comparison of widths by different models with various input masses. Instead of width, we introduce a model independent quantity $X$ and the ratio $\Gamma/{|{\vec P_f}|^3}$, which are almost mass independent, to give us useful information. The results show that, all the existing theoretical predictions $X_{D_s(2S) \to D^*K}=0.25\sim 0.41$ and $\Gamma/{|{\vec P_f}|^3}=0.81\sim1.77$ MeV$^{-2}$ are much smaller than experimental data $0.585^{+0.015}_{-0.035}$ and $4.54^{+0.25}_{-0.52}$ MeV$^{-2}$. Further compared with $X^{ex}_{D^*(2010) \to D\pi}=0.58$, the current data $X^{ex}_{D_s(2S) \to D^*K}=0.585^{+0.015}_{-0.035}$ is too big to be an reasonable value, so to confirm $D_{s0}(2590)^{+}$ as the state $D_s(2^1S_0)^+$, more experimental studies are needed.
Guo-Li Wang, Wei Li, Tai-Fu Feng, Yue-Long Wang, Yu-Bin Liu [pdf]
-
Spatio-temporal Parking Behaviour Forecasting and Analysis Before and
During COVID-19 -
Abstract
- Parking demand forecasting and behaviour analysis have received increasing attention in recent years because of their critical role in mitigating traffic congestion and understanding travel behaviours. However, previous studies usually only consider temporal dependence but ignore the spatial correlations among parking lots for parking prediction. This is mainly due to the lack of direct physical connections or observable interactions between them. Thus, how to quantify the spatial correlation remains a significant challenge. To bridge the gap, in this study, we propose a spatial-aware parking prediction framework, which includes two steps, i.e. spatial connection graph construction and spatio-temporal forecasting. A case study in Ningbo, China is conducted using parking data of over one million records before and during COVID-19. The results show that the approach is superior on parking occupancy forecasting than baseline methods, especially for the cases with high temporal irregularity such as during COVID-19. Our work has revealed the impact of the pandemic on parking behaviour and also accentuated the importance of modelling spatial dependence in parking behaviour forecasting, which can benefit future studies on epidemiology and human travel behaviours.
Shuhui Gong, Xiaopeng Mo, Rui Cao, Yu Liu, Wei Tu, Ruibin Bai [pdf]
-
Iterative Self-consistent Parallel Magnetic Resonance Imaging
Reconstruction based on Nonlocal Low-Rank Regularization -
Abstract
- Iterative self-consistent parallel imaging reconstruction (SPIRiT) is an effective self-calibrated reconstruction model for parallel magnetic resonance imaging (PMRI). The joint L1 norm of wavelet coefficients and joint total variation (TV) regularization terms are incorporated into the SPIRiT model to improve the reconstruction performance. The simultaneous two-directional low-rankness (STDLR) in k-space data is incorporated into SPIRiT to realize improved reconstruction. Recent methods have exploited the nonlocal self-similarity (NSS) of images by imposing nonlocal low-rankness of similar patches to achieve a superior performance. To fully utilize both the NSS in Magnetic resonance (MR) images and calibration consistency in the k-space domain, we propose a nonlocal low-rank (NLR)-SPIRiT model by incorporating NLR regularization into the SPIRiT model. We apply the weighted nuclear norm (WNN) as a surrogate of the rank and employ the Nash equilibrium (NE) formulation and alternating direction method of multipliers (ADMM) to efficiently solve the NLR-SPIRiT model. The experimental results demonstrate the superior performance of NLR-SPIRiT over the state-of-the-art methods via three objective metrics and visual comparison.
Ting Pan, Jizhong Duan, Junfeng Wang, Yu Liu [pdf]
-
SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution
with Skip-Transformer -
Abstract
- Point cloud completion aims to predict a complete shape in high accuracy from its partial observation. However, previous methods usually suffered from discrete nature of point cloud and unstructured prediction of points in local regions, which makes it hard to reveal fine local geometric details on the complete shape. To resolve this issue, we propose SnowflakeNet with Snowflake Point Deconvolution (SPD) to generate the complete point clouds. The SnowflakeNet models the generation of complete point clouds as the snowflake-like growth of points in 3D space, where the child points are progressively generated by splitting their parent points after each SPD. Our insight of revealing detailed geometry is to introduce skip-transformer in SPD to learn point splitting patterns which can fit local regions the best. Skip-transformer leverages attention mechanism to summarize the splitting patterns used in the previous SPD layer to produce the splitting in the current SPD layer. The locally compact and structured point cloud generated by SPD is able to precisely capture the structure characteristic of 3D shape in local patches, which enables the network to predict highly detailed geometries, such as smooth regions, sharp edges and corners. Our experimental results outperform the state-of-the-art point cloud completion methods under widely used benchmarks. Code will be available at https://github.com/AllenXiangX/SnowflakeNet.
Peng Xiang, Xin Wen, Yu-Shen Liu, Yan-Pei Cao, Pengfei Wan, Wen Zheng, Zhizhong Han [pdf]
-
A generalized phenomenological model for the magnetic field penetration
and magnetization hysteresis loops of a type-II superconductor -
Abstract
- A generalized phenomenological model for the critical state of type-II superconductors with magnetic field parallel to the superconducting plate is proposed. This model considers the global magnetization including both the equilibrium magnetization from surface screening current and the non-equilibrium magnetization from bulk pinning in a self-consistent way. Our model can be used to simulate the magnetization-hysteresis-loops (MHLs) and flux penetrating process of different type-II superconductors, from low- to high-kappa values. Here we take an optimally doped Ba0.6K0.4Fe2As2 single crystal as a testing example. The model can fit the data quite well and several important parameters can be extracted from the fitting. Thus, the model can be extended to a general case for studying the magnetization and flux penetration in other type-II superconductors.
Wei Xie, Yu-Hao Liu, Hai-Hu Wen [pdf]
-
Unified Regularity Measures for Sample-wise Learning and Generalization -
Abstract
- Fundamental machine learning theory shows that different samples contribute unequally both in learning and testing processes. Contemporary studies on DNN imply that such sample difference is rooted on the distribution of intrinsic pattern information, namely sample regularity. Motivated by the recent discovery on network memorization and generalization, we proposed a pair of sample regularity measures for both processes with a formulation-consistent representation. Specifically, cumulative binary training/generalizing loss (CBTL/CBGL), the cumulative number of correct classiffcations of the training/testing sample within training stage, is proposed to quantize the stability in memorization-generalization process; while forgetting/mal-generalizing events, i.e., the mis-classification of previously learned or generalized sample, are utilized to represent the uncertainty of sample regularity with respect to optimization dynamics. Experiments validated the effectiveness and robustness of the proposed approaches for mini-batch SGD optimization. Further applications on training/testing sample selection show the proposed measures sharing the unified computing procedure could benefit for both tasks.
Chi Zhang, Xiaoning Ma, Yu Liu, Le Wang, Yuanqi Su, Yuehu Liu [pdf]
-
Unsupervised Learning of Fine Structure Generation for 3D Point Clouds
by 2D Projection Matching -
Abstract
- Learning to generate 3D point clouds without 3D supervision is an important but challenging problem. Current solutions leverage various differentiable renderers to project the generated 3D point clouds onto a 2D image plane, and train deep neural networks using the per-pixel difference with 2D ground truth images. However, these solutions are still struggling to fully recover fine structures of 3D shapes, such as thin tubes or planes. To resolve this issue, we propose an unsupervised approach for 3D point cloud generation with fine structures. Specifically, we cast 3D point cloud learning as a 2D projection matching problem. Rather than using entire 2D silhouette images as a regular pixel supervision, we introduce structure adaptive sampling to randomly sample 2D points within the silhouettes as an irregular point supervision, which alleviates the consistency issue of sampling from different view angles. Our method pushes the neural network to generate a 3D point cloud whose 2D projections match the irregular point supervision from different view angles. Our 2D projection matching approach enables the neural network to learn more accurate structure information than using the per-pixel difference, especially for fine and thin 3D structures. Our method can recover fine 3D structures from 2D silhouette images at different resolutions, and is robust to different sampling methods and point number in irregular point supervision. Our method outperforms others under widely used benchmarks. Our code, data and models are available at https://github.com/chenchao15/2D\_projection\_matching.
Chen Chao, Zhizhong Han, Yu-Shen Liu, Matthias Zwicker [pdf]
-
Hierarchical View Predictor: Unsupervised 3D Global Feature Learning
through Hierarchical Prediction among Unordered Views -
Abstract
- Unsupervised learning of global features for 3D shape analysis is an important research challenge because it avoids manual effort for supervised information collection. In this paper, we propose a view-based deep learning model called Hierarchical View Predictor (HVP) to learn 3D shape features from unordered views in an unsupervised manner. To mine highly discriminative information from unordered views, HVP performs a novel hierarchical view prediction over a view pair, and aggregates the knowledge learned from the predictions in all view pairs into a global feature. In a view pair, we pose hierarchical view prediction as the task of hierarchically predicting a set of image patches in a current view from its complementary set of patches, and in addition, completing the current view and its opposite from any one of the two sets of patches. Hierarchical prediction, in patches to patches, patches to view and view to view, facilitates HVP to effectively learn the structure of 3D shapes from the correlation between patches in the same view and the correlation between a pair of complementary views. In addition, the employed implicit aggregation over all view pairs enables HVP to learn global features from unordered views. Our results show that HVP can outperform state-of-the-art methods under large-scale 3D shape benchmarks in shape classification and retrieval.
Zhizhong Han, Xiyang Wang, Yu-Shen Liu, Matthias Zwicker [pdf]
-
The microstructure and Ruppeiner geometry of charged anti-de Sitter
black holes in Gauss-Bonnet gravity: from the critical point to the triple
point -
Abstract
- Ruppeiner geometry has been successfully applied in the study of the black hole microstructure by combining with the small-large black hole phase transition. In this paper, we will extend the study to the triple point, where three black hole phases coexist. For the six-dimensional charged Gauss-Bonnet anti-de Sitter black hole, we thoroughly investigate the swallow tail behaviors of the Gibbs free energy and the equal area laws. After obtaining the black hole triple point, we exhibit its phase structures both in pressure-temperature and temperature-horizon radius diagrams. Quite different from the liquid-vapor phase transition, a double peak behavior is present in the temperature-horizon radius phase diagram. Then we construct the Ruppeiner geometry and calculate the corresponding normalized curvature scalar. Near the triple point, we observe multiple negatively divergent behaviors. Positive curvature scalar is observed for the small black hole with high temperature, which indicates that the repulsive interaction dominates among the microstructure. Furthermore, we consider the variation of the curvature scalar along the coexisting intermediate and large black hole curves. Combining with the observation for different fluids, the result suggests that this black hole system behaves more like the argon or methane. Our study provides a first and preliminary step towards understanding black hole microstructure near the triple point, as well as uncovering the particular properties of the Gauss-Bonnet gravity.
Shao-Wen Wei, Yu-Xiao Liu [pdf]
-
Real‐time keypoints detection for autonomous recovery of the unmanned ground vehicle -
Abstract
- The combination of a small unmanned ground vehicle (UGV) and a large unmanned carrier vehicle allows more flexibility in real applications such as rescue in dangerous scenarios. The autonomous recovery system, which is used to guide the small UGV back to the carrier vehicle, is an essential component to achieve a seamless combination of the two vehicles. This paper proposes a novel autonomous recovery framework with a low-cost monocular vision system to provide accurate positioning and attitude estimation of the UGV during navigation. First, we introduce a light-weight convolutional neural network called UGV-KPNet to detect the keypoints of the small UGV from the images captured by a monocular camera. UGV-KPNet is computationally efficient with a small number of parameters and provides pixel-level accurate keypoints detection results in real-time. Then, six degrees of freedom pose is estimated using the detected keypoints to obtain positioning and attitude information of the UGV. Besides, we are the first to create a large-scale real-world keypoints dataset of the UGV. The experimental results demonstrate that the proposed system achieves state-of-the-art performance in terms of both accuracy and speed on UGV keypoint detection, and can further boost the 6-DoF pose estimation for the UGV.
Jie Li, Sheng Zhang, Kai Han, Xia Yuan, Chunxia Zhao, Yu Liu [pdf] DOI: 10.1049/iet-ipr.2020.0864 2107.12852v1 [pdf]
-
Learning to See Through Obstructions with Layered Decomposition -
Abstract
- We present a learning-based approach for removing unwanted obstructions, such as window reflections, fence occlusions, or adherent raindrops, from a short sequence of images captured by a moving camera. Our method leverages motion differences between the background and obstructing elements to recover both layers. Specifically, we alternate between estimating dense optical flow fields of the two layers and reconstructing each layer from the flow-warped images via a deep convolutional neural network. This learning-based layer reconstruction module facilitates accommodating potential errors in the flow estimation and brittle assumptions, such as brightness consistency. We show that the proposed approach learned from synthetically generated data performs well to real images. Experimental results on numerous challenging scenarios of reflection and fence removal demonstrate the effectiveness of the proposed method.
Yu-Lun Liu, Wei-Sheng Lai, Ming-Hsuan Yang, Yung-Yu Chuang, Jia-Bin Huang [pdf]
-
Pulsed characteristic-function measurement of a thermalizing harmonic oscillator -
Abstract
- We present a method for the direct measurement of the Wigner characteristic function of a thermalizing harmonic oscillator that is completely inaccessible for control or measurement. The strategy employs a recently proposed probe-measurement-based scheme [Phys. Rev. Lett. 122, 110406 (2019)] which relies on the pulsed control of a two-level probe. We generalize this scheme to the case of a nonunitary time evolution of the target harmonic oscillator, describing its thermalization through contact to a finite-temperature environment, given in the form of a Lindblad master equation. This generalization is achieved using a superoperator formalism and yields analytical expressions for the direct measurement of the characteristic function, accounting for the decoherence during the measurement process.
Ralf Betzholz, Yu Liu, Jianming Cai Journal reference: Phys. Rev. A 104, 012421 (2021) [pdf] DOI: 10.1103/PhysRevA.104.012421
-
Layer Hall effect in a 2D topological axion antiferromagnet -
Abstract
- While ferromagnets have been known and exploited for millennia, antiferromagnets (AFMs) were only discovered in the 1930s. The elusive nature indicates AFMs' unique properties: At large scale, due to the absence of global magnetization, AFMs may appear to behave like any non-magnetic material; However, such a seemingly mundane macroscopic magnetic property is highly nontrivial at microscopic level, where opposite spin alignment within the AFM unit cell forms a rich internal structure. In topological AFMs, such an internal structure leads to a new possibility, where topology and Berry phase can acquire distinct spatial textures. Here, we study this exciting possibility in an AFM Axion insulator, even-layered MnBi$_2$Te$_4$ flakes, where spatial degrees of freedom correspond to different layers. Remarkably, we report the observation of a new type of Hall effect, the layer Hall effect, where electrons from the top and bottom layers spontaneously deflect in opposite directions. Specifically, under no net electric field, even-layered MnBi$_2$Te$_4$ shows no anomalous Hall effect (AHE); However, applying an electric field isolates the response from one layer and leads to the surprising emergence of a large layer-polarized AHE (~50%$\frac{e^2}{h}$). Such a layer Hall effect uncovers a highly rare layer-locked Berry curvature, which serves as a unique character of the space-time $\mathcal{PT}$-symmetric AFM topological insulator state. Moreover, we found that the layer-locked Berry curvature can be manipulated by the Axion field, E$\cdot$B, which drives the system between the opposite AFM states. Our results achieve previously unavailable pathways to detect and manipulate the rich internal spatial structure of fully-compensated topological AFMs. The layer-locked Berry curvature represents a first step towards spatial engineering of Berry phase, such as through layer-specific moir\'e potential.
-
Biased Tracer Reconstruction with Halo Mass Information -
Abstract
- Plenty of crucial information about our Universe is encoded in the cosmic large-scale structure (LSS). However, the extractions of these information are usually hindered by the nonlinearities of the LSS, which can be largely alleviated by various techniques known as the reconstruction. In realistic applications, the efficiencies of these methods are always degraded by many limiting factors, a quite important one being the shot noise induced by the finite number density of biased matter tracers (i.e., luminous galaxies or dark matter halos) in observations. In this work, we explore the gains of biased tracer reconstruction achieved from halo mass information, which can suppress shot noise component and dramatically improves the cross-correlation between tracer field and dark matter. To this end, we first closely study the clustering biases and the stochasticity properties of halo fields with various number densities under different weighting schemes, i.e., the uniform, mass and optimal weightings. Then, we apply the biased tracer reconstruction method to these different weighted halo fields and investigate how linear bias and observational mass scatter affect the reconstruction performance. Our results demonstrate that halo masses are critical information for significantly improving the performance of biased tracer reconstruction, indicating a great application potential for substantially promoting the precision of cosmological measurements [especially for baryon acoustic oscillations (BAO)] in the ambitious on-going and future galaxy surveys.
Yu Liu, Yu Yu, Baojiu Li Journal reference: The Astrophysical Journal Supplement Series, Volume 254, Issue 1, id.4, 16 pp. (2021) [pdf] DOI: 10.3847/1538-4365/abe868
-
$g+ig$ topological superconductivity in the 30$^o$-twisted bilayer
graphene -
Abstract
- Based on our revised perturbational-band theory, we study possible pairing states driven by interaction in the electron-doped quasicrystal 30\degree-twisted bilayer graphene. Our mean-field study on the related t-J model predicts that, the beneath-van-Hove and beyond-van-Hove low doping regimes are covered by the chiral $d+id$ and $g+ig$ topological superconductivities (TSCs) respectively. The $g+ig$-TSC possesses a pairing angular momentum 4, and hence following each effective $C_{12}$- rotation by $\Delta\phi=n\pi/6$, the pairing phase changes $4\Delta\phi$. This intriguing TSC is novel, as it belongs to a special 2D $E_4$- irreducible representation of the effective $D_{12}$ point group unique to this quasicystal and absent on periodic lattices. The Ginzburg-Landau theory suggested that the $g+ig$- TSC originates from the Josephson coupling between the $d+id$ pairings on the two mono-layers.
Yu-Bo Liu, Yongyou Zhang, Wei-Qiang Chen, Fan Yang [pdf]
-
Motion of test particle in rotating boson star -
Abstract
- Motion of a test particle plays an important role in understanding the properties of a spacetime. As a new type of the strong gravity system, boson stars could mimic black holes located at the center of galaxies. Studying the motion of a test particle in the spacetime of a rotating boson star will provide the astrophysical observable effects if a boson star is located at the center of a galaxy. In this paper, we investigate the timelike geodesic of a test particle in the background of a rotating boson star with angular number $m=(1, 2, 3)$. With the change of angular number and frequency, a rotating boson star will transform from the low rotating state to the highly relativistic rapidly rotating state, the corresponding Lense-Thirring effects will be more and more significant and it should be studied in detail. By solving the four-velocity of a test particle and integrating the geodesics, we investigate the bound orbits with a zero and nonzero angular momentum. We find that a test particle can stay more longer time in the central region of a boson star when the boson star becomes from low rotating state to highly relativistic rotating state. Such behaviors of the orbits are quite different from the orbits in a Kerr black hole, and the observable effects from these orbits will provide a rule to investigate the astrophysical compact objects in the Galactic center.
Yu-Peng Zhang, Yan-Bo Zeng, Yong-Qiang Wang, Shao-Wen Wei, Yu-Xiao Liu [pdf]
-
Ergodic numerical approximation to periodic measures of stochastic differential equations -
Abstract
- In this paper, we consider numerical approximation to periodic measure of a time periodic stochastic differential equations (SDEs) under weakly dissipative condition. For this we first study the existence of the periodic measure $\rho_t$ and the large time behaviour of $\mathcal{U}(t+s,s,x) := \mathbb{E}\phi(X_{t}^{s,x})-\int\phi d\rho_t,$ where $X_t^{s,x}$ is the solution of the SDEs and $\phi$ is a test function being smooth and of polynomial growth at infinity. We prove $\mathcal{U}$ and all its spatial derivatives decay to 0 with exponential rate on time $t$ in the sense of average on initial time $s$. We also prove the existence and the geometric ergodicity of the periodic measure of the discretized semi-flow from the Euler-Maruyama scheme and moment estimate of any order when the time step is sufficiently small (uniform for all orders). We thereafter obtain that the weak error for the numerical scheme of infinite horizon is of the order $1$ in terms of the time step. We prove that the choice of step size can be uniform for all test functions $\phi$. Subsequently we are able to estimate the average periodic measure with ergodic numerical schemes.
Chunrong Feng, Yu Liu, Huaizhong Zhao Journal reference: Journal of Computational and Applied Mathematics, 398 (2021) 113701 [pdf] DOI: 10.1016/j.cam.2021.113701
-
Heavy and light jet quenching in different collision systems at the LHC
energies -
Abstract
- Recent experiments have observed large anisotropic collective flows in high multiplicity proton-lead collisions at the Large Hadron Collider (LHC), which indicates the possible formation of mini quark-gluon plasma (QGP) in small collision systems. However, no jet quenching has been confirmed in such small systems so far. To understand this intriguing result, the system size scan experiments have been proposed to bridge the gap between large and small systems. In this work, we perform a systematic study on both heavy and light flavor jet quenching in different collision systems at the LHC energies. Using our state-of-the-art jet quenching model, which combines the next-to-leading-order perturbative QCD framework, a linear Boltzmann transport model and the (3+1)-dimensional viscous hydrodynamics simulation, we provide a good description of nuclear modification factor $R_{\rm AA}$ for charged hadrons and $D$ mesons in central and mid-central Pb+Pb and Xe+Xe collisions measured by CMS collaboration. We further predict the transverse momentum and centrality dependences of $R_{AA}$ for charged hadrons, $D$ and $B$ mesons in Pb+Pb, Xe+Xe, Ar+Ar and O+O collisions at the LHC energies. Our numerical results show a clear system size dependence for both light and heavy flavor hadron $R_{AA}$ across different collision systems. Sizable jet quenching effect is obtained for both heavy and light flavor hadrons in central O+O collisions at the LHC energies. Our study provides a significant bridge for jet quenching from large to small systems, and should be helpful for finding the smallest QGP droplet and the disappearance of QGP in relativistic nuclear collisions.
Yu-Fei Liu, Wen-Jing Xing, Xiang-Yu Wu, Guang-You Qin, Shanshan Cao, Hongxi Xing [pdf]
-
Smooth braneworld in 6-dimensional asymptotically AdS spacetime -
Abstract
- In this paper, we investigate a $6$-dimensional smooth thick braneworld model which contains a compact extra dimension and an infinite large one. The braneworld is generated by a real scalar field with a $\phi^6$ potential and the bulk is asymptotically $\text{AdS}_6$ spacetime. The geometry achieves the localization of the free $U(1)$ gauge field, which is a problem in the $5$-dimensional Randall-Sundrum-like models. In addition, we analyze the stability of the braneworld system and the localization of gravitons.
Jun-Jie Wan, Zheng-Quan Cui, Wen-Bin Feng, Yu-Xiao Liu Journal reference: JHEP 05 (2021) 017 [pdf] DOI: 10.1007/JHEP05(2021)017
-
Curvature Graph Neural Network -
Abstract
- Graph neural networks (GNNs) have achieved great success in many graph-based tasks. Much work is dedicated to empowering GNNs with the adaptive locality ability, which enables measuring the importance of neighboring nodes to the target node by a node-specific mechanism. However, the current node-specific mechanisms are deficient in distinguishing the importance of nodes in the topology structure. We believe that the structural importance of neighboring nodes is closely related to their importance in aggregation. In this paper, we introduce discrete graph curvature (the Ricci curvature) to quantify the strength of structural connection of pairwise nodes. And we propose Curvature Graph Neural Network (CGNN), which effectively improves the adaptive locality ability of GNNs by leveraging the structural property of graph curvature. To improve the adaptability of curvature to various datasets, we explicitly transform curvature into the weights of neighboring nodes by the necessary Negative Curvature Processing Module and Curvature Normalization Module. Then, we conduct numerous experiments on various synthetic datasets and real-world datasets. The experimental results on synthetic datasets show that CGNN effectively exploits the topology structure information, and the performance is improved significantly. CGNN outperforms the baselines on 5 dense node classification benchmark datasets. This study deepens the understanding of how to utilize advanced topology information and assign the importance of neighboring nodes from the perspective of graph curvature and encourages us to bridge the gap between graph theory and neural networks.
Haifeng Li, Jun Cao, Jiawei Zhu, Yu Liu, Qing Zhu, Guohua Wu [pdf]
-
Bimolecular chemistry in the ultracold regime -
Abstract
- Advances in atomic, molecular, and optical (AMO) physics techniques allowed the cooling of simple molecules down to the ultracold regime ($\lesssim$ 1 mK), and opened the opportunities to study chemical reactions with unprecedented levels of control. This review covers recent developments in studying bimolecular chemistry at ultralow temperatures. We begin with a brief overview of methods for producing, manipulating, and detecting ultracold molecules. We then survey experimental works that exploit the controllability of ultracold molecules to probe and modify their long-range interactions. Further combining the use of physical chemistry techniques, such as mass spectrometry and ion imaging, significantly improved the detection of ultracold reactions and enabled explorations of their dynamics in the short-range. We discuss a series of studies on the reaction KRb + KRb $\rightarrow$ K$_2$ + Rb$_2$ initiated below 1 $\mu$K, including the direct observation of a long-lived complex, the demonstration of product rotational state control via conserved nuclear spins, and a test of the statistical model using the complete quantum state distribution of the products.
Yu Liu, Kang-Kuen Ni [pdf] DOI: 10.1146/annurev-physchem-090419-043244 2107.01088v1 [pdf]
-
Application of radial basis functions neutral networks in spectral
functions -
Abstract
- The reconstruction of spectral function from correlation function in Euclidean space is a challenging task. In this paper, we employ the Machine Learning techniques in terms of the radial basis functions networks to reconstruct the spectral function from a finite number of correlation data. To test our method, we first generate one type of correlation data using a mock spectral function by mixing several Breit-Wigner propagators. We found that compared with other traditional methods, TSVD, Tikhonov, and MEM, our approach gives a continuous and unified reconstruction for both positive definite and negative spectral function, which is especially useful for studying the QCD phase transition. Moreover, our approach has considerably better performance in the low frequency region. This has advantages for the extraction of transport coefficients which are related to the zero frequency limit of the spectral function. With the mock data generated through a model spectral function of stress energy tensor, we find our method gives a precise and stable extraction of the transport coefficients.
Meng Zhou, Fei Gao, Jingyi Chao, Yu-Xin Liu, Huichao Song [pdf]
-
Cycle4Completion: Unpaired Point Cloud Completion using Cycle
Transformation with Missing Region Coding -
Abstract
- In this paper, we present a novel unpaired point cloud completion network, named Cycle4Completion, to infer the complete geometries from a partial 3D object. Previous unpaired completion methods merely focus on the learning of geometric correspondence from incomplete shapes to complete shapes, and ignore the learning in the reverse direction, which makes them suffer from low completion accuracy due to the limited 3D shape understanding ability. To address this problem, we propose two simultaneous cycle transformations between the latent spaces of complete shapes and incomplete ones. The insight of cycle transformation is to promote networks to understand 3D shapes by learning to generate complete or incomplete shapes from their complementary ones. Specifically, the first cycle transforms shapes from incomplete domain to complete domain, and then projects them back to the incomplete domain. This process learns the geometric characteristic of complete shapes, and maintains the shape consistency between the complete prediction and the incomplete input. Similarly, the inverse cycle transformation starts from complete domain to incomplete domain, and goes back to complete domain to learn the characteristic of incomplete shapes. We provide a comprehensive evaluation in experiments, which shows that our model with the learned bidirectional geometry correspondence outperforms state-of-the-art unpaired completion methods.
Xin Wen, Zhizhong Han, Yan-Pei Cao, Pengfei Wan, Wen Zheng, Yu-Shen Liu [pdf]
-
PMP-Net: Point Cloud Completion by Learning Multi-step Point Moving
Paths -
Abstract
- The task of point cloud completion aims to predict the missing part for an incomplete 3D shape. A widely used strategy is to generate a complete point cloud from the incomplete one. However, the unordered nature of point clouds will degrade the generation of high-quality 3D shapes, as the detailed topology and structure of discrete points are hard to be captured by the generative process only using a latent code. In this paper, we address the above problem by reconsidering the completion task from a new perspective, where we formulate the prediction as a point cloud deformation process. Specifically, we design a novel neural network, named PMP-Net, to mimic the behavior of an earth mover. It moves each point of the incomplete input to complete the point cloud, where the total distance of point moving paths (PMP) should be shortest. Therefore, PMP-Net predicts a unique point moving path for each point according to the constraint of total point moving distances. As a result, the network learns a strict and unique correspondence on point-level, which can capture the detailed topology and structure relationships between the incomplete shape and the complete target, and thus improves the quality of the predicted complete shape. We conduct comprehensive experiments on Completion3D and PCN datasets, which demonstrate our advantages over the state-of-the-art point cloud completion methods.
Xin Wen, Peng Xiang, Zhizhong Han, Yan-Pei Cao, Pengfei Wan, Wen Zheng, Yu-Shen Liu [pdf]
-
A general thermodynamic geometry approach for rotating Kerr anti-de
Sitter black holes -
Abstract
- Combining with the small-large black hole phase transition, the thermodynamic geometry has been well applied to study the microstructure for the charged AdS black hole. In this paper, we extend the geometric approach to the rotating Kerr-AdS black hole and aim to develop a general approach for the Kerr-AdS black hole. Treating the entropy and pressure as the fluctuation coordinates, we construct the Ruppeiner geometry for the Kerr-AdS black hole by making the use of the Christodoulou-Ruffini-like squared-mass formula, which is quite different from the charged case. Employing the empirical observation of the corresponding scalar curvature, we find that, for the near-extremal Kerr-AdS black hole, the repulsive interaction dominates among its microstructure. While for far-from-extremal Kerr-AdS black hole, the attractive interaction dominates. The critical phenomenon is also observed for the scalar curvature. These results uncover the characteristic microstructure of the Kerr-AdS black hole. Such general thermodynamic geometry approach is worth generalizing to other rotating AdS black holes, and more interesting microstructure is expected to be discovered.
Shao-Wen Wei, Yu-Xiao Liu [pdf]
-
Quantum phase transition in a non-Hermitian XY spin chain with global complex transverse field -
Abstract
- In this work, we investigate the quantum phase transition in a non-Hermitian XY spin chain. The phase diagram shows that the critical points of Ising phase transition expand into a critical transition zone after introducing a non-Hermitian effect. By analyzing the non-Hermitian gap and long-range correlation function, one can distinguish different phases by means of different gap features and decay properties of correlation function, a tricky problem in traditional XY model. Furthermore, the results reveal the relationship among different regions of the phase diagram, non-Hermitian energy gap and long-range correlation function.
Yu-Guo Liu, Lu Xu, Zhi Li Journal reference: J. Phys.: Condens. Matter 33 295401 (2021) [pdf] DOI: 10.1088/1361-648X/ac00dd
-
Resolving Galactic binaries in LISA data using particle swarm optimization and cross-validation -
Abstract
- The space-based gravitational wave (GW) detector LISA is expected to observe signals from a large population of compact object binaries, comprised predominantly of white dwarfs, in the Milky Way. Resolving individual sources from this population against its self-generated confusion noise poses a major data analysis problem. We present an iterative source estimation and subtraction method to address this problem based on the use of particle swarm optimization (PSO). In addition to PSO, a novel feature of the method is the cross-validation of sources estimated from the same data using different signal parameter search ranges. This is found to greatly reduce contamination by spurious sources and may prove to be a useful addition to any multi-source resolution method. Applied to a recent mock data challenge, the method is able to find $O(10^4)$ Galactic binaries across a signal frequency range of $[0.1,15]$ mHz, and, for frequency $\gtrsim 4$ mHz, reduces the residual data after subtracting out estimated signals to the instrumental noise level.
Xue-Hao Zhang, Soumya D. Mohanty, Xiao-Bo Zou, Yu-Xiao Liu Journal reference: Phys. Rev. D 104, 024023 (2021) [pdf] DOI: 10.1103/PhysRevD.104.024023
-
Detection of Long-Lived Complexes in Ultracold Atom-Molecule Collisions -
Abstract
- We investigate collisional loss in an ultracold mixture of $^{40}$K$^{87}$Rb molecules and $^{87}$Rb atoms, where chemical reactions between the two species are energetically forbidden. Through direct detection of the KRb$_{2}^{*}$ intermediate complexes formed from atom-molecule collisions, we show that a $1064$ nm laser source used for optical trapping of the sample can efficiently deplete the complex population via photo-excitation, an effect which can explain the universal two-body loss observed in the mixture. By monitoring the time-evolution of the KRb$_{2}^{*}$ population after a sudden reduction in the $1064$ nm laser intensity, we measure the lifetime of the complex ($0.39(6)$ ms), as well as the photo-excitation rate for $1064$ nm light ($0.50(3)$ $\mu$s$^{-1}($kW/cm$^{2})^{-1}$). The observed lifetime is ${\sim}10^{5}$ times longer than recent estimates based on the Rice-Ramsperger-Kassel-Marcus statistical theory, which calls for new insight to explain such a dramatic discrepancy.
Matthew A. Nichols, Yi-Xiang Liu, Lingbang Zhu, Ming-Guang Hu, Yu Liu, Kang-Kuen Ni [pdf]
-
New insight on the quark condensate beyond chiral limit -
Abstract
- With analyzing the mass function obtained by solving Dyson-Schwinger Equations, we propose a cut-off independent definition of quark condensate beyond chiral limit. With this well-defined condensate, we then analyze the evolution of the condensate and its susceptibility with the current quark mass. The susceptibility shows a critical mass in the neighborhood of the s-quark current mass, which defines a transition boundary for internal hadron dynamics.
Ling-feng Chen, Zhan Bai, Fei Gao, Yu-xin Liu [pdf]
-
FNAS: Uncertainty-Aware Fast Neural Architecture Search -
Abstract
- Reinforcement learning (RL)-based neural architecture search (NAS) generally guarantees better convergence yet suffers from the requirement of huge computational resources compared with gradient-based approaches, due to the rollout bottleneck -- exhaustive training for each sampled generation on proxy tasks. In this paper, we propose a general pipeline to accelerate the convergence of the rollout process as well as the RL process in NAS. It is motivated by the interesting observation that both the architecture and the parameter knowledge can be transferred between different experiments and even different tasks. We first introduce an uncertainty-aware critic (value function) in Proximal Policy Optimization (PPO) to utilize the architecture knowledge in previous experiments, which stabilizes the training process and reduces the searching time by 4 times. Further, an architecture knowledge pool together with a block similarity function is proposed to utilize parameter knowledge and reduces the searching time by 2 times. It is the first to introduce block-level weight sharing in RLbased NAS. The block similarity function guarantees a 100% hitting ratio with strict fairness. Besides, we show that a simply designed off-policy correction factor used in "replay buffer" in RL optimization can further reduce half of the searching time. Experiments on the Mobile Neural Architecture Search (MNAS) search space show the proposed Fast Neural Architecture Search (FNAS) accelerates standard RL-based NAS process by ~10x (e.g. ~256 2x2 TPUv2 x days / 20,000 GPU x hour -> 2,000 GPU x hour for MNAS), and guarantees better performance on various vision tasks.
Jihao Liu, Ming Zhang, Yangting Sun, Boxiao Liu, Guanglu Song, Yu Liu, Hongsheng Li [pdf]
-
Thick branes with inner structure in mimetic $f(R)$ gravity -
Abstract
- In this paper, we study the structure and gravitational resonances of thick branes generated by a mimetic scalar field in $f(R)$ gravity. We obtain several typical thick brane solutions for $f(R)=R+\alpha R^2$. To study their stability, we analyze the tensor perturbation of the metric. It is shown that any thick brane model with $df/dR>0$ is stable and the graviton zero mode can be localized on the brane for each solution, which indicates that the four-dimensional Newtonian gravity can be restored. The effect of the parameter $\alpha$ on the gravitational resonances is studied. As a brane splits into multi sub-branes, the effective potential of the tensor perturbation will have an abundant inner structure with multi-wells, and this will lead to new phenomena of the gravitational resonances.
Jing Chen, Wen-Di Guo, Yu-Xiao Liu [pdf]
-
Neural-Pull: Learning Signed Distance Functions from Point Clouds by
Learning to Pull Space onto Surfaces -
Abstract
- Reconstructing continuous surfaces from 3D point clouds is a fundamental operation in 3D geometry processing. Several recent state-of-the-art methods address this problem using neural networks to learn signed distance functions (SDFs). In this paper, we introduce \textit{Neural-Pull}, a new approach that is simple and leads to high quality SDFs. Specifically, we train a neural network to pull query 3D locations to their closest points on the surface using the predicted signed distance values and the gradient at the query locations, both of which are computed by the network itself. The pulling operation moves each query location with a stride given by the distance predicted by the network. Based on the sign of the distance, this may move the query location along or against the direction of the gradient of the SDF. This is a differentiable operation that allows us to update the signed distance value and the gradient simultaneously during training. Our outperforming results under widely used benchmarks demonstrate that we can learn SDFs more accurately and flexibly for surface reconstruction and single image reconstruction than the state-of-the-art methods.
Baorui Ma, Zhizhong Han, Yu-Shen Liu, Matthias Zwicker [pdf]
-
On the Decycling Number of Bubble-sort Star Graphs -
Abstract
- Bubble-sort star graphs are a combination of star graphs and bubble sort graphs. They are bipartite graphs and also form a family of Cayley graphs. The decycling number of a graph is the minimum number of vertices whose removal from the graph results in an acyclic subgraph. In this paper, we prove the decycling number D(n) of an n-dimensional bubble-sort star graph for n <= 5. We also show D(n) satisfies the inequalities for n >= 6.
Yu-Zhe Liu, Shyue-Ming Tang, Jou-Ming Chang [pdf]
-
Sparsity Prior Regularized Q-learning for Sparse Action Tasks -
Abstract
- In many decision-making tasks, some specific actions are limited in their frequency or total amounts, such as "fire" in the gunfight game and "buy/sell" in the stock trading. We name such actions as "sparse action". Sparse action often plays a crucial role in achieving good performance. However, their Q-values, estimated by \emph{classical Bellman update}, usually suffer from a large estimation error due to the sparsity of their samples. The \emph{greedy} policy could be greatly misled by the biased Q-function and takes sparse action aggressively, which leads to a huge sub-optimality. This paper constructs a reference distribution that assigns a low probability to sparse action and proposes a regularized objective with an explicit constraint to the reference distribution. Furthermore, we derive a regularized Bellman operator and a regularized optimal policy that can slow down the propagation of error and guide the agent to take sparse action more carefully. The experiment results demonstrate that our method achieves state-of-the-art performance on typical sparse action tasks.
Jing-Cheng Pang, Tian Xu, Sheng-Yi Jiang, Yu-Ren Liu, Yang Yu [pdf]
-
Linking continuum and lattice quark mass functions via an effective
charge -
Abstract
- The quark mass function is computed both by solving the quark propagator Dyson-Schwinger equation and from lattice simulations implementing overlap and Domain-Wall fermion actions for valence and sea quarks, respectively. The results are confronted and seen to produce a very congruent picture, showing a remarkable agreement for the explored range of current-quark masses. The effective running-interaction is based on a process-independent charge rooted on a particular truncation of the Dyson-Schwinger equations in the gauge sector, establishing thus a link from there to the quark sector and inspiring a correlation between the emergence of gluon and hadron masses.
Lei Chang, Yu-Bin Liu, Khépani Raya, J. Rodríguez-Quintero, Yi-Bo Yang [pdf]
-
The impact and recovery of asteroid 2018 LA -
Abstract
- The June 2, 2018, impact of asteroid 2018 LA over Botswana is only the second asteroid detected in space prior to impacting over land. Here, we report on the successful recovery of meteorites. Additional astrometric data refine the approach orbit and define the spin period and shape of the asteroid. Video observations of the fireball constrain the asteroid's position in its orbit and were used to triangulate the location of the fireball's main flare over the Central Kalahari Game Reserve. 23 meteorites were recovered. A consortium study of eight of these classifies Motopi Pan as a HED polymict breccia derived from howardite, cumulate and basaltic eucrite, and diogenite lithologies. Before impact, 2018 LA was a solid rock of about 156 cm diameter with high bulk density about 2.85 g/cm3, a relatively low albedo pV about 0.25, no significant opposition effect on the asteroid brightness, and an impact kinetic energy of about 0.2 kt. The orbit of 2018 LA is consistent with an origin at Vesta (or its Vestoids) and delivery into an Earth-impacting orbit via the nu_6 resonance. The impact that ejected 2018 LA in an orbit towards Earth occurred 22.8 +/- 3.8 Ma ago. Zircons record a concordant U-Pb age of 4563 +/- 11 Ma and a consistent 207Pb/206Pb age of 4563 +/- 6 Ma. A much younger Pb-Pb phosphate resetting age of 4234 +/- 41 Ma was found. From this impact chronology, we discuss what is the possible source crater of Motopi Pan and the age of Vesta's Veneneia impact basin.
-
QCD phase transition and equation of state of stellar strong interaction matter via Dyson–Schwinger equation approach -
Abstract
- We study the phase structure and phase transition of cold dense QCD matter via the Dyson-Schwinger equation approach. We take the rainbow approximation and the Gaussian-type gluon model. In order to guarantee that the quark number density begins to appear at the nuclear liquid-gas phase transition chemical potential, we propose a chemical potential dependent modification factor for the gluon model. We find that for the iso-symmetric quark matter, the modification reduces the chemical potential of the phase coexistence region of the first--order phase transition. We also implement the relativistic mean field theory to describe the hadron matter, and make use of the Maxwell and Gibbs construction method to study the phase transition of beta--equilibrium and charge neutral matter in compact stars. The results show that the phase transition will not happen in case of the Gaussian--type gluon model without any modification. The results also indicate that the upper boundary of the coexistence region should be larger than the current Nambu solution existing region. We also calculate the mass-radius relation of the compact stars, and find that the hadron-quark phase transition happens at too high chemical potential so that the maximum mass of the compact star is hardly affected by the hadron-quark phase transition.
Zhan Bai, Yu-xin Liu [pdf] DOI: 10.1140/epjc/s10052-021-09423-y 2105.03947v1 [pdf]
-
First-principles study of the role of surface in the heavy-fermion compound
-
Abstract
- In the heavy fermion materials, the characteristic energy scales of many exotic strongly correlated phenomena (Kondo effect, magnetic order, superconductivity, etc.) are at milli-electron-volt order, implying that the heavy fermion materials are surface sensitive. Here, we investigate the electronic structures for Si- and Ce-terminated surfaces of CeRh$_2$Si$_2$ by first-principles methods. Our research reveals three notable impacts of surface effects on electronic structures, which are consistent with recent angle-resolved photoemission spectroscopy (ARPES) experiments. Firstly, the relaxation of surface crystal structures changes the relative position of Fermi level, adjusts the dispersion of bands and enhances the Kondo resonance. Secondly, the decrease of the hybridization between the Ce-4$f$ and conduction electrons in the surface layer leads to a weaker Kondo resonance peak and the shift of spin-orbit bands. Thirdly, the variation of crystal electric field around surface Ce atoms affects the splitting of Kondo resonance peaks, and also pushes down the lower-Hubbard bands of surface 4$f$ electrons. Moreover, we find the characteristic of bulk's lower-Hubbard bands, which was overlooked in previous works. Our investigation suggests that these surface effects are potentially important and highlighted in the future researches on properties of strongly correlated materials.
Yue-Chao Wang, Yuan-Ji Xu, Yu Liu, Xing-Jie Han, Xie-Gang Zhu, Yi-feng Yang, Yan Bi, Hai-Feng Liu, Hai-Feng Song Journal reference: Phys. Rev. B 103, 165140 (2021) [pdf] DOI: 10.1103/PhysRevB.103.165140
-
Testing the microstructure of
-
Abstract
- Understanding black hole microstructure via the thermodynamic geometry can provide us with more deeper insight into black hole thermodynamics in modified gravities. In this paper, we study the black hole phase transition and Ruppeiner geometry for the $d$-dimensional charged Gauss-Bonnet anti-de Sitter black holes. The results show that the small-large black hole phase transition is universal in this gravity. By reducing the thermodynamic quantities with the black hole charge, we clearly exhibit the phase diagrams in different parameter spaces. Of particular interest is that the radius of the black hole horizon can act as the order parameter to characterize the black hole phase transition. We also disclose that different from the five-dimensional neutral black holes, the charged ones allow the repulsive interaction among its microstructure for small black hole of higher temperature. Another significant difference between them is that the microscopic interaction changes during the small-large black hole phase transition for the charged case, where the black hole microstructure undergoes a sudden change. These results are helpful for peeking into the microstructure of charged black holes in the Gauss-Bonnet gravity.
Shao-Wen Wei, Yu-Xiao Liu Journal reference: Phys. Rev. D 104, 024062 (2021) [pdf] DOI: 10.1103/PhysRevD.104.024062
-
Dynamics and kinetics of phase transition for Kerr AdS black hole on
free energy landscape -
Abstract
- By treating the black hole event horizon as a stochastic thermal fluctuating variable for small-large black hole phase transition, we investigate the dynamical process of phase transition for the Kerr AdS black holes on free energy landscape. We find that the extremal points of the off-shell Gibbs free energy correspond to physical black holes. For small-large black hole phase transition, the off-shell Gibbs free energy exhibits a double well behavior with the same depth. Contrary to previous research for the dynamics of phase transition for the Kerr-Newman AdS family black holes on free energy landscape, we find that there is a lower bound for the order parameter and the lower bound corresponds to extremal black holes. In particular, the off-shell Gibbs free energy is zero instead of divergent as previous work suggested for vanishing black hole horizon radius, which corresponds to the Gibbs free energy of thermal AdS space. The investigation for the evolution of the probability distribution for the phase transition indicates that the initial stable small (large) black hole tends to switch to stable large (small) black hole. Increasing the temperature along the coexistence curve, the switching process becomes faster and the probability distribution reaches the final stationary Boltzmann distribution at a shorter time. The distribution of the first passage time indicates the time scale of the small-large black hole phase transition, and the peak of the distribution becomes sharper and shifts to the left with the increase of temperature along the coexistence curve. This suggests that a considerable first passage process occurs at a shorter time for higher temperature.
Si-Jiang Yang, Run Zhou, Shao-Wen Wei, Yu-Xiao Liu [pdf]
-
Large-Momentum Effective Theory -
Abstract
- Since the parton model was introduced by Feynman more than fifty years ago, we have learned much about the partonic structure of the proton through a large body of high-energy experimental data and dedicated global fits. However, calculating the partonic observables such as parton distribution function (PDFs) from the fundamental theory of strong interactions, QCD, has made limited progress. Recently, the authors have advocated a formalism, large-momentum effective theory (LaMET), through which one can extract parton physics from the properties of the proton travelling at a moderate boost-factor, e.g., $\gamma\sim (2-5)$. The key observation behind this approach is that Lorentz symmetry allows the standard formalism of partons in terms of light-front operators to be replaced by an equivalent one with large-momentum states and time-independent operators of a universality class. With LaMET, the PDFs, generalized PDFs or GPDs, transverse-momentum-dependent PDFs, and light-front wave functions can all be extracted in principle from lattice simulations of QCD (or other non-perturbative methods) through standard effective field theory matching and running. Future lattice QCD calculations with exa-scale computational facilities can help to understand the experimental data related to the hadronic structure, including those from the upcoming Electron-Ion Colliders dedicated to exploring the partonic landscape of the proton. Here we review the progress made in the past few years in development of the LaMET formalism and its applications, particularly on the demonstration of its effectiveness from initial lattice QCD simulations.
Xiangdong Ji, Yu-Sheng Liu, Yizhuang Liu, Jian-Hui Zhang, Yong Zhao [pdf]
-
A Novel Unified Stereo Stimuli based Binocular Eye-Tracking System for
Accurate 3D Gaze Estimation -
Abstract
- In addition to the high cost and complex setup, the main reason for the limitation of the three-dimensional (3D) display is the problem of accurately estimating the user's current point-of-gaze (PoG) in a 3D space. In this paper, we present a novel noncontact technique for the PoG estimation in a stereoscopic environment, which integrates a 3D stereoscopic display system and an eye-tracking system. The 3D stereoscopic display system can provide users with a friendly and immersive high-definition viewing experience without wearing any equipment. To accurately locate the user's 3D PoG in the field of view, we build a regression-based 3D eye-tracking model with the eye movement data and stereo stimulus videos as input. Besides, to train an optimal regression model, we also design and annotate a dataset that contains 30 users' eye-tracking data corresponding to two designed stereo test scenes. Innovatively, this dataset introduces feature vectors between eye region landmarks for the gaze vector estimation and a combined feature set for the gaze depth estimation. Moreover, five traditional regression models are trained and evaluated based on this dataset. Experimental results show that the average errors of the 3D PoG are about 0.90~cm on the X-axis, 0.83~cm on the Y-axis, and 1.48~cm$/$0.12~m along the Z-axis with the scene-depth range in 75~cm$/$8~m, respectively.
Sunjing Lin, Yu Liu, Shaochu Wang, Chang Li, Han Wang [pdf]
-
Actor-Context-Actor Relation Network for Spatio-Temporal Action
Localization -
Abstract
- Localizing persons and recognizing their actions from videos is a challenging task towards high-level video understanding. Recent advances have been achieved by modeling direct pairwise relations between entities. In this paper, we take one step further, not only model direct relations between pairs but also take into account indirect higher-order relations established upon multiple elements. We propose to explicitly model the Actor-Context-Actor Relation, which is the relation between two actors based on their interactions with the context. To this end, we design an Actor-Context-Actor Relation Network (ACAR-Net) which builds upon a novel High-order Relation Reasoning Operator and an Actor-Context Feature Bank to enable indirect relation reasoning for spatio-temporal action localization. Experiments on AVA and UCF101-24 datasets show the advantages of modeling actor-context-actor relations, and visualization of attention maps further verifies that our model is capable of finding relevant higher-order relations to support action detection. Notably, our method ranks first in the AVA-Kineticsaction localization task of ActivityNet Challenge 2020, out-performing other entries by a significant margin (+6.71mAP). Training code and models will be available at https://github.com/Siyu-C/ACAR-Net.
Junting Pan, Siyu Chen, Mike Zheng Shou, Yu Liu, Jing Shao, Hongsheng Li [pdf]
-
Role-Aware Modeling for N-ary Relational Knowledge Bases -
Abstract
- N-ary relational knowledge bases (KBs) represent knowledge with binary and beyond-binary relational facts. Especially, in an n-ary relational fact, the involved entities play different roles, e.g., the ternary relation PlayCharacterIn consists of three roles, ACTOR, CHARACTER and MOVIE. However, existing approaches are often directly extended from binary relational KBs, i.e., knowledge graphs, while missing the important semantic property of role. Therefore, we start from the role level, and propose a Role-Aware Modeling, RAM for short, for facts in n-ary relational KBs. RAM explores a latent space that contains basis vectors, and represents roles by linear combinations of these vectors. This way encourages semantically related roles to have close representations. RAM further introduces a pattern matrix that captures the compatibility between the role and all involved entities. To this end, it presents a multilinear scoring function to measure the plausibility of a fact composed by certain roles and entities. We show that RAM achieves both theoretical full expressiveness and computation efficiency, which also provides an elegant generalization for approaches in binary relational KBs. Experiments demonstrate that RAM outperforms representative baselines on both n-ary and binary relational datasets.
Yu Liu, Quanming Yao, Yong Li [pdf]
-
Integrating Information Theory and Adversarial Learning for Cross-modal
Retrieval -
Abstract
- Accurately matching visual and textual data in cross-modal retrieval has been widely studied in the multimedia community. To address these challenges posited by the heterogeneity gap and the semantic gap, we propose integrating Shannon information theory and adversarial learning. In terms of the heterogeneity gap, we integrate modality classification and information entropy maximization adversarially. For this purpose, a modality classifier (as a discriminator) is built to distinguish the text and image modalities according to their different statistical properties. This discriminator uses its output probabilities to compute Shannon information entropy, which measures the uncertainty of the modality classification it performs. Moreover, feature encoders (as a generator) project uni-modal features into a commonly shared space and attempt to fool the discriminator by maximizing its output information entropy. Thus, maximizing information entropy gradually reduces the distribution discrepancy of cross-modal features, thereby achieving a domain confusion state where the discriminator cannot classify two modalities confidently. To reduce the semantic gap, Kullback-Leibler (KL) divergence and bi-directional triplet loss are used to associate the intra- and inter-modality similarity between features in the shared space. Furthermore, a regularization term based on KL-divergence with temperature scaling is used to calibrate the biased label classifier caused by the data imbalance issue. Extensive experiments with four deep models on four benchmarks are conducted to demonstrate the effectiveness of the proposed approach.
Wei Chen, Yu Liu, Erwin M. Bakker, Michael S. Lew [pdf]
-
Self-supervised Video Representation Learning by Context and Motion
Decoupling -
Abstract
- A key challenge in self-supervised video representation learning is how to effectively capture motion information besides context bias. While most existing works implicitly achieve this with video-specific pretext tasks (e.g., predicting clip orders, time arrows, and paces), we develop a method that explicitly decouples motion supervision from context bias through a carefully designed pretext task. Specifically, we take the keyframes and motion vectors in compressed videos (e.g., in H.264 format) as the supervision sources for context and motion, respectively, which can be efficiently extracted at over 500 fps on the CPU. Then we design two pretext tasks that are jointly optimized: a context matching task where a pairwise contrastive loss is cast between video clip and keyframe features; and a motion prediction task where clip features, passed through an encoder-decoder network, are used to estimate motion features in a near future. These two tasks use a shared video backbone and separate MLP heads. Experiments show that our approach improves the quality of the learned video representation over previous works, where we obtain absolute gains of 16.0% and 11.1% in video retrieval recall on UCF101 and HMDB51, respectively. Moreover, we find the motion prediction to be a strong regularization for video networks, where using it as an auxiliary task improves the accuracy of action recognition with a margin of 7.4%~13.8%.
Lianghua Huang, Yu Liu, Bin Wang, Pan Pan, Yinghui Xu, Rong Jin [pdf]
-
MulDE: Multi-teacher Knowledge Distillation for Low-dimensional Knowledge Graph Embeddings -
Abstract
- Link prediction based on knowledge graph embeddings (KGE) aims to predict new triples to automatically construct knowledge graphs (KGs). However, recent KGE models achieve performance improvements by excessively increasing the embedding dimensions, which may cause enormous training costs and require more storage space. In this paper, instead of training high-dimensional models, we propose MulDE, a novel knowledge distillation framework, which includes multiple low-dimensional hyperbolic KGE models as teachers and two student components, namely Junior and Senior. Under a novel iterative distillation strategy, the Junior component, a low-dimensional KGE model, asks teachers actively based on its preliminary prediction results, and the Senior component integrates teachers' knowledge adaptively to train the Junior component based on two mechanisms: relation-specific scaling and contrast attention. The experimental results show that MulDE can effectively improve the performance and training speed of low-dimensional KGE models. The distilled 32-dimensional model is competitive compared to the state-of-the-art high-dimensional methods on several widely-used datasets.
Kai Wang, Yu Liu, Qian Ma, Quan Z. Sheng [pdf] DOI: 10.1145/3442381.3449898 2010.07152v4 [pdf]
-
Dissipative Topological Phase Transition with Strong System-Environment
Coupling -
Abstract
- A primary motivation for studying topological matter regards the protection of topological order from its environment. In this work, we study a topological emitter array coupled to an electromagnetic environment. The photon-emitter coupling produces nonlocal interactions between emitters. Using periodic boundary conditions for all ranges of environment-induced interactions, chiral symmetry inherent to the emitter array is preserved and protects the topological phase. A topological phase transition occurs at a critical photon-emitter coupling which is related to the energy spectrum width of the emitter array. It produces a band touching with parabolic dispersion, distinct to the linear one without considering the environment. Interestingly, the critical point nontrivially changes dissipation rates of edge states, yielding dissipative topological phase transition. In the protected topological phase, edge states suffer from environment-induced dissipation for weak photon-emitter coupling. However, strong coupling leads to dissipationless edge states. Our work presents a way to study topological criticality in open quantum systems.
Wei Nie, Mauro Antezza, Yu-xi Liu, Franco Nori [pdf]
-
High-efficiency Euclidean-based Models for Low-dimensional Knowledge
Graph Embeddings -
Abstract
- Recent knowledge graph embedding (KGE) models based on hyperbolic geometry have shown great potential in a low-dimensional embedding space. However, the necessity of hyperbolic space in KGE is still questionable, because the calculation based on hyperbolic geometry is much more complicated than Euclidean operations. In this paper, based on the state-of-the-art hyperbolic-based model RotH, we develop two lightweight Euclidean-based models, called RotL and Rot2L. The RotL model simplifies the hyperbolic operations while keeping the flexible normalization effect. Utilizing a novel two-layer stacked transformation and based on RotL, the Rot2L model obtains an improved representation capability, yet costs fewer parameters and calculations than RotH. The experiments on link prediction show that Rot2L achieves the state-of-the-art performance on two widely-used datasets in low-dimensional knowledge graph embeddings. Furthermore, RotL achieves similar performance as RotH but only requires half of the training time.
Kai Wang, Yu Liu, Quan Z. Sheng [pdf]
-
Lifelong Person Re-Identification via Adaptive Knowledge Accumulation -
Abstract
- Person ReID methods always learn through a stationary domain that is fixed by the choice of a given dataset. In many contexts (e.g., lifelong learning), those methods are ineffective because the domain is continually changing in which case incremental learning over multiple domains is required potentially. In this work we explore a new and challenging ReID task, namely lifelong person re-identification (LReID), which enables to learn continuously across multiple domains and even generalise on new and unseen domains. Following the cognitive processes in the human brain, we design an Adaptive Knowledge Accumulation (AKA) framework that is endowed with two crucial abilities: knowledge representation and knowledge operation. Our method alleviates catastrophic forgetting on seen domains and demonstrates the ability to generalize to unseen domains. Correspondingly, we also provide a new and large-scale benchmark for LReID. Extensive experiments demonstrate our method outperforms other competitors by a margin of 5.8% mAP in generalising evaluation.
Nan Pu, Wei Chen, Yu Liu, Erwin M. Bakker, Michael S. Lew [pdf]
-
Topology-Enhanced Nonreciprocal Scattering and Photon Absorption in a Waveguide -
Abstract
- Topological matter and topological optics have been studied in many systems, with promising applications in materials science and photonics technology. These advances motivate the study of the interaction between topological matter and light, as well as topological protection in light-matter interactions. In this work, we study a waveguide-interfaced topological atom array. The light-matter interaction is nontrivially modified by topology, yielding novel optical phenomena. We find topology-enhanced photon absorption from the waveguide for large Purcell factor, i.e., $\Gamma/\Gamma_0\gg 1$, where $\Gamma$ and $\Gamma_0$ are the atomic decays to waveguide and environment, respectively. To understand this unconventional photon absorption, we propose a multi-channel scattering approach and study the interaction spectra for edge- and bulk-state channels. We find that, by breaking inversion and time-reversal symmetries, optical anisotropy is enabled for reflection process, but the transmission is isotropic. Through a perturbation analysis of the edge-state channel, we show that the anisotropy in the reflection process originates from the waveguide-mediated non-Hermitian interaction. However, the inversion symmetry in the non-Hermitian interaction makes the transmission isotropic. At a topology-protected atomic spacing, the subradiant edge state exhibits huge anisotropy. Due to the interplay between edge- and bulk-state channels, a large topological bandgap enhances nonreciprocal reflection of photons in the waveguide for weakly broken time-reversal symmetry, i.e., $\Gamma_0/\Gamma\ll 1$, producing complete photon absorption. We show that our proposal can be implemented in superconducting quantum circuits. The topology-enhanced photon absorption is useful for quantum detection. This work shows the potential to manipulate light with topological quantum matter.
Wei Nie, Tao Shi, Franco Nori, Yu-xi Liu Journal reference: Phys. Rev. Applied 15, 044041 (2021) [pdf] DOI: 10.1103/PhysRevApplied.15.044041
-
Boundary effect and dressed states of a giant atom in a topological
waveguide -
Abstract
- The interaction between the quantum emitter and topological photonic system makes the photon behave in exotic ways. We here study the properties of a giant atom coupled to two sites of a one-dimensional topological waveguide, which is described by the Su-Schrieffer-Heeger (SSH) chain. We find that the giant atom can act as an effective boundary and induce the chiral zero modes, which are similar to those in the SSH model with open boundary, for the waveguide under the periodical boundary. Except for the boundary effect, we also find that the giant atom can lift energy degeneracy inside the energy bands of the SSH chain and adjust spatial symmetry of the photon distributions for the states of the dressed giant atom and waveguide. That is, the giant atom can be used to change the properties of the topological environment. Our work may stimulate more studies on the interaction between matter and topological environment.
Weijun Cheng, Zhihai Wang, Yu-xi Liu [pdf]
-
ACDnet: An action detection network for real-time edge computing based on flow-guided feature approximation and memory aggregation -
Abstract
- Interpreting human actions requires understanding the spatial and temporal context of the scenes. State-of-the-art action detectors based on Convolutional Neural Network (CNN) have demonstrated remarkable results by adopting two-stream or 3D CNN architectures. However, these methods typically operate in a non-real-time, ofline fashion due to system complexity to reason spatio-temporal information. Consequently, their high computational cost is not compliant with emerging real-world scenarios such as service robots or public surveillance where detection needs to take place at resource-limited edge devices. In this paper, we propose ACDnet, a compact action detection network targeting real-time edge computing which addresses both efficiency and accuracy. It intelligently exploits the temporal coherence between successive video frames to approximate their CNN features rather than naively extracting them. It also integrates memory feature aggregation from past video frames to enhance current detection stability, implicitly modeling long temporal cues over time. Experiments conducted on the public benchmark datasets UCF-24 and JHMDB-21 demonstrate that ACDnet, when integrated with the SSD detector, can robustly achieve detection well above real-time (75 FPS). At the same time, it retains reasonable accuracy (70.92 and 49.53 frame mAP) compared to other top-performing methods using far heavier configurations. Codes will be available at https://github.com/dginhac/ACDnet.
Yu Liu, Fan Yang, Dominique Ginhac Journal reference: Pattern Recognition Letters, 145 , 118-126, 2021 [pdf] DOI: 10.1016/j.patrec.2021.02.001
-
Phase-Controlled Pathway Interferences and Switchable Fast-Slow Light in a Cavity-Magnon Polariton System -
Abstract
- We study the phase controlled transmission properties in a compound system consisting of a 3D copper cavity and an yttrium iron garnet (YIG) sphere. By tuning the relative phase of the magnon pumping and cavity probe tones, constructive and destructive interferences occur periodically, which strongly modify both the cavity field transmission spectra and the group delay of light. Moreover, the tunable amplitude ratio between pump-probe tones allows us to further improve the signal absorption or amplification, accompanied by either significantly enhanced optical advance or delay. Both the phase and amplitude-ratio can be used to realize in-situ tunable and switchable fast-slow light. The tunable phase and amplitude-ratio lead to the zero reflection of the transmitted light and an abrupt fast-slow light transition. Our results confirm that direct magnon pumping through the coupling loops provides a versatile route to achieve controllable signal transmission, storage, and communication, which can be further expanded to the quantum regime, realizing coherent-state processing or quantum-limited precise measurements.
Jie Zhao, Longhao Wu, Tiefu Li, Yu-xi Liu, Franco Nori, Yulong Liu, Jiangfeng Du Journal reference: Phys. Rev. Applied 15, 024056 (2021) [pdf] DOI: 10.1103/PhysRevApplied.15.024056
-
Sieve Methods in Random Graph Theory -
Abstract
- In this paper, we apply the Turan sieve and the simple sieve developed by R. Murty and the first author to study problems in random graph theory. In particular, we obtain upper and lower bounds on the probability of a graph on n vertices having diameter 2 (or diameter 3 in the case of bipartite graphs) with edge probability p(n) where the edges are chosen independently . An interesting feature revealed in these results is that the Turan sieve and the simple sieve `almost completely' complement each other. As a corollary to our result, we note that the probability of a random graph having diameter 2 approaches 1 as n approaches infinity for constant edge probability p(n)=1/2. This is an appendix of a shorter version of this paper.
Yu-Ru Liu, J. C. Saunders [pdf]
-
Two-dimensional charge order stabilized in clean polytype heterostructures -
Abstract
- Strong evidence suggests that transformative correlated electron behavior may exist only in unrealized clean-limit 2D materials such as 1T-TaS2. Unfortunately, experiment and theory suggest that extrinsic disorder in free standing 2D layers impedes correlation-driven quantum behavior. Here we demonstrate a new route to realizing fragile 2D quantum states through epitaxial polytype engineering of van der Waals materials. The isolation of truly 2D charge density waves (CDWs) between metallic layers stabilizes commensurate long-range order and lifts the coupling between neighboring CDW layers to restore mirror symmetries via interlayer CDW twinning. The twinned-commensurate charge density wave (tC-CDW) reported herein has a single metal-insulator phase transition at ~350 K as measured structurally and electronically. Fast in-situ transmission electron microscopy and scanned nanobeam diffraction map the formation of tC-CDWs. This work introduces epitaxial polytype engineering of van der Waals materials to access latent 2D ground states distinct from conventional 2D fabrication.
Suk Hyun Sung, Noah Schnitzer, Steve Novakov, Ismail El Baggari, Xiangpeng Luo, Jiseok Gim, Nguyen Vu, Zidong Li, Todd Brintlinger, Yu Liu, Wenjian Lu, Yuping Sun, Parag Deotare, Kai Sun, Liuyan Zhao, Lena F. Kourkoutis, John T. Heron, Robert Hovden [pdf] DOI: 10.1017/S1431927621003469 2102.09079v1 [pdf]
-
A Possible Kilonova Powered by Magnetic Wind from a Newborn Black Hole -
Abstract
- The merger of binary neutron stars (NS-NS) as the progenitor of short Gamma-ray bursts (GRBs) has been confirmed by the discovery of the association of the gravitational wave (GW) event GW170817 with GRB 170817A. However, the merger product of binary NS remains an open question. An X-ray plateau followed by a steep decay ("internal plateau") has been found in some short GRBs, implying that a supra-massive magnetar operates as the merger remnant and then collapses into a newborn black hole (BH) at the end of the plateau. X-ray bump or second-plateau following the "internal plateau" is considered as the expected signature from the fallback accretion onto this newborn BH through Blandford-Znajek mechanism (BZ). At the same time, a nearly isotropic wind driven by Blandford-Paynemechanism (BP) from the newborn BH's disk can produce a bright kilonova. Therefore, the bright kilonova observation for a short GRB with "internal plateau" (and followed by X-ray bump or second-plateau) provides further evidence for this scenario. In this paper, we find that GRB 160821B is a candidate of such a case, and the kilonova emission of GRB 160821B is possibly powered by the BP wind from a newborn BH. Future GW detection of GRB 160821B-like events may provide further support to this scenario, enable us to investigate the properties of the magnetar and the newborn BH, and constrain the equation of state of neutron stars.
Shuai-Bing Ma, Wei Xie, Bin Liao, Bin-Bin Zhang, Hou-Jun Lü, Yu Liu, Wei-Hua Lei [pdf] DOI: 10.3847/1538-4357/abe71b 2010.01338v2 [pdf]
-
Understanding Bounding Functions in Safety-Critical UAV Software -
Abstract
- Unmanned Aerial Vehicles (UAVs) are an emerging computation platform known for their safety-critical need. In this paper, we conduct an empirical study on a widely used open-source UAV software framework, Paparazzi, with the goal of understanding the safety-critical concerns of UAV software from a bottom-up developer-in-the-field perspective. We set our focus on the use of Bounding Functions (BFs), the runtime checks injected by Paparazzi developers on the range of variables. Through an in-depth analysis on BFs in the Paparazzi autopilot software, we found a large number of them (109 instances) are used to bound safety-critical variables essential to the cyber-physical nature of the UAV, such as its thrust, its speed, and its sensor values. The novel contributions of this study are two fold. First, we take a static approach to classify all BF instances, presenting a novel datatype-based 5-category taxonomy with fine-grained insight on the role of BFs in ensuring the safety of UAV systems. Second, we dynamically evaluate the impact of the BF uses through a differential approach, establishing the UAV behavioral difference with and without BFs. The two-pronged static and dynamic approach together illuminates a rarely studied design space of safety-critical UAV software systems.
Xiaozhou Liang, John Henry Burns, Joseph Sanchez, Karthik Dantu, Lukasz Ziarek, Yu David Liu [pdf]
-
Corrigendum to "Hardy Spaces $H_{\mathcal L}^1({\mathbb R}^n)$
Associated to Schrödinger Type Operators $(-Δ)^2+V^2$" [Houston J.
Math 36 (4) (2010), 1067-1095] -
Abstract
- We rectify an incorrect citation of the reference in obtaining the Gaussian upper bound for heat kernels of the Schr\"odinger type operators $(-\Delta)^2+V^2$.
Jun Cao, Yu Liu, Dachun Yang [pdf]
-
Train a One-Million-Way Instance Classifier for Unsupervised Visual
Representation Learning -
Abstract
- This paper presents a simple unsupervised visual representation learning method with a pretext task of discriminating all images in a dataset using a parametric, instance-level classifier. The overall framework is a replica of a supervised classification model, where semantic classes (e.g., dog, bird, and ship) are replaced by instance IDs. However, scaling up the classification task from thousands of semantic labels to millions of instance labels brings specific challenges including 1) the large-scale softmax computation; 2) the slow convergence due to the infrequent visiting of instance samples; and 3) the massive number of negative classes that can be noisy. This work presents several novel techniques to handle these difficulties. First, we introduce a hybrid parallel training framework to make large-scale training feasible. Second, we present a raw-feature initialization mechanism for classification weights, which we assume offers a contrastive prior for instance discrimination and can clearly speed up converge in our experiments. Finally, we propose to smooth the labels of a few hardest classes to avoid optimizing over very similar negative pairs. While being conceptually simple, our framework achieves competitive or superior performance compared to state-of-the-art unsupervised approaches, i.e., SimCLR, MoCoV2, and PIC under ImageNet linear evaluation protocol and on several downstream visual tasks, verifying that full instance classification is a strong pretraining technique for many semantic visual tasks.
Yu Liu, Lianghua Huang, Pan Pan, Bin Wang, Yinghui Xu, Rong Jin [pdf]
-
Two Quasi-periodic Fast-propagating Magnetosonic Wave Events Observed in Active Region NOAA 11167 -
Abstract
- We report a detailed observational study of two quasi-periodic fast-propagating (QFP) magnetosonic wave events occurred on 2011 March 09 and 10, respectively. Interestingly, both the two events have two wave trains (WTs): one main and strong (WT-1) whereas the second appears small and weak (WT-2). Peculiar and common characteristics of the two events are observed, namely: 1) the two QFP waves are accompanied with brightenings during the whole stage of the eruptions; 2) both the two main wave trains are nearly propagating along the same direction; 3) EUV waves are found to be associated with the two events. Investigating various aspects of the target events, we argue that: 1) the second event is accompanied with a flux rope eruption during the whole stage; 2) the second event eruption produces a new filament-like (FL) dark feature; 3) the ripples of the two WT-2 QFP waves seem to result from different triggering mechanisms. Based on the obtained observational results, we propose that the funnel-like coronal loop system is indeed playing an important role in the two WT-1 QFP waves. The development of the second WT-2 QFP wave can be explained as due to the dispersion of the main EUV front. The co-existence of the two events offer thereby a significant opportunity to reveal what driving mechanisms and structures are tightly related to the waves.
Yuhu Miao, Yu Liu, A. Elmhamdi, A. S. Kordi, Y. D. Shen, Rehab Al-Shammari, Khaled Al-Mosabeh, Chaowei Jiang, Ding Yuan [pdf] DOI: 10.3847/1538-4357/ab655f 1912.11792v2 [pdf]
-
Deep Image Retrieval: A Survey -
Abstract
- In recent years a vast amount of visual content has been generated and shared from various fields, such as social media platforms, medical images, and robotics. This abundance of content creation and sharing has introduced new challenges. In particular, searching databases for similar content, i.e.content based image retrieval (CBIR), is a long-established research area, and more efficient and accurate methods are needed for real time retrieval. Artificial intelligence has made progress in CBIR and has significantly facilitated the process of intelligent search. In this survey we organize and review recent CBIR works that are developed based on deep learning algorithms and techniques, including insights and techniques from recent papers. We identify and present the commonly-used benchmarks and evaluation methods used in the field. We collect common challenges and propose promising future directions. More specifically, we focus on image retrieval with deep learning and organize the state of the art methods according to the types of deep network structure, deep features, feature enhancement methods, and network fine-tuning strategies. Our survey considers a wide variety of recent methods, aiming to promote a global view of the field of instance-based CBIR.
Wei Chen, Yu Liu, Weiping Wang, Erwin Bakker, Theodoros Georgiou, Paul Fieguth, Li Liu, Michael S. Lew [pdf]
-
Observing dynamic oscillatory behavior of triple points among black hole
thermodynamic phase transitions -
Abstract
- Understanding the dynamic process of black hole thermodynamic phase transitions at a triple point is a huge challenge. In this letter, we carry out the first investigation of dynamical phase behaviour at a black hole triple point. By numerically solving the Smoluchowski equation near the triple point for a six-dimensional charged Gauss-Bonnet anti-de Sitter black hole, we find that initial small, intermediate, or large black holes can transit to the other two coexistent phases at the triple point, indicating that thermodynamic phase transitions can indeed occur dynamically. More significantly, we observe characteristic weak and strong oscillatory behaviour in this dynamic process, which can be understood from an investigation of the rate of first passage from one phase to another. Our results further an understanding of the dynamic process of black hole thermodynamic phase transitions.
Shao-Wen Wei, Yong-Qiang Wang, Yu-Xiao Liu, Robert B. Mann [pdf]
-
Can the Hyperfine Mass Splitting Formula in Heavy Quarkonia be Applied to the $$B_c$$ System? -
Abstract
- The mass relation ${M_{0^{+}}+3M_{1^{+\prime}}+5M_{2^{+}}= 9M_{1^{+}}}$ miraculously holds for the $P$-wave charmonium $(c\bar{c})$ and bottomonium $(b\bar{b})$ systems with soaring precision. The origin of such relation can be addressed from Quark Models, and have been confirmed experimentally in a limited number of cases. In this connection, we propose $M_{0^{+}}+5M_{2^{+}}=3(M_{1^{+\prime}}+M_{1^{+}})$ as an extension to the $P$-wave $B_{c}$ case. In order to test its applicability, we employ a variety of Quark Model predictions for the $B_c$ mass spectrum. Our numerical analysis confirms such formula is accurate up to very small deviations.
Lei Chang, Muyang Chen, Xue-qian Li, Yu-xin Liu, Khépani Raya [pdf] DOI: 10.1007/s00601-020-01586-w 1912.08339v2 [pdf]
-
Weak deflection angle by electrically and magnetically charged black holes from nonlinear electrodynamics -
Abstract
- Nonlinear electrodynamic (NLED) theories are well-motivated for their extensions to classical electrodynamics in the strong field regime, and have been extensively investigated in seeking for regular black hole solutions. In this paper, we focus on two spherically symmetric and static black hole solutions based on two types of NLED models: the Euler-Heisenberg NLED model and the Bronnikov NLED model, and calculate the weak deflection angle of light by these two black holes with the help of the Gauss-Bonnet theorem. We investigate the effects of the one-loop corrections to quantum electrodynamics on the deflection angle and analyse the behavior of the deflection angle by a regular magnetically charged black hole. It is found that the weak deflection angle of the electrically charged Einstein-Euler-Heisenberg black hole increases with the one-loop corrections and the regular magnetically charged black hole based on the Bronnikov NLED model has a smaller deflection angle than the singular one. Besides, we also calculate the deflection angle of light by the geodesic method for verification. In addition, we discuss the effects of a cold non-magnetized plasma on the deflection angle and find that the deflection angle increases with the plasma parameter.
Qi-Ming Fu, Li Zhao, Yu-Xiao Liu Journal reference: Phys. Rev. D 104, 024033 (2021) [pdf] DOI: 10.1103/PhysRevD.104.024033
-
OpenUVR: an Open-Source System Framework for Untethered Virtual Reality
Applications -
Abstract
- Advancements in heterogeneous computing technologies enable the significant potential of virtual reality (VR) applications. To offer the best user experience (UX), a system should adopt an untethered, wireless-network-based architecture to transfer VR content between the user and the content generator. However, modern wireless network technologies make implementing such an architecture challenging, as VR applications require superior video quality -- with high resolution, high frame rates, and very low latency. This paper presents OpenUVR, an open-source framework that uses commodity hardware components to satisfy the demands of interactive, real-time VR applications. OpenUVR significantly improves UX through a redesign of the system stack and addresses the most time-sensitive issues associated with redundant memory copying in modern computing systems. OpenUVR presents a cross-layered VR datapath to avoid redundant data operations and computation among system components, OpenUVR customizes the network stack to eliminate unnecessary memory operations incurred by mismatching data formats in each layer, and OpenUVR uses feedback from mobile devices to remove memory buffers. Together, these modifications allow OpenUVR to reduce VR application delays to 14.32 ms, meeting the 20 ms minimum latency in avoiding motion sickness. As an open-source system that is fully compatible with commodity hardware, OpenUVR offers the research community an opportunity to develop, investigate, and optimize applications for untethered, high-performance VR architectures.
Alec Rohloff, Zackary Allen, Kung-Min Lin, Joshua Okrend, Chengyi Nie, Yu-Chia Liu, Hung-Wei Tseng [pdf]
-
Quantum versus Classical Regime in Circuit Quantum Acoustodynamics -
Abstract
- We experimentally study a circuit quantum acoustodynamics system, which consists of a superconducting artificial atom, coupled to both a two-dimensional surface acoustic wave resonator and a one-dimensional microwave transmission line. The strong coupling between the artificial atom and the acoustic wave resonator is confirmed by the observation of the vacuum Rabi splitting at the base temperature of dilution refrigerator. We show that the propagation of microwave photons in the microwave transmission line can be controlled by a few phonons in the acoustic wave resonator. Furthermore, we demonstrate the temperature effect on the measurements of the Rabi splitting and temperature induced transitions from high excited dressed states. We find that the spectrum structure of two-peak for the Rabi splitting becomes into those of several peaks, and gradually disappears with the increase of the environmental temperature $T$. The quantum-to-classical transition is observed around the crossover temperature $T_{c}$, which is determined via the thermal fluctuation energy $k_{B}T$ and the characteristic energy level spacing of the coupled system. Experimental results agree well with the theoretical simulations via the master equation of the coupled system at different effective temperatures.
Gang-hui Zeng, Yang Zhang, Aleksey N. Bolgar, Dong He, Bin Li, Xin-hui Ruan, Lan Zhou, Le-Mang Kuang, Oleg V. Astafiev, Yu-xi Liu, Z. H. Peng [pdf]
-
Design and characterization of a low-vibration laboratory with cylindrical inertia block geometry -
Abstract
- Many modern nanofabrication and imaging techniques require an ultra-quiet environment to reach optimal resolution. Isolation from ambient vibrations is often achieved by placing the sensitive instrument atop a massive block that floats on air springs and is surrounded by acoustic barriers. Because typical building noise drops off above 120 Hz, it is advantageous to raise the flexural resonance frequencies of the inertia block and instrument far above 120 Hz. However, it can be challenging to obtain a high fundamental frequency of the floating block using a simple rectangular design. Here we design, construct, and characterize a vibration isolation system with a cylindrical inertia block, whose lowest resonance frequency of 249 Hz shows good agreement between finite element analysis simulation and directly measured modes. Our simulations show that a cylindrical design can achieve higher fundamental resonance frequency than a rectangular design of the same mass.
Wenjie Gong, Yu Liu, Wan-Ting Liao, Joseph Gibbons, Jennifer E. Hoffman [pdf] DOI: 10.1063/5.0004964 2101.06815v1 [pdf]
-
Anomalous Hall effect in the weak-itinerant ferrimagnet
-
Abstract
- We carried out a comprehensive study of electronic transport, thermal and thermodynamic properties in FeCr$_2$Te$_4$ single crystals. It exhibits bad-metallic behavior and anomalous Hall effect (AHE) below a weak-itinerant paramagentic-to-ferrimagnetic transition $T_c$ $\sim$ 123 K. The linear scaling between the anomalous Hall resistivity $\rho_{xy}$ and the longitudinal resistivity $\rho_{xx}$ implies that the AHE in FeCr$_2$Te$_4$ is most likely dominated by extrinsic skew-scattering mechanism rather than intrinsic KL or extrinsic side-jump mechanism, which is supported by our Berry phase calculations.
Yu Liu, Hengxin Tan, Zhixiang Hu, Binghai Yan, C. Petrovic Journal reference: Physical Review B 103, 045106 (2021) [pdf] DOI: 10.1103/PhysRevB.103.045106
-
Precision test of statistical dynamics with state-to-state ultracold chemistry -
Abstract
- Chemical reactions represent a class of quantum problems that challenge both the current theoretical understanding and computational capabilities. Reactions that occur at ultralow temperatures provide an ideal testing ground for quantum chemistry and scattering theories, as they can be experimentally studied with unprecedented control, yet display dynamics that are highly complex. Here, we report the full product state distribution for the reaction 2KRb $\rightarrow$ K$_2$ + Rb$_2$. Ultracold preparation of the reactants grants complete control over their initial quantum degrees of freedom, while state-resolved, coincident detection of both products enables the measurement of scattering probabilities into all 57 allowed rotational state-pairs. Our results show an overall agreement with a state-counting model based on statistical theory, but also reveal several deviating state-pairs. In particular, we observe a strong suppression of population in the state-pair closest to the exoergicity limit, which we precisely determine to be $9.7711^{+0.0007}_{-0.0005}$ cm$^{-1}$, as a result of the long-range potential inhibiting the escape of products. The completeness of our measurements provides a valuable benchmark for quantum dynamics calculations beyond the current state-of-the-art.
Yu Liu, Ming-Guang Hu, Matthew A. Nichols, Dongzheng Yang, Daiqian Xie, Hua Guo, Kang-Kuen Ni Journal reference: Nature 593, 379-384 (2021) [pdf] DOI: 10.1038/s41586-021-03459-6
-
Electronic properties of InAs/EuS/Al hybrid nanowires -
Abstract
- We study the electronic properties of InAs/EuS/Al heterostructures as explored in a recent experiment [S. Vaitiekenas \emph{et al.}, Nat. Phys. (2020)], combining both spectroscopic results and microscopic device simulations. In particular, we use angle-resolved photoemission spectroscopy to investigate the band bending at the InAs/EuS interface. The resulting band offset value serves as an essential input to subsequent microscopic device simulations, allowing us to map the electronic wave function distribution. We conclude that the magnetic proximity effects at the Al/EuS as well as the InAs/EuS interfaces are both essential to achieve topological superconductivity at zero applied magnetic field. Mapping the topological phase diagram as a function of gate voltages and proximity-induced exchange couplings, we show that the ferromagnetic hybrid nanowire with overlapping Al and EuS layers can become a topological superconductor within realistic parameter regimes, and that the topological phase can be optimized by external gating. Our work highlights the need for a combined experimental and theoretical effort for faithful device simulation.
Chun-Xiao Liu, Sergej Schuwalow, Yu Liu, Kostas Vilkelis, A. L. R. Manesco, P. Krogstrup, Michael Wimmer Journal reference: Phys. Rev. B 104, 014516 (2021) [pdf] DOI: 10.1103/PhysRevB.104.014516
-
Energy-level attraction and heating-resistant cooling of mechanical resonators with exceptional points -
Abstract
- We study the energy-level evolution and ground-state cooling of mechanical resonators under a synthetic phononic gauge field. The tunable gauge phase is mediated by the phase difference between the $\mathcal{PT}$- and anti-$\mathcal{PT}$-symmetric mechanical couplings in a multimode optomechanical system. The transmission spectrum then exhibits the asymmetric Fano line shape or double optomechanically induced transparency by modulating the gauge phase. Moreover, the eigenvalues will collapse and become degenerate although the mechanical coupling is continuously increased. Such counterintuitive energy-attraction, instead of anti-crossing, attributes to destructive interferences between $\mathcal{PT}$- and anti-$\mathcal{PT}$-symmetric couplings. We find that the energy-attraction, as well as the accompanied exceptional points (EPs), can be more intuitively observed in the cavity output power spectrum where the mechanical eigenvalues correspond to the peaks. For mechanical cooling, the average phonon occupation number becomes minimum at these EPs. Especially, phonon transport becomes nonreciprocal and even ideally unidirectional at the EPs. Finally, we propose a heating-resistant ground-state cooling based on the nonreciprocal phonon transport, which is mediated by the gauge field. Towards the quantum regime of macroscopic mechanical resonators, most optomechanical systems are ultimately limited by their intrinsic cavity or mechanical heating. Our work revealed that the thermal energy transfer can be blocked by tuning the gauge phase, which supports a promising route to overpass the notorious heating limitations.
Cheng Jiang, Yu-Long Liu, Mika A. Sillanpää Journal reference: Phys. Rev. A 104, 013502 (2021) [pdf] DOI: 10.1103/PhysRevA.104.013502
-
Nuclear spin conservation enables state-to-state control of ultracold molecular reactions -
Abstract
- Quantum control of reactive systems has enabled microscopic probes of underlying interaction potentials, the opening of novel reaction pathways, and the alteration of reaction rates using quantum statistics. However, extending such control to the quantum states of reaction outcomes remains challenging. In this work, we realize this goal through the nuclear spin degree of freedom, a result which relies on the conservation of nuclear spins throughout the reaction. Using resonance-enhanced multiphoton ionization spectroscopy to investigate the products formed in bimolecular reactions between ultracold KRb molecules, we find that the system retains a near-perfect memory of the reactants' nuclear spins, manifested as a strong parity preference for the rotational states of the products. We leverage this effect to alter the occupation of these product states by changing the coherent superposition of initial nuclear spin states with an external magnetic field. In this way, we are able to control both the inputs and outputs of a bimolecular reaction with quantum state resolution. The techniques demonstrated here open up the possibilities to study quantum interference between reaction pathways, quantum entanglement between reaction products, and ultracold reaction dynamics at the state-to-state level.
Ming-Guang Hu, Yu Liu, Matthew A. Nichols, Lingbang Zhu, Goulven Quéméner, Olivier Dulieu, Kang-Kuen Ni Journal reference: Nat. Chem. 13, 435 (2021) [pdf] DOI: 10.1038/s41557-020-00610-0
-
A gridded establishment dataset as a proxy for economic activity in China -
Abstract
- Measuring the geographical distribution of economic activity plays a key role in scientific research and policymaking. However, previous studies and data on economic activity either have a coarse spatial resolution or cover a limited time span, and the high-resolution characteristics of socioeconomic dynamics are largely unknown. Here, we construct a dataset on the economic activity of mainland China, the gridded establishment dataset (GED), which measures the volume of establishments at a 0.01$^{\circ}$ latitude by 0.01$^{\circ}$ longitude scale. Specifically, our dataset captures the geographically based opening and closing of approximately 25.5 million firms that registered in mainland China over the period 2005-2015. The characteristics of fine granularity and long-term observability give the GED a high application value. The dataset not only allows us to quantify the spatiotemporal patterns of the establishments, urban vibrancy and socioeconomic activity, but also helps us uncover the fundamental principles underlying the dynamics of industrial and economic development.
Lei Dong, Xiaohui Yuan, Meng Li, Carlo Ratti, Yu Liu Journal reference: Sci Data 8, 5 (2021) [pdf] DOI: 10.1038/s41597-020-00792-9
-
Mass dependence of pseudocritical temperature in mean field approximation -
Abstract
- We restrict our computation in the mean field approximation which could lead to a clear critical behavior. We analyze the scaling behavior with different shape of interaction kernel by considering different dressed-gluon models. The critical exponent we obtained is consistent with that in the $3D$ $\textrm{O}(4)$ universality class. The size of critical region is up to $m_{0}^{} \le 2\sim 4\;$MeV in this mean field approximation which sets naturally an upper bound of the critical region since the fluctuations beyond mean-field usually diminish the critical region. Besides, we analyze the possible percentage of the maximum chiral susceptibility and pion mass range at which the chiral phase transition temperature is independent of the current quark mass. The results show that the percentage and the pion mass range depend on the details of interaction kernel, which differs in gluon models.
Zhan Bai, Lei Chang, Jingyi Chao, Fei Gao, Yu-xin Liu Journal reference: Phys. Rev. D 104, 014005 (2021) [pdf] DOI: 10.1103/PhysRevD.104.014005
-
From $n$-exangulated categories to $n$-abelian categories -
Abstract
- Herschend-Liu-Nakaoka introduced the notion of $n$-exangulated categories. It is not only a higher dimensional analogue of extriangulated categories defined by Nakaoka-Palu, but also gives a simultaneous generalization of $n$-exact categories in the sense of Jasso and $(n+2)$-angulated in the sense of Geiss-Keller-Oppermann. Let $\mathscr C$ be an $n$-exangulated category with enough projectives and enough injectives, and $\mathscr X$ a cluster tilting subcategory of $\mathscr C$. In this article, we show that the quotient category $\mathscr C/\mathscr X$ is an $n$-abelian category. This extends a result of Zhou-Zhu for $(n+2)$-angulated categories. Moreover, it highlights new phenomena when it is applied to $n$-exact categories.
Yu Liu, Panyue Zhou [pdf]
-
Identification of time-varying signals in quantum systems -
Abstract
- The identification of time-varying \textit{in situ} signals is crucial for characterizing the dynamics of quantum processes occurring in highly isolated environments. Under certain circumstances, they can be identified from time-resolved measurements via Ramsey interferometry experiments, but only with very special probe systems can the signals be explicitly read out, and a theoretical analysis is lacking on whether the measurement data are sufficient for unambiguous identification. In this paper, we formulate this problem as the invertibility of the underlying quantum input-output system, and derive the algebraic identifiability criterion and the algorithm for numerically identifying the signals. The criterion and algorithm can be applied to both closed and open quantum systems, and their effectiveness is demonstrated by numerical examples.
Xi Cao, Yu-xi Liu, Rebing Wu Journal reference: Phys. Rev. A 103, 022612 (2021) [pdf] DOI: 10.1103/PhysRevA.103.022612
-
Gorenstein dimension of abelian categories -
Abstract
- Let C be triangulated category and X a cluster tilting subcategory of C. Koenig and Zhu showed that the quotient category C/X is Gorenstein of Gorenstein dimension at most one. The notion of an extriangulated category was introduced by Nakaoka and Palu as a simultaneous generalization of exact categories and triangulated categories. Now let C be extriangulated category with enough projectives and enough injectives, and X a cluster tilting subcategory of C. In this article, we show that under certain conditions the quotient category C/X is Gorenstein of Gorenstein dimension at most one. As an application, this result generalizes work by Koenig and Zhu.
Yu Liu, Panyue Zhou [pdf]
-
Characteristic interaction potential of black hole molecules from the
microscopic interpretation of Ruppeiner geometry -
Abstract
- 2020
-
Covariant spin kinetic theory I: collisionless limit -
Abstract
- We develop a covariant kinetic theory for massive fermions in curved spacetime and external electromagnetic field based on quantum field theory. We derive four coupled semi-classical kinetic equations accurate at $O(\hbar)$, which describe the transports of particle number and spin degrees of freedom. The relation with the chiral kinetic theory is discussed. As an application, we study the spin polarization in the presence of finite Riemann curvature and electromagnetic field in both local and global equilibrium states.
Yu-Chen Liu, Kazuya Mameda, Xu-Guang Huang Journal reference: Chin. Phys. C 44, 094101 (2020) [pdf] DOI: 10.1088/1674-1137/44/9/094101
-
Prediction of spin polarized Fermi arcs in quasiparticle interference in CeBi -
Abstract
- We predict that CeBi in the ferromagnetic state is a Weyl semimetal. Our calculations within density functional theory show the existence of two pairs of Weyl nodes on the momentum path $(0, 0, k_z)$ at $15$ meV} above and $100$ meV below the Fermi level. Two corresponding Fermi arcs are obtained on surfaces of mirror-symmetric (010)-oriented slabs at $E=15$ meV and both arcs are interrupted into three segments due to hybridization with a set of trivial surface bands. By studying the spin texture of surface states, we find the two Fermi arcs are strongly spin-polarized but in opposite directions, which can be detected by spin-polarized ARPES measurements. Our theoretical study of quasiparticle interference (QPI) for a nonmagnetic impurity at the Bi site also reveals several features related to the Fermi arcs. Specifically, we predict that the spin polarization of the Fermi arcs leads to a bifurcation-shaped feature only in the spin-dependent QPI spectrum, serving as a fingerprint of the Weyl nodes.
Zhao Huang, Christopher A. Lane, Chao Cao, Guo-Xiang Zhi, Yu Liu, Christian Matt, Brinda Kuthanazhi, Paul C. Canfield, Dmitry Yarotski, A. J. Taylor, Jian-Xin Zhu Journal reference: Phys. Rev. B 102, 235167 (2020) [pdf] DOI: 10.1103/PhysRevB.102.235167
-
Simulation and Control of Deformable Autonomous Airships in Turbulent
Wind -
Abstract
- Abstract. Fixed wing and multirotor UAVs are common in the field of robotics. Solutions for simulation and control of these vehicles are ubiquitous. This is not the case for airships, a simulation of which needs to address unique properties, i) dynamic deformation in response to aerodynamic and control forces, ii) high susceptibility to wind and turbulence at low airspeed, iii) high variability in airship designs regarding placement, direction and vectoring of thrusters and control surfaces. We present a flexible framework for modeling, simulation and control of airships, based on the Robot operating system (ROS), simulation environment (Gazebo) and commercial off the shelf (COTS) electronics, both of which are open source. Based on simulated wind and deformation, we predict substantial effects on controllability, verified in real world flight experiments. All our code is shared as open source, for the benefit of the community and to facilitate lighter-than-air vehicle (LTAV) research. https://github.com/robot-perception-group/airship_simulation
Eric Price, Yu Tang Liu, Michael J. Black, Aamir Ahmad [pdf]
-
Universal Urban Spreading Pattern of COVID-19 and Its Underlying
Mechanism -
Abstract
- Currently, the global situation of COVID-19 is aggravating, pressingly calling for efficient control and prevention measures. Understanding spreading pattern of COVID-19 has been widely recognized as a vital step for implementing non-pharmaceutical measures. Previous studies investigated such an issue in large-scale (e.g., inter-country or inter-state) scenarios while urban spreading pattern still remains an open issue. Here, we fill this gap by leveraging the trajectory data of 197,808 smartphone users (including 17,808 anonymous confirmed cases) in 9 cities in China. We find a universal spreading pattern in all cities: the spatial distribution of confirmed cases follows a power-law-like model and the spreading centroid is time-invariant. Moreover, we reveal that human mobility in a city drives the spatialtemporal spreading process: long average travelling distance results in a high growth rate of spreading radius and wide spatial diffusion of confirmed cases. With such insight, we adopt Kendall model to simulate urban spreading of COVID-19 that can well fit the real spreading process. Our results unveil the underlying mechanism behind the spatial-temporal urban evolution of COVID-19, and can be used to evaluate the performance of mobility restriction policies implemented by many governments and to estimate the evolving spreading situation of COVID-19.
-
Dynamic State Estimation for Power System Control and Protection -
Abstract
- Dynamic state estimation (DSE) accurately tracks the dynamics of a power system and provides the evolution of the system state in real-time. This paper focuses on the control and protection applications of DSE, comprehensively presenting different facets of control and protection challenges arising in modern power systems. It is demonstrated how these challenges are effectively addressed with DSE-enabled solutions. As precursors to these solutions, reformulation of DSE considering both synchrophasor and sampled value measurements and comprehensive comparisons of DSE and observers have been presented. The usefulness and necessity of DSE based solutions in ensuring system stability, reliable protection and security, and resilience by revamping of control and protection methods are shown through examples, practical applications, and suggestions for further development.
-
Spin-polarized imaging of strongly interacting fermions in the
ferrimagnetic state of Weyl candidate CeBi -
Abstract
- CeBi has an intricate magnetic phase diagram whose fully-polarized state has recently been suggested as a Weyl semimetal, though the role of $f$ states in promoting strong interactions has remained elusive. Here we focus on the less-studied, but also time-reversal symmetry-breaking ferrimagnetic phase of CeBi, where our density functional theory (DFT) calculations predict additional Weyl nodes near the Fermi level $E_\mathrm{F}$. We use spin-polarized scanning tunneling microscopy and spectroscopy to image the surface ferrimagnetic order on the itinerant Bi $p$ states, indicating their orbital hybridization with localized Ce $f$ states. We observe suppression of this spin-polarized signature at $E_\mathrm{F}$, coincident with a Fano line shape in the conductance spectra, suggesting the Bi $p$ states partially Kondo screen the $f$ magnetic moments, and this $p-f$ hybridization causes strong Fermi-level band renormalization. The $p$ band flattening is supported by our quasiparticle interference (QPI) measurements, which also show band splitting in agreement with DFT, painting a consistent picture of a strongly interacting magnetic Weyl semimetal.
Christian E. Matt, Yu Liu, Harris Pirie, Nathan C. Drucker, Na Hyun Jo, Brinda Kuthanazhi, Zhao Huang, Christopher Lane, Jian-Xin Zhu, Paul C. Canfield, Jennifer E. Hoffman [pdf]
-
Fine-Grained 3D Shape Classification With Hierarchical Part-View Attention -
Abstract
- Fine-grained 3D shape classification is important for shape understanding and analysis, which poses a challenging research problem. However, the studies on the fine-grained 3D shape classification have rarely been explored, due to the lack of fine-grained 3D shape benchmarks. To address this issue, we first introduce a new 3D shape dataset (named FG3D dataset) with fine-grained class labels, which consists of three categories including airplane, car and chair. Each category consists of several subcategories at a fine-grained level. According to our experiments under this fine-grained dataset, we find that state-of-the-art methods are significantly limited by the small variance among subcategories in the same category. To resolve this problem, we further propose a novel fine-grained 3D shape classification method named FG3D-Net to capture the fine-grained local details of 3D shapes from multiple rendered views. Specifically, we first train a Region Proposal Network (RPN) to detect the generally semantic parts inside multiple views under the benchmark of generally semantic part detection. Then, we design a hierarchical part-view attention aggregation module to learn a global shape representation by aggregating generally semantic part features, which preserves the local details of 3D shapes. The part-view attention module hierarchically leverages part-level and view-level attention to increase the discriminability of our features. The part-level attention highlights the important parts in each view while the view-level attention highlights the discriminative views among all the views of the same object. In addition, we integrate a Recurrent Neural Network (RNN) to capture the spatial relationships among sequential views from different viewpoints. Our results under the fine-grained 3D shape dataset show that our method outperforms other state-of-the-art methods.
Xinhai Liu, Zhizhong Han, Yu-Shen Liu, Matthias Zwicker [pdf] DOI: 10.1109/TIP.2020.3048623 2005.12541v2 [pdf]
-
Tensor perturbations and thick branes in higher-dimensional f(R) gravity -
Abstract
- We study brane worlds in an anisotropic higher-dimensional spacetime within the context of $f(R)$ gravity. Firstly, we demonstrate that this spacetime with a concrete metric ansatz is stable against linear tensor perturbations under certain conditions. Moreover, the Kaluza-Klein modes of the graviton are analyzed. Secondly, we investigate thick brane solutions in six dimensions and their properties. We further exhibit two sets of solutions for thick branes. At last, the effective potential of the Kaluza-Klein modes of the graviton is discussed for the two solved $f(R)$ models in higher dimensions.
Zheng-Quan Cui, Zi-Chao Lin, Jun-Jie Wan, Yu-Xiao Liu, Li Zhao Journal reference: JHEP 12 (2020) 130 [pdf] DOI: 10.1007/JHEP12(2020)130
-
A Semi-Lagrangian Computation of Front Speeds of G-equation in ABC and
Kolmogorov Flows with Estimation via Ballistic Orbits -
Abstract
- The Arnold-Beltrami-Childress (ABC) flow and the Kolmogorov flow are three dimensional periodic divergence free velocity fields that exhibit chaotic streamlines. We are interested in front speed enhancement in G-equation of turbulent combustion by large intensity ABC and Kolmogorov flows. First, we give a quantitative construction of the ballistic orbits of ABC and Kolmogorov flows, namely those with maximal large time asymptotic speeds in a coordinate direction. Thanks to the optimal control theory of G-equation (a convex but non-coercive Hamilton-Jacobi equation), the ballistic orbits serve as admissible trajectories for front speed estimates. To study the tightness of the estimates, we compute front speeds of G-equation based on a semi-Lagrangian (SL) scheme with Strang splitting and weighted essentially non-oscillatory (WENO) interpolation. The SL scheme is stable when the ratio of time step and spatial grid size (in the propagation direction) is smaller than a positive constant independent of the flow intensity. Numerical results show that the front speed growth rate in terms of the flow intensity may approach the analytical bounds from the ballistic orbits.
Chou Kao, Yu-Yu Liu, Jack Xin [pdf]
-
Gaussian Estimates for Heat Kernels of Higher Order Schrödinger
Operators with Potentials in Generalized Schechter Classes -
Abstract
- Let $m\in\mathbb N$, $P(D):=\sum_{|\alpha|=2m}(-1)^m a_\alpha D^\alpha$ be a $2m$-order homogeneous elliptic operator with real constant coefficients on $\mathbb{R}^n$, and $V$ a measurable function on $\mathbb{R}^n$. In this article, the authors introduce a new generalized Schechter class concerning $V$ and show that the higher order Schr\"odinger operator $\mathcal{L}:=P(D)+V$ possesses a heat kernel that satisfies the Gaussian upper bound and the H\"older regularity when $V$ belongs to this new class. The Davies--Gaffney estimates for the associated semigroup and their local versions are also given. These results pave the way for many further studies on the analysis of $\mathcal{L}$.
Jun Cao, Yu Liu, Dachun Yang, Chao Zhang [pdf]
-
Hereditary cotorsion pairs on extriangulated subcategories -
Abstract
- Let $\mathcal B$ be an extriangulated category with enough projectives and enough injectives. We define a proper $m$-term subcategory $\mathcal G$ on $\mathcal B$, which is an extriangulated subcategory. Then we give a correspondence between cotorsion pairs on $\mathcal G$, support $\tau$-tilting subcategories on an abelian quotient of $\mathcal G$ when $m=2$. If such $\mathcal G$ is induced by a hereditary cotorsion pair, then we give a correspondence between cotorsion pairs on $\mathcal G$ and intermediate cotorsion pairs on $\mathcal B$ under certain assumptions. At last, we study an important property of such extriangulated subcategory $\mathcal G$.
Yu Liu, Panyue Zhou [pdf]
-
High Fermi velocities and small cyclotron masses in LaAlGe -
Abstract
- We report quantum oscillation measurements of LaAlGe, a Lorentz-violating type-II Weyl semimetal with tilted Weyl cones. Very small quasiparticle masses and very high Fermi velocities were detected at the Fermi surface. Whereas three main frequencies have been observed, angular dependence of two Fermi surface sheets indicates possible two-dimensional (2D) character despite the absence of the 2D structural features such as van der Waals bonds. Such conducting states may offer a good platform for low-dimensional polarized spin current in magnetic RAlGe (R = Ce, Pr) materials.
Zhixiang Hu, Qianheng Du, Yu Liu, D. Graf, C. Petrovic Journal reference: Applied Physics Letters 117, 224410 (2020) - Editor's pick scilight [pdf] DOI: 10.1063/5.0035445
-
SPU-Net: Self-Supervised Point Cloud Upsampling by Coarse-to-Fine
Reconstruction with Self-Projection Optimization -
Abstract
- The task of point cloud upsampling aims to acquire dense and uniform point sets from sparse and irregular point sets. Although significant progress has been made with deep learning models, they require ground-truth dense point sets as the supervision information, which can only trained on synthetic paired training data and are not suitable for training under real-scanned sparse data. However, it is expensive and tedious to obtain large scale paired sparse-dense point sets for training from real scanned sparse data. To address this problem, we propose a self-supervised point cloud upsampling network, named SPU-Net, to capture the inherent upsampling patterns of points lying on the underlying object surface. Specifically, we propose a coarse-to-fine reconstruction framework, which contains two main components: point feature extraction and point feature expansion, respectively. In the point feature extraction, we integrate self-attention module with graph convolution network (GCN) to simultaneously capture context information inside and among local regions. In the point feature expansion, we introduce a hierarchically learnable folding strategy to generate the upsampled point sets with learnable 2D grids. Moreover, to further optimize the noisy points in the generated point sets, we propose a novel self-projection optimization associated with uniform and reconstruction terms, as a joint loss, to facilitate the self-supervised point cloud upsampling. We conduct various experiments on both synthetic and real-scanned datasets, and the results demonstrate that we achieve comparable performance to the state-of-the-art supervised methods.
Xinhai Liu, Xinchen Liu, Zhizhong Han, Yu-Shen Liu [pdf]
-
Fast Accurate Beam and Channel Tracking for Two-Dimensional Phased Antenna Arrays -
Abstract
- The sparsity and the severe attenuation of millimeter-wave (mmWave) channel imply that highly directional communication is needed. The narrow beam produced by large array requires accurate alignment, which is difficult to achieve when serving fast-moving users. In this paper, we focus on accurate two-dimensional (2D) beam and channel tracking problem aiming at minimizing exploration overhead and tracking error. Using a typical frame structure with periodic exploration and communication, a proven minimum overhead of exploration is provided first. Then tracking algorithms are designed for three types of channels with different dynamic properties. It is proved that the algorithms for quasi-static channels and channels in Dynamic Case I are optimal in approaching the minimum Cramer-Rao lower bound (CRLB). The computational complexity of our algorithms is analyzed showing their efficiency, and simulation results verify their advantages in both tracking error and tracking speed.
Yu Liu, Jiahui Li, Xiujun Zhang, Shidong Zhou Journal reference: in IEEE Access, vol. 8, pp. 209844-209877, 2020 [pdf] DOI: 10.1109/ACCESS.2020.3038699
-
Overcharging a Reissner-Nordstrom Taub-NUT regular black hole -
Abstract
- The destruction of a regular black hole event horizon might provide us the possibility to access regions inside black hole event horizon. This paper investigates the possibility of overcharging a charged Taub-NUT regular black hole via the scattering of a charged field and the absorption of a charged particle, respectively. For the charged scalar field scattering, both the near-extremal and extremal charged Taub-NUT regular black holes cannot be overcharged. For the test charged particle absorption, the result shows that the event horizon of the extremal charged Taub-NUT regular black hole still exists while the event horizon of the near-extremal one can be destroyed. However, if the charge and energy cross the event horizon in a continuous path, the near-extremal charged Taub-NUT regular black hole might not be overcharged.
Wen-Bin Feng, Si-Jiang Yang, Qin Tan, Jie Yang, Yu-Xiao Liu [pdf]
-
Understanding the mesoscopic scaling patterns within cities -
Abstract
- Understanding quantitative relationships between urban elements is crucial for a wide range of applications. The observation at the macroscopic level demonstrates that the aggregated urban quantities (e.g., gross domestic product) scale systematically with population sizes across cities, also known as urban scaling laws. However, at the mesoscopic level, we lack an understanding of whether the simple scaling relationship holds within cities, which is a fundamental question regarding the spatial origin of scaling in urban systems. Here, by analyzing four extensive datasets covering millions of mobile phone users and urban facilities, we investigate the scaling phenomena within cities. We find that the mesoscopic infrastructure volume and socioeconomic activity scale sub- and super-linearly with the active population, respectively. For a same scaling phenomenon, however, the exponents vary in cities of similar population sizes. To explain these empirical observations, we propose a conceptual framework by considering the heterogeneous distributions of population and facilities, and the spatial interactions between them. Analytical and numerical results suggest that, despite the large number of complexities that influence urban activities, the simple interaction rules can effectively explain the observed regularity and heterogeneity in scaling behaviors within cities.
Lei Dong, Zhou Huang, Jiang Zhang, Yu Liu Journal reference: Sci Rep 10, 21201 (2020) [pdf] DOI: 10.1038/s41598-020-78135-2
-
End-To-End Quantum Machine Learning Implemented with Controlled Quantum Dynamics -
Abstract
- Toward quantum machine learning deployed on imperfect near-term intermediate-scale quantum (NISQ) processors, the entire physical implementation of should include as less as possible hand-designed modules with only a few ad-hoc parameters to be determined. This work presents such a hardware-friendly end-to-end quantum machine learning scheme that can be implemented with imperfect near-term intermediate-scale quantum (NISQ) processors. The proposal transforms the machine learning task to the optimization of controlled quantum dynamics, in which the learning model is parameterized by experimentally tunable control variables. Our design also enables automated feature selection by encoding the raw input to quantum states through agent control variables. Comparing with the gate-based parameterized quantum circuits, the proposed end-to-end quantum learning model is easy to implement as there are only few ad-hoc parameters to be determined. Numerical simulations on the benchmarking MNIST dataset demonstrate that the model can achieve high performance using only 3-5 qubits without downsizing the dataset, which shows great potential for accomplishing large-scale real-world learning tasks on NISQ processors.arning models. The scheme is promising for efficiently performing large-scale real-world learning tasks using intermediate-scale quantum processors.
Re-Bing Wu, Xi Cao, Pinchen Xie, Yu-xi Liu Journal reference: Phys. Rev. Applied 14, 064020 (2020) [pdf] DOI: 10.1103/PhysRevApplied.14.064020
-
Air temperature and humidity during the solar eclipses of 26 December
2019 and of 21 June 2020 in Saudi Arabia and in other eclipses with similar
environments -
Abstract
- We report air temperature and humidity changes during the two solar eclipses of 26 December 2019, and of 21 June 2020, respectively, in the cities of Al-Hofuf and Riyadh in Saudi Arabia. During the December eclipse the Sun rose already eclipsed (91.53% of the area covered) while the June eclipse, although also annular in other places of the Arabian Peninsula, was just partial at Riyadh (area covered 72.80%). This difference apparently affected the observed response on the recorded variables of temperature, relative humidity (RH) and vapor pressure (VP) in the two events. Change in these variables went unnoticed for the first eclipse since it was within the natural variability of the day; yet for the other, they showed clearly some trend alterations, which we analyze and discuss. A decrease in temperature of 3.2 {\deg}C was detected in Riyadh; however, RH and VP showed an oscillation that we explain in the light of a similar effect reported in other eclipses. We found a time lag of about 15 min measured from the eclipse central phase in this city. We made an inspection of related fluctuations and dynamics from the computed rates of the temporal variation of temperature and RH. Trying to identify the influence of solar eclipses in similar environments we have made a broad inter-comparison with other observations of these variables in the Near East, northern Africa and in the United States. We compare our results with results obtained by other authors working with the December eclipse but in the United Arab Emirates and Oman, which showed dissimilar results. These inter-comparisons show how effectively the lower atmosphere can respond to a solar eclipse within a desert environment and others similar. As a preamble, a historical revision of temperature and humidity in the context of eclipse meteorology is also included.
Marcos A. Penaloza-Murillo, Abouazza Elmhamdi, Jay M. Pasachoff, Michael T. Roman, Yu Liu, Z. A. Al-Mostafa, A. H. Maghrabi, H. A. Al-Trabulsy [pdf]
-
Equivalence of solutions between the four-dimensional novel and regularized EGB theories in a cylindrically symmetric spacetime -
Abstract
- Recently, a novel four-dimensional Einstein-Gauss-Bonnet (EGB) theory was presented to bypass the Lovelock's theorem and to give nontrivial effects on the four-dimensional local gravity. The main mechanism is to introduce a redefinition $\alpha\rightarrow\alpha/(D-4)$ and to take the limit $D\rightarrow4$. However, this theory does not have standard four-dimensional field equations. Some regularization procedures are then proposed to address this problem [arXiv:2003.11552, arXiv:2003.12771, arXiv:2004.08362, arXiv:2004.09472, arXiv:2004.10716]. The resultant regularized four-dimensional EGB theory has the same on-shell action as the original theory. Thus it is expected that the novel four-dimensional EGB theory is equivalent to its regularized version. However, the equivalence of these two theories is symmetry-dependent. In this paper, we test the equivalence in a cylindrically symmetric spacetime. The well-defined field equations of the two theories are obtained, with which our follow-up analysis shows that they are equivalent in such spacetime. Cylindrical cosmic strings are then considered as specific examples of the metric. Three sets of solutions are obtained and the corresponding string mass densities are evaluated. The results reveal how the Gauss-Bonnet term in four dimensions contributes to the string geometry in the new theory.
Zi-Chao Lin, Ke Yang, Shao-Wen Wei, Yong-Qiang Wang, Yu-Xiao Liu Journal reference: Eur. Phys. J. C 80, 1033 (2020) [pdf] DOI: 10.1140/epjc/s10052-020-08612-5
-
Desires and Motivation: The Computational Rule, the Underlying Neural
Circuitry, and the Relevant Clinical Disorders -
Abstract
- As organism is a dissipative system. The process from multi desires to exclusive motivation is of great importance among all sensory-action loops. In this paper we argued that a proper Desire-Motivation model should be a continuous dynamic mapping from the dynamic desire vector to the sparse motivation vector. Meanwhile, it should at least have specific stability and adjustability of motivation intensity. Besides, the neuroscience evidences suggest that the Desire-Motivation model should have dynamic information acquisition and should be a recurrent neural network. A five-equation model is built based on the above arguments, namely the Recurrent Gating Desire-Motivation (RGDM) model. Additionally, a heuristic speculation based on the RGDM model about corresponding brain regions is carried out. It believes that the tonic and phasic firing of ventral tegmental area dopamine neurons should execute the respective and collective feedback functions of recurrent processing. The analysis about the RGMD model shows the expectations about individual personality from three dimensions, namely stability, intensity, and motivation decision speed. These three dimensions can be combined and create eight different personalities, which is correspondent to Jung's personality structure theorem. Furthermore, the RGDM model can be used to predict three different brand-new types of depressive disorder with different phenotypes. Moreover, it can also explain several other psychiatry disorders from new perspectives.
Yu Liu, Yinghong Zhao, Mo Chen [pdf]
-
DASNet: Dual Attentive Fully Convolutional Siamese Networks for Change Detection in High-Resolution Satellite Images -
Abstract
- Change detection is a basic task of remote sensing image processing. The research objective is to identity the change information of interest and filter out the irrelevant change information as interference factors. Recently, the rise of deep learning has provided new tools for change detection, which have yielded impressive results. However, the available methods focus mainly on the difference information between multitemporal remote sensing images and lack robustness to pseudo-change information. To overcome the lack of resistance of current methods to pseudo-changes, in this paper, we propose a new method, namely, dual attentive fully convolutional Siamese networks (DASNet) for change detection in high-resolution images. Through the dual-attention mechanism, long-range dependencies are captured to obtain more discriminant feature representations to enhance the recognition performance of the model. Moreover, the imbalanced sample is a serious problem in change detection, i.e. unchanged samples are much more than changed samples, which is one of the main reasons resulting in pseudo-changes. We put forward the weighted double margin contrastive loss to address this problem by punishing the attention to unchanged feature pairs and increase attention to changed feature pairs. The experimental results of our method on the change detection dataset (CDD) and the building change detection dataset (BCDD) demonstrate that compared with other baseline methods, the proposed method realizes maximum improvements of 2.1\% and 3.6\%, respectively, in the F1 score. Our Pytorch implementation is available at https://github.com/lehaifeng/DASNet.
Jie Chen, Ziyang Yuan, Jian Peng, Li Chen, Haozhe Huang, Jiawei Zhu, Yu Liu, Haifeng Li Journal reference: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2020 [pdf] DOI: 10.1109/JSTARS.2020.3037893
-
Transverse-momentum-dependent parton distribution functions from large-momentum effective theory -
Abstract
- We show that transverse-momentum-dependent parton distribution functions (TMDPDFs), important non-perturbative quantities for describing the properties of hadrons in high-energy scattering processes such as Drell-Yan and semi-inclusive deep-inelastic scattering with observed small transverse momentum, can be obtained from Euclidean QCD calculations in the framework of large-momentum effective theory (LaMET). We present a LaMET factorization of the Euclidean quasi-TMDPDFs in terms of the physical TMDPDFs and off-light-cone soft function at leading order in $1/P^z$ expansion, with the perturbative matching coefficient satisfying a renormalization group equation. We also discuss the implementation in lattice QCD with finite-length gauge links as well as the rapidity-regularization-independent factorization for Drell-Yan cross section.
Xiangdong Ji, Yizhuang Liu, Yu-Sheng Liu [pdf] DOI: 10.1016/j.physletb.2020.135946 1911.03840v2 [pdf]
-
Novel dual relation and constant in Hawking-Page phase transitions -
Abstract
- Universal relations and constants have important applications in understanding a physical theory. In this article, we explore this issue for Hawking-Page phase transitions in Schwarzschild anti-de Sitter black holes. We find a novel exact dual relation between the minimum temperature of the ($d$+1)-dimensional black hole and the Hawking-Page phase transition temperature in $d$ dimensions, reminiscent of the holographic principle. Furthermore, we find that the normalized Ruppeiner scalar curvature is a universal constant at the Hawking-Page transition point. Since the Ruppeiner curvature can be treated as an indicator of the intensity of the interactions amongst black hole microstructures, we conjecture that this universal constant denotes an interaction threshold, beyond which a virtual black hole becomes a real one. This new dual relation and universal constant are fundamental in understanding Hawking-Page phase transitions, and might have new important applications in the black hole physics in the near future.
Shao-Wen Wei, Yu-Xiao Liu, Robert B. Mann Journal reference: Phys. Rev. D 102, 104011 (2020) [pdf] DOI: 10.1103/PhysRevD.102.104011
-
Visual Localization Under Appearance Change: Filtering Approaches -
Abstract
- A major focus of current research on place recognition is visual localization for autonomous driving. In this scenario, as cameras will be operating continuously, it is realistic to expect videos as an input to visual localization algorithms, as opposed to the single-image querying approach used in other visual localization works. In this paper, we show that exploiting temporal continuity in the testing sequence significantly improves visual localization - qualitatively and quantitatively. Although intuitive, this idea has not been fully explored in recent works. To this end, we propose two filtering approaches to exploit the temporal smoothness of image sequences: i) filtering on discrete domain with Hidden Markov Model, and ii) filtering on continuous domain with Monte Carlo-based visual localization. Our approaches rely on local features with an encoding technique to represent an image as a single vector. The experimental results on synthetic and real datasets show that our proposed methods achieve better results than state of the art (i.e., deep learning-based pose regression approaches) for the task on visual localization under significant appearance change. Our synthetic dataset and source code are made publicly available at https://sites.google.com/view/g2d-software/home and https://github.com/dadung/Visual-Localization-Filtering.
Anh-Dzung Doan, Yasir Latif, Tat-Jun Chin, Yu Liu, Shin-Fang Ch'ng, Thanh-Toan Do, Ian Reid [pdf]
-
A Search for the Guest Star Associated with Swift J1818-5937 -
Abstract
- We searched the possible historical records for the young magnetar Swift J1818.0-1607, and found a guest star in AD 1798 that might be associated with it.
Yu Liu, Yuan-Chuan Zou [pdf] DOI: 10.3847/2515-5172/abbad9 2009.12806v2 [pdf]
-
$τ$-tilting theory in abelian categories -
Abstract
- Let $\mathcal A$ be a Hom-finite abelian category with enough projectives. In this note, we show that any covariantly finite $\tau$-rigid subcategory is contained in a support $\tau$-tilting subcategory. We also show that support $\tau$-tilting subcategories are in bijection with certain finitely generated torsion classes. Some applications of our main results are also given.
Yu Liu, Panyue Zhou [pdf]
-
Explorable Tone Mapping Operators -
Abstract
- Tone-mapping plays an essential role in high dynamic range (HDR) imaging. It aims to preserve visual information of HDR images in a medium with a limited dynamic range. Although many works have been proposed to provide tone-mapped results from HDR images, most of them can only perform tone-mapping in a single pre-designed way. However, the subjectivity of tone-mapping quality varies from person to person, and the preference of tone-mapping style also differs from application to application. In this paper, a learning-based multimodal tone-mapping method is proposed, which not only achieves excellent visual quality but also explores the style diversity. Based on the framework of BicycleGAN, the proposed method can provide a variety of expert-level tone-mapped results by manipulating different latent codes. Finally, we show that the proposed method performs favorably against state-of-the-art tone-mapping algorithms both quantitatively and qualitatively.
Chien-Chuan Su, Ren Wang, Hung-Jin Lin, Yu-Lun Liu, Chia-Ping Chen, Yu-Lin Chang, Soo-Chang Pei [pdf]
-
On the Exploration of Incremental Learning for Fine-grained Image
Retrieval -
Abstract
- In this paper, we consider the problem of fine-grained image retrieval in an incremental setting, when new categories are added over time. On the one hand, repeatedly training the representation on the extended dataset is time-consuming. On the other hand, fine-tuning the learned representation only with the new classes leads to catastrophic forgetting. To this end, we propose an incremental learning method to mitigate retrieval performance degradation caused by the forgetting issue. Without accessing any samples of the original classes, the classifier of the original network provides soft "labels" to transfer knowledge to train the adaptive network, so as to preserve the previous capability for classification. More importantly, a regularization function based on Maximum Mean Discrepancy is devised to minimize the discrepancy of new classes features from the original network and the adaptive network, respectively. Extensive experiments on two datasets show that our method effectively mitigates the catastrophic forgetting on the original classes while achieving high performance on the new classes.
Wei Chen, Yu Liu, Weiping Wang, Tinne Tuytelaars, Erwin M. Bakker, Michael Lew [pdf]
-
Characterizing and Comparing COVID-19 Misinformation Across Languages,
Countries and Platforms -
Abstract
- Misinformation/disinformation about COVID-19 has been rampant on social media around the world. In this study, we investigate COVID-19 misinformation/ disinformation on social media in multiple languages - Farsi (Persian), Chinese, and English, about multiple countries - Iran, China, and the United States (US), and on multiple platforms such as Twitter, Facebook, Instagram, Weibo, and WhatsApp. Misinformation, especially about a global pandemic, is a global problem yet it is common for studies of COVID-19 misinformation on social media to focus on a single language, like English, a single country, like the US, or a single platform, like Twitter. We utilized opportunistic sampling to compile 200 specific items of viral and yet debunked misinformation across these languages, countries and platforms emerged between January 1 and August 31. We then categorized this collection based both on the topics of the misinformation and the underlying roots of that misinformation. Our multi-cultural and multilingual team observed that the nature of COVID-19 misinformation on social media varied in substantial ways across different languages/countries depending on the cultures, beliefs/religions, popularity of social media, types of platforms, freedom of speech and the power of people versus governments. We observe that politics is at the root of most of the collected misinformation across all three languages in this dataset. We further observe the different impact of government restrictions on platforms and platform restrictions on content in Iran, China, and the US and their impact on a key question of our age: how do we control misinformation without silencing the voices we need to hold governments accountable?
Golshan Madraki, Isabella Grasso, Jacqueline Otala, Yu Liu, Jeanna Matthews [pdf]
-
Lattice QCD Calculations of Transverse-Momentum-Dependent Soft Function through Large-Momentum Effective Theory -
Abstract
- The transverse-momentum-dependent (TMD) soft function is a key ingredient in QCD factorization of Drell-Yan and other processes with relatively small transverse momentum. We present a lattice QCD study of this function at moderately large rapidity on a 2+1 flavor CLS dynamic ensemble with $a=0.098$ fm. We extract the rapidity-independent (or intrinsic) part of the soft function through a large-momentum-transfer pseudo-scalar meson form factor and its quasi-TMD wave function using leading-order factorization in large-momentum effective theory. We also investigate the rapidity-dependent part of the soft function---the Collins-Soper evolution kernel---based on the large-momentum evolution of the quasi-TMD wave function.
Qi-An Zhang, Jun Hua, Yikai Huo, Xiangdong Ji, Yizhuang Liu, Yu-Sheng Liu, Maximilian Schlemmer, Andreas Schäfer, Peng Sun, Wei Wang, Yi-Bo Yang Journal reference: Phys. Rev. Lett. 125, 192001 (2020) [pdf] DOI: 10.1103/PhysRevLett.125.192001
-
Adaptive Subspace Sampling for Class Imbalance Processing-Some
clarifications, algorithm, and further investigation including applications
to Brain Computer Interface -
Abstract
- Kohonen's Adaptive Subspace Self-Organizing Map (ASSOM) learns several subspaces of the data where each subspace represents some invariant characteristics of the data. To deal with the imbalance classification problem, earlier we have proposed a method for oversampling the minority class using Kohonen's ASSOM. This investigation extends that study, clarifies some issues related to our earlier work, provides the algorithm for generation of the oversamples, applies the method on several benchmark data sets, and makes application to three Brain Computer Interface (BCI) applications. First we compare the performance of our method using some benchmark data sets with several state-of-the-art methods. Finally, we apply the ASSOM-based technique to analyze the three BCI based applications using electroencephalogram (EEG) datasets. These tasks are classification of motor imagery , drivers' fatigue states, and phases of migraine. Our results demonstrate the effectiveness of the ASSOM-based meth od in dealing with imbalance classification problem.
Chin-Teng Lin, Kuan-Chih Huang, Yu-Ting Liu, Yang-Yin Lin, Tsung-Yu Hsieh, Nikhil R. Pal, Shang-Lin Wu, Chieh-Ning Fang, Zehong Cao [pdf]
-
Most lithium-rich low-mass evolved stars revealed as red clump stars by asteroseismology and spectroscopy -
Abstract
- Lithium has confused scientists for decades at almost each scale of the universe. Lithium-rich giants are peculiar stars with lithium abundances over model prediction. A large fraction of lithium-rich low-mass evolved stars are traditionally supposed to be red giant branch (RGB) stars. Recent studies, however, report that red clump (RC) stars are more frequent than RGB. Here, we present a uniquely large systematic study combining the direct asteroseismic analysis with the spectroscopy on the lithium-rich stars. The majority of lithium-rich stars are confirmed to be RCs, whereas RGBs are minor. We reveal that the distribution of lithium-rich RGBs steeply decline with the increasing lithium abundance, showing an upper limit around 2.6 dex, whereas the Li abundances of RCs extend to much higher values. We also find that the distributions of mass and nitrogen abundance are notably different between RC and RGB stars. These findings indicate that there is still unknown process that significantly affects surface chemical composition in low-mass stellar evolution.
Hong-Liang Yan, Yu-Tao Zhou, Xianfei Zhang, Yaguang Li, Qi Gao, Jian-Rong Shi, Gang Zhao, Wako Aoki, Tadafumi Matsuno, Yan Li, Xiao-Dong Xu, Haining Li, Ya-Qian Wu, Meng-Qi Jin, Benoît Mosser, Shao-Lan Bi, Jian-Ning Fu, Kaike Pan, Takuma Suda, Yu-Juan Liu, Jing-Kun Zhao, Xi-Long Liang [pdf] DOI: 10.1038/s41550-020-01217-8 2010.02106v1 [pdf]
-
Magnetic mixed valent semimetal
-
Abstract
- We report discovery of new antiferromagnetic semimetal EuZnSb$_2$, obtained and studied in the form of single crystals. Electric resistivity, magnetic susceptibility and heat capacity indicate antiferromagnetic order of Eu with $T_N$ = 20 K. The effective moment of Eu$^{2+}$ inferred from the magnetization and specific heat measurement is 3.5 $\mu_B$, smaller than the theoretical value of Eu$^{2+}$ due to presence of both Eu$^{3+}$ and Eu$^{2+}$. Magnetic field-dependent resistivity measurements suggest dominant quasi two dimensional Fermi surfaces whereas the first-principle calculations point to the presence of Dirac fermions. Therefore, EuZnSb$_2$ could represent the first platform to study the interplay of dynamical charge fluctuations, localized magnetic 4$f$ moments and Dirac states with Sb orbital character.
Aifeng Wang, Sviatoslav Baranets, Yu Liu, Xiao Tong, E. Stavitski, Jing Zhang, Yisheng Chai, Wei-Guo Yin, Svilen Bobev, C. Petrovic Journal reference: Physical Review Research 2, 033462 (2020) [pdf] DOI: 10.1103/PhysRevResearch.2.033462
-
Quantum optimal control using phase-modulated driving fields -
Abstract
- Quantum optimal control represents a powerful technique to enhance the performance of quantum experiments by engineering the controllable parameters of the Hamiltonian. However, the computational overhead for the necessary optimization of these control parameters drastically increases as their number grows. We devise a novel variant of a gradient-free optimal-control method by introducing the idea of phase-modulated driving fields, which allows us to find optimal control fields efficiently. We numerically evaluate its performance and demonstrate the advantages over standard Fourier-basis methods in controlling an ensemble of two-level systems showing an inhomogeneous broadening. The control fields optimized with the phase-modulated method provide an increased robustness against such ensemble inhomogeneities as well as control-field fluctuations and environmental noise, with one order of magnitude less of average search time. Robustness enhancement of single quantum gates is also achieved by the phase-modulated method. Under environmental noise, an XY-8 sequence constituted by optimized gates prolongs the coherence time by $50\%$ compared with standard rectangular pulses in our numerical simulations, showing the application potential of our phase-modulated method in improving the precision of signal detection in the field of quantum sensing.
Jiazhao Tian, Haibin Liu, Yu Liu, Pengcheng Yang, Ralf Betzholz, Ressa S. Said, Fedor Jelezko, Jianming Cai Journal reference: Phys. Rev. A 102, 043707 (2020) [pdf] DOI: 10.1103/PhysRevA.102.043707
-
Probing the Partonic Degrees of Freedom in High-Multiplicity
-
Abstract
- We investigate the role of partonic degrees of freedom in high multiplicity p-Pb collisions at $\sqrt{s_{NN}}=$ 5.02 TeV carried out at the Large Hadron Collider (LHC) by studying the production and collective flow of identified hadrons at intermediate $p_T$ via the coalescence of soft and hard partons generated from viscous hydrodynamics (VISH2+1) and the energy loss model (LBT), respectively. We find that combining the intermediate $p_T$ hadrons from the coalescence with the low $p_T$ hadrons from hydrodynamics and high $p_T$ hadrons from the jet fragmentation, our Hydro-Coal-Frag model provides a nice description of the measured $p_T$-spectra and the differential elliptic flow $v_2(p_T)$ of pions, kaons and protons over the $p_T$ range from 0 to 6 GeV. We further demonstrate the necessity of including the quark coalescence contribution to reproduce the experimentally observed approximate number of constituent quark scaling of hadron $v_2$ at intermediate $p_T$. Our results thus indicate the importance of partonic degrees of freedom and also hint at the possible formation of quark-gluon plasma in high multiplicity p+Pb collisions at the LHC.
Wenbin Zhao, Che Ming Ko, Yu-Xin Liu, Guang-You Qin, Huichao Song Journal reference: Phys. Rev. Lett. 125, 072301 (2020) [pdf] DOI: 10.1103/PhysRevLett.125.072301
-
Commands 4 Autonomous Vehicles (C4AV) Workshop Summary -
Abstract
- The task of visual grounding requires locating the most relevant region or object in an image, given a natural language query. So far, progress on this task was mostly measured on curated datasets, which are not always representative of human spoken language. In this work, we deviate from recent, popular task settings and consider the problem under an autonomous vehicle scenario. In particular, we consider a situation where passengers can give free-form natural language commands to a vehicle which can be associated with an object in the street scene. To stimulate research on this topic, we have organized the \emph{Commands for Autonomous Vehicles} (C4AV) challenge based on the recent \emph{Talk2Car} dataset (URL: https://www.aicrowd.com/challenges/eccv-2020-commands-4-autonomous-vehicles). This paper presents the results of the challenge. First, we compare the used benchmark against existing datasets for visual grounding. Second, we identify the aspects that render top-performing models successful, and relate them to existing state-of-the-art models for visual grounding, in addition to detecting potential failure cases by evaluating on carefully selected subsets. Finally, we discuss several possibilities for future work.
Thierry Deruyttere, Simon Vandenhende, Dusan Grujicic, Yu Liu, Luc Van Gool, Matthew Blaschko, Tinne Tuytelaars, Marie-Francine Moens [pdf]
-
Image Retrieval for Structure-from-Motion via Graph Convolutional
Network -
Abstract
- Conventional image retrieval techniques for Structure-from-Motion (SfM) suffer from the limit of effectively recognizing repetitive patterns and cannot guarantee to create just enough match pairs with high precision and high recall. In this paper, we present a novel retrieval method based on Graph Convolutional Network (GCN) to generate accurate pairwise matches without costly redundancy. We formulate image retrieval task as a node binary classification problem in graph data: a node is marked as positive if it shares the scene overlaps with the query image. The key idea is that we find that the local context in feature space around a query image contains rich information about the matchable relation between this image and its neighbors. By constructing a subgraph surrounding the query image as input data, we adopt a learnable GCN to exploit whether nodes in the subgraph have overlapping regions with the query photograph. Experiments demonstrate that our method performs remarkably well on the challenging dataset of highly ambiguous and duplicated scenes. Besides, compared with state-of-the-art matchable retrieval methods, the proposed approach significantly reduces useless attempted matches without sacrificing the accuracy and completeness of reconstruction.
Shen Yan, Yang Pen, Shiming Lai, Yu Liu, Maojun Zhang [pdf]
-
Topological approach to derive the global Hawking temperature of (massive) BTZ black hole -
Abstract
- In this paper, we study the Hawking temperature of the BTZ black hole based on the purely topological method proposed by Robson, Villari, and Biancalana (RVB) [Phys. Rev. D 99, 044042 (2019)]. The Hawking temperature of the charged rotating BTZ black hole can be accurately derived by this topological method. We also calculate the Hawking temperature of the BTZ black hole in massive gravity. Because the metric function of the BTZ black hole in massive gravity has a mass term, the corresponding Hawking temperature cannot be derived unless an integral constant is added.
Yu-Peng Zhang, Shao-Wen Wei, Yu-Xiao Liu [pdf] DOI: 10.1016/j.physletb.2020.135788 2009.07704v1 [pdf]
-
Superconducting Order from Local Disorder -
Abstract
- In all Fe superconductors the maximal $T_c$ correlates with the average anion height above the Fe plane, i.e. with the geometry of the FeAs$_4$ or FeCh$_4$ (Ch = Te, Se, S) tetrahedron. By synthesizing FeSe$_{1-x}$S$_x$ (0 $\leq$ x $\leq$ 1) single crystal alloys and by performing a series of experiments we find that $T_c$ does scale with the average anion height for $x$ in the presence of nematic order and near FeS, whereas superconductivity changes for all other $x$ track local crystallographic disorder and disorder-related scattering. Our findings demonstrate the strong coupling between disorder and $T_c$ as $x$ is tuned beyond the nematic critical point (NCP) and provide evidence of a $T_c$ tuning mechanism related to local bond disorder.
-
Ground state cooling of magnomechanical resonator in PT-symmetric cavity
magnomechanical system at room temperature -
Abstract
- We propose to realize the ground state cooling of magnomechanical resonator in a parity-time (PT)-symmetric cavity magnomechanical system composed of a loss ferromagnetic sphere and a gain microwave cavity. In the scheme, the magnomechanical resonator can be cooled close to its ground state via the magnomechanical interaction, and it is found that the cooling effect in PT-symmetric system is much higher than that in non-PT-symmetric system. Resorting to the magnetic force noise spectrum, we investigate the final mean phonon number with experimentally feasible parameters and find surprisingly that the ground state cooling of magnomechanical resonator can be directly achieved at room temperature. Furthermore, we also illustrate that the ground state cooling can be flexibly controlled via the external magnetic field.
Zhi-Xin Yang, Liang Wang, Yu-Mu Liu, Dong-Yang Wang, Cheng-Hua Bai, Shou Zhang, Hong-Fu Wang [pdf]
-
Holographic flows with scalar self-interaction toward the Kasner
universe -
Abstract
- Considering a thermal state of the dual CFT with a uniform deformation by a scalar operator, we study a holographic renormalization group flow at nonzero temperature in the bulk described by the Einstein-scalar field theory with the self-interaction term $\lambda \phi^4$ in asymptotic anti-de Sitter spacetime. We show that the holographic flow with the self-interaction term could run smoothly through the event horizon of a black hole and deform the Schwarzschild singularity to a Kasner universe at late times. Furthermore, we also study the effect of the scalar self-interaction on the deformed near-singularity Kasner exponents and the relationship between entanglement velocity and Kasner singularity exponents at late times.
Yong-Qiang Wang, Yan Song, Qian Xiang, Shao-Wen Wei, Tao Zhu, Yu-Xiao Liu [pdf]
-
Dynamic properties of thermodynamic phase transition for
five-dimensional neutral Gauss-Bonnet AdS black hole on free energy landscape -
Abstract
- Understanding the dynamic process of the thermodynamic phase transition can provide the deep insight into the black hole microscopic properties and structures. We in this paper study the dynamic properties of the stable small-large black hole phase transition for the five-dimensional neutral Gauss-Bonnet AdS black hole. Firstly, by using the first law of black holes, we prove that the extremal points of the free energy on the landscape denote the real black hole solutions satisfying the field equations. The local maximal and minimal points correspond to local unstable and stable black hole states, respectively. Especially, on the free energy landscape, the wells of the coexistence small and large black holes have the same depth. Then we investigate the probability evolution governed by the Fokker-Planck equation. Due to the thermal fluctuation, we find that the small (large) black hole state can transit to the large (small) black hole state. Furthermore, the first passage time is calculated. For each temperature, a single peak is presented, which suggests that there is a considerable fraction of the first passage events taking place at short time. And the higher the temperature is, the faster decrease of the probability is. These results will uncover some intriguing dynamic properties of the stable small-large black hole phase transition in modified gravity.
Shao-Wen Wei, Yu-Xiao Liu, Yong-Qiang Wang [pdf]
-
Three-dimensional Fermi surface and small effective masses in Mo
-
Abstract
- We report Fermi surface characteristics of Mo8Ga41, a two-gap superconductor with critical temperature Tc = 10 K, obtained from quantum oscillation measurements. Four major frequencies have been observed with relatively small quasiparticle masses. Angular dependence of major frequencies indicates three-dimensional Fermi surface sheets. This argues for a relatively isotropic superconducting state and, given its relatively high Tc, shows that a search for materials in this class could be of interest for superconducting wire applications.
Zhixiang Hu, D. Graf, Yu Liu, C. Petrovic Journal reference: Applied Physics Letters 116, 202601 (2020) [pdf] DOI: 10.1063/5.0005177
-
Testing the nature of Gauss-Bonnet gravity by four-dimensional rotating
black hole shadow -
Abstract
- The recent discover of the novel four-dimensional static and spherically symmetric Gauss-Bonnet black hole provides a promising bed to test the Gauss-Bonnet gravity by using the astronomical observation [Phys. Rev. Lett. 124, 081301 (2020)]. In this paper, we first obtain the rotating Gauss-Bonnet black hole solution by using the Newman-Janis algorithm, and then study the shadow cast by non-rotating and rotating Gauss-Bonnet black holes. The result indicates that positive Gauss-Bonnet coupling parameter shrinks the shadow, while negative one enlarges it. Meanwhile, both the distortion and ratio of two diameters of the shadow are found to increase with the coupling parameter for certain spin. Comparing with the Kerr black hole, the shadow gets more distorted for positive coupling parameter, and less distorted for negative one. Furthermore, we calculate angular diameter of the shadow by making use of the observation of M87*. The result indicates that negative dimensionless Gauss-Bonnet coupling parameter in (-4.5, 0) is more favored. Therefore, our result gives a first constraint to the Gauss-Bonnet gravity. We believe further study on the four-dimensional rotating black hole will shed new light on the Gauss-Bonnet gravity.
Shao-Wen Wei, Yu-Xiao Liu [pdf]
-
Discriminability Distillation in Group Representation Learning -
Abstract
- Learning group representation is a commonly concerned issue in tasks where the basic unit is a group, set, or sequence. Previously, the research community tries to tackle it by aggregating the elements in a group based on an indicator either defined by humans such as the quality and saliency, or generated by a black box such as the attention score. This article provides a more essential and explicable view. We claim the most significant indicator to show whether the group representation can be benefited from one of its element is not the quality or an inexplicable score, but the discriminability w.r.t. the model. We explicitly design the discrimiability using embedded class centroids on a proxy set. We show the discrimiability knowledge has good properties that can be distilled by a light-weight distillation network and can be generalized on the unseen target set. The whole procedure is denoted as discriminability distillation learning (DDL). The proposed DDL can be flexibly plugged into many group-based recognition tasks without influencing the original training procedures. Comprehensive experiments on various tasks have proven the effectiveness of DDL for both accuracy and efficiency. Moreover, it pushes forward the state-of-the-art results on these tasks by an impressive margin.
Manyuan Zhang, Guanglu Song, Hang Zhou, Yu Liu [pdf]
-
Valence band electronic structure of the van der Waals ferromagnetic insulators: VI$$_3$$ and CrI$$_3$$ -
Abstract
- Ferromagnetic van der Waals (vdW) insulators are of great scientific interest for their promising applications in spintronics. It has been indicated that in the two materials within this class, CrI$_3$ and VI$_3$, the magnetic ground state, the band gap, and the Fermi level could be manipulated by varying the layer thickness, strain or doping. To understand how these factors impact the properties, a detailed understanding of the electronic structure would be required. However, the experimental studies of the electronic structure of these materials are still very sparse. Here, we present the detailed electronic structure of CrI$_3$ and VI$_3$ measured by angle-resolved photoemission spectroscopy (ARPES). Our results show a band-gap of the order of 1 eV, sharply contrasting some theoretical predictions such as Dirac half-metallicity and metallic phases, indicating that the intra-atomic interaction parameter (U) and spin-orbit coupling (SOC) were not properly accounted for in the calculations. We also find significant differences in the electronic properties of these two materials, in spite of similarities in their crystal structure. In CrI$_3$, the valence band maximum is dominated by the I 5{\it p}, whereas in VI$_3$ it is dominated by the V 3{\it d} derived states. Our results represent valuable input for further improvements in the theoretical modeling of these systems.
Asish K. Kundu, Yu Liu, C. Petrovic, T. Valla Journal reference: Scientific Reports 10 (2020) 15602 [pdf] DOI: 10.1038/s41598-020-72487-5
-
Complete Strain Mapping of Nanosheets of Tantalum Disulfide -
Abstract
- Quasi-two-dimensional (quasi-2D) materials hold promise for future electronics because of their unique band structures that result in electronic and mechanical properties sensitive to crystal strains in all three dimensions. Quantifying crystal strain is a prerequisite to correlating it with the performance of the device, and calls for high resolution but spatially resolved rapid characterization methods. Here we show that using fly-scan nano X-ray diffraction we can accomplish a tensile strain sensitivity below 0.001% with a spatial resolution of better than 80 nm over a spatial extent of 100 $\mu$m on quasi 2D flakes of 1T-TaS2. Coherent diffraction patterns were collected from a $\sim$ 100 nm thick sheet of 1T-TaS2 by scanning 12keV focused X-ray beam across and rotating the sample. We demonstrate that the strain distribution around micron and sub-micron sized 'bubbles' that are present in the sample may be reconstructed from these images. The experiments use state of the art synchrotron instrumentation, and will allow rapid and non-intrusive strain mapping of thin film samples and electronic devices based on quasi 2D materials.
-
Complementary Boundary Generator with Scale-Invariant Relation Modeling
for Temporal Action Localization: Submission to ActivityNet Challenge 2020 -
Abstract
- This technical report presents an overview of our solution used in the submission to ActivityNet Challenge 2020 Task 1 (\textbf{temporal action localization/detection}). Temporal action localization requires to not only precisely locate the temporal boundaries of action instances, but also accurately classify the untrimmed videos into specific categories. In this paper, we decouple the temporal action localization task into two stages (i.e. proposal generation and classification) and enrich the proposal diversity through exhaustively exploring the influences of multiple components from different but complementary perspectives. Specifically, in order to generate high-quality proposals, we consider several factors including the video feature encoder, the proposal generator, the proposal-proposal relations, the scale imbalance, and ensemble strategy. Finally, in order to obtain accurate detections, we need to further train an optimal video classifier to recognize the generated proposals. Our proposed scheme achieves the state-of-the-art performance on the temporal action localization task with \textbf{42.26} average mAP on the challenge testing set.
Haisheng Su, Jinyuan Feng, Hao Shao, Zhenyu Jiang, Manyuan Zhang, Wei Wu, Yu Liu, Hongsheng Li, Junjie Yan [pdf]
-
Multispinon excitations in the spin S=1/2 antiferromagnetic Heisenberg
model -
Abstract
- With the commutation relations of the spin operators, we first write out the equations of motion of the spin susceptibility and related correlation functions that have a hierarchical structure, then under the "soft cut-off" approximation, we give a set of equations of motion of spin susceptibilities for a spin S=1/2 antiferromagnetic Heisenberg model, that is independent of whether or not the system has a long range order in the low energy/temperature limit. Applying for a chain, a square lattice and a honeycomb lattice, respectively, we obtain the upper and the lowest boundaries of the low-lying excitations by solving this set of equations. For a chain, the upper and the lowest boundaries of the low-lying excitations are the same as that of the exact ones obtained by the Bethe ansatz, where the elementary excitations are the spinon pairs. For a square lattice, the spin wave excitation (magnons) resides in the region close to the lowest boundary of the low-lying excitations, and the multispinon excitations take place in the high energy region close to the upper boundary of the low-lying excitations. For a honeycomb lattice, we have one kind of "mode" of the low-lying excitation. The present results obey the Lieb-Schultz-Mattis theorem, and they are also consistent with recent neutron scattering observations and numerical simulations for a square lattice.
Yu-Liang Liu [pdf]
-
Learning Camera-Aware Noise Models -
Abstract
- Modeling imaging sensor noise is a fundamental problem for image processing and computer vision applications. While most previous works adopt statistical noise models, real-world noise is far more complicated and beyond what these models can describe. To tackle this issue, we propose a data-driven approach, where a generative noise model is learned from real-world noise. The proposed noise model is camera-aware, that is, different noise characteristics of different camera sensors can be learned simultaneously, and a single learned noise model can generate different noise for different camera sensors. Experimental results show that our method quantitatively and qualitatively outperforms existing statistical noise models and learning-based methods.
Ke-Chi Chang, Ren Wang, Hung-Jin Lin, Yu-Lun Liu, Chia-Ping Chen, Yu-Lin Chang, Hwann-Tzong Chen [pdf]
-
Gravitational resonances on f(T)-branes -
Abstract
- In this work, we investigate the gravitational resonances in various $f(T)$-brane models with the warp factor $\text{e}^{A(y)}=\tanh\big(k(y+b)\big)-\tanh\big(k(y-b)\big)$. For three kinds of $f(T)$, we give the solutions to the system. Besides, we consider the tensor perturbation of vielbein and obtain the effective potentials by the Kaluza-Klein (KK) decomposition. Then, we analyze what kind of effective potential can produce the gravitational resonances. Effects of different parameters on the gravitational resonances are analysed. The lifetimes of the resonances could be long enough as the age of our universe in some ranges of the parameters. This indicates that the gravitational resonances might be considered as one of the candidates of dark matter. Combining the current experimental observations, we constrain the parameters for these brane models.
Qin Tan, Wen-Di Guo, Yu-Peng Zhang, Yu-Xiao Liu [pdf] DOI: 10.1140/epjc/s10052-021-09162-0 2008.08440v1 [pdf]
-
Phase transition and microstructures of five-dimensional charged Gauss-Bonnet-AdS black holes in the grand canonical ensemble -
Abstract
- In this paper, we study the small-large black hole phase transition and construct the Ruppeiner geometry for the five-dimensional charged Gauss-Bonnet-AdS black hole in the grand canonical ensemble. By making use of the equal area law, we obtain the analytical coexistence curve of the small and large black holes. Then the phase diagrams are examined. We also calculate the change of the thermodynamic volume during the small-large phase transition, which indicates that there exists a sudden change among the black hole microstructures. The corresponding normalized scalar curvature of the Ruppeiner geometry is also calculated. Combing with the empirical observation of scalar curvature, we find that for low electric potential, the attractive interaction dominates among the microstructures, while a high electric potential produces repulsive interactions. In the reduced parameter space, we observe that only attractive interaction is allowed when the coexistence region is excluded. The normalized scalar curvature also admits a critical exponent 2 and a universal constant $-\frac{1}{8}$. In particular, the value of the normalized scalar curvature keeps the same along the coexistence small and large black hole curves. So in the grand canonical ensemble, the interaction can keep constant at the phase transition where the black hole microstructures change. These results disclose the intriguing microstructures for the charged AdS black hole in the Gauss-Bonnet gravity.
Run Zhou, Yu-Xiao Liu, Shao-Wen Wei [pdf] DOI: 10.1103/PhysRevD.102.124015 2008.08301v1 [pdf]
-
Three-dimensional Ising ferrimagnetism of Cr-Fe-Cr trimers in
-
Abstract
- We carried out a comprehensive study of magnetic critical behavior in single crystals of ternary chalcogenide FeCr$_2$Te$_4$ that undergoes a ferrimagnetic transition below $T_c$ $\sim$ 123 K. Detailed critical behavior analysis and scaled magnetic entropy change indicate a second-order ferrimagentic transition. Critical exponents $\beta = 0.30(1)$ with $T_c = 122.4(5)$ K, $\gamma = 1.22(1)$ with $T_c = 122.8(1)$ K, and $\delta = 4.24(2)$ at $T_c$ $\sim$ 123 K suggest that the spins approach three-dimensional Ising ($\beta$ = 0.325, $\gamma$ = 1.24, and $\delta$ = 4.82) model coupled with the attractive long-range interactions between spins that decay as $J(r)\approx r^{-4.88}$. Our results suggest that the ferrimagnetism in FeCr$_2$Te$_4$ is due to itinerant ferromagnetism among the antiferromagnetically coupled Cr-Fe-Cr trimers.
Yu Liu, R. J. Koch, Zhixiang Hu, Niraj Aryal, Eli Stavitski, Xiao Tong, Klaus Attenkofer, E. S. Bozin, Weiguo Yin, C. Petrovic Journal reference: Phys. Rev. B 102, 085158 (2020) [pdf] DOI: 10.1103/PhysRevB.102.085158
-
Dark information in black hole with mimetic dark matter -
Abstract
- It has been shown that the nonthermal spectrum of Hawking radiation will lead to information-carrying correlations between emitted particles in the radiation. The mutual information carried by such correlations can not be locally observed and hence is dark. With dark information, the black hole information is conserved. In this paper, we look for the spherically symmetric black hole solution in the background of dark matter in mimetic gravity and investigate the radiation spectrum and dark information of the black hole. The black hole has a similar spacetime structure to the Schwarzschild case, while its horizon radius is decreased by the dark matter. By using the statistical mechanical method, the nonthermal radiation spectrum is calculated. This radiation spectrum is very different from the Schwarzschild case at its last stage because of the effect of the dark matter. The mimetic dark matter reduces the lifetime of the black hole but increases the dark information of the Hawking radiation.
Yu-Xiao Liu, Yu-Han Ma, Yong-Qiang Wang, Shao-Wen Wei, Chang-Pu Sun [pdf]
-
Room-Temperature Skyrmion Thermopower in Fe3Sn2 -
Abstract
- We present first room-temperature thermoelectric signature of the skyrmion lattice. This was observed in Fe3Sn2, a Kagome Dirac crystal with massive Dirac fermions that features high-temperature skyrmion phase. The room-temperature skyrmion lattice shows magnetic-field dependence of the wavevector whereas thermopower is dominated by the electronic diffusion mechanism, allowing for the skyrmionic bubble lattice detection. Our results pave the way for the future skyrmion-based devices based on the manipulation of the thermal gradient.
Qianheng Du, Myung-Geun Han, Yu Liu, Weijun Ren, Yimei Zhu, Cedomir Petrovic [pdf]
-
Single Cell Transcriptome Research in Human Placenta -
Abstract
- Human placenta is a complex and heterogeneous organ interfacing between the mother and the fetus that supports fetal development. Alterations to placental structural components are associated with various pregnancy complications. To reveal the heterogeneity among various placenta cell types in normal and diseased placentas, as well as elucidate molecular interactions within a population of placental cells, a new genomics technology called single cell RNA-Seq (or scRNA-seq) has been employed in the last couple of years. Here we review the principles of scRNA-seq technology, and summarize the recent human placenta studies at scRNA-seq level across gestational ages as well as in pregnancy complications such as preterm birth and preeclampsia. We list the computational analysis platforms and resources available for the public use. Lastly, we discuss the future areas of interest for placenta single cell studies, as well as the data analytics needed to accomplish them.
Hui Li, Qianhui Huang, Yu Liu, Lana X Garmire [pdf]
-
Dual Gaussian-based Variational Subspace Disentanglement for
Visible-Infrared Person Re-Identification -
Abstract
- Visible-infrared person re-identification (VI-ReID) is a challenging and essential task in night-time intelligent surveillance systems. Except for the intra-modality variance that RGB-RGB person re-identification mainly overcomes, VI-ReID suffers from additional inter-modality variance caused by the inherent heterogeneous gap. To solve the problem, we present a carefully designed dual Gaussian-based variational auto-encoder (DG-VAE), which disentangles an identity-discriminable and an identity-ambiguous cross-modality feature subspace, following a mixture-of-Gaussians (MoG) prior and a standard Gaussian distribution prior, respectively. Disentangling cross-modality identity-discriminable features leads to more robust retrieval for VI-ReID. To achieve efficient optimization like conventional VAE, we theoretically derive two variational inference terms for the MoG prior under the supervised setting, which not only restricts the identity-discriminable subspace so that the model explicitly handles the cross-modality intra-identity variance, but also enables the MoG distribution to avoid posterior collapse. Furthermore, we propose a triplet swap reconstruction (TSR) strategy to promote the above disentangling process. Extensive experiments demonstrate that our method outperforms state-of-the-art methods on two VI-ReID datasets.
Nan Pu, Wei Chen, Yu Liu, Erwin M. Bakker, Michael S. Lew [pdf]
-
Comparative Analyses of Plasma Properties and Composition in Two Types of Small-scale Interplanetary Flux-ropes -
Abstract
- The origin of small-scale interplanetary magnetic flux-ropes (SIMFRs) and the relationship between SIMFRs and magnetic clouds (MCs) are still controversial. In this study, two populations of SMIFRs were collected, i.e., SIMFRs originating from the Sun (SIMFR-SUN) and those originating from the solar wind (SIMFR-SW). We defined the SIMFR-SUN (SIMFR-SW) as the SMIFRs that include (exclude) the counter-streaming suprathermal electrons and stay away from (close to) the heliospheric current sheet. After fitting with force-free flux-rope model, 52 SIMFR-SUN and 57 SIMFR-SW events observed by Advanced Composition Explorer (ACE) from 1998 February to 2011 August were qualified. Using the approach of relating the measurements to their spatial position within the flux-ropes, a comparative survey of plasma and composition characteristics inside the two populations of SIMFRs is presented. Results show that the two populations of SIMFRs have apparent differences. Compared with SIMFR-SW, SIMFR-SUN are MC-like, featuring lower central proton density, higher Vrad, higher low-FIP element abundances, higher and more fluctuate average ion charge-states and the ion chargestate ratios which are related to the heating in low corona. In addition, for the ion charge-state distributions inside SIMFR-SUN, the sunward side is higher than earthward, which might be caused by the flare heating during eruption. Moreover, both SIMFR-SUN and MCs show anti-correlation between plasma beta and He/P trend. These characteristics indicate that SIMFR-SUN and MCs are very likely to have the identical origination. This study supports the two-source origin of SIMFRs, i.e., the solar corona and the solar wind.
Jin Huang, Yu Liu, Jihong Liu, Yuandeng Shen [pdf] DOI: 10.3847/2041-8213/abac18 2008.02256v1 [pdf]
-
Cooper instability and superconductivity on the Penrose lattice -
Abstract
- Bulk SC has recently been observed in the Al-Zn-Mg QC. To settle the several fundamental issues on the SC on the QC, we perform a systematic study on an attractive Hubbard model on the Penrose lattice. The first issue is the Cooper instability under an infinitesimal attractive interaction on the QC without a Fermi surface. We start from the two-electron problem outside the filled Fermi-sea, where we analytically prove that an infinitesimal Hubbard attraction can lead to the Cooper instability as long as the density of state is nonzero at the Fermi level, which provides the basis for the SC on the QC. Our numerical results yield that the Cooper pairing always takes place between a time-reversal partner, satisfying the Anderson's theorem. On this basis, we perform a MF study on the system, at both the zero and finite temperatures. The MF study also shows that an arbitrarily weak attraction can lead to the pairing order, with the resulting pairing state well described by the BCS theory, and the thermal dynamic behaviors well consistent with experiment results. The second issue is about the superfluid density on the QC without translational symmetry. It's clarified that although the normal state of the system locates at the critical point of the metal-insulator transition, the pairing state exhibits real SC, carrying finite superfluid density that can be verified by the Meissner effect. Further more, our study reveals a fundamental difference between the SC on the periodic lattice and that on the QC: while the paramagnetic superfluid density in the former case vanishes at zero temperature, that in the latter case is nonzero due to the lack of translational symmetry, reflecting the consumption of superfluid density from the scattering by the non-periodic structure. These properties of the SC on the Penrose lattice revealed here are universal for all QCs.
Yongyou Zhang, Yu-Bo Liu, Ye Cao, Wei-Qiang Chen, Fan Yang [pdf]
-
AirCapRL: Autonomous Aerial Human Motion Capture using Deep
Reinforcement Learning -
Abstract
- In this letter, we introduce a deep reinforcement learning (RL) based multi-robot formation controller for the task of autonomous aerial human motion capture (MoCap). We focus on vision-based MoCap, where the objective is to estimate the trajectory of body pose and shape of a single moving person using multiple micro aerial vehicles. State-of-the-art solutions to this problem are based on classical control methods, which depend on hand-crafted system and observation models. Such models are difficult to derive and generalize across different systems. Moreover, the non-linearity and non-convexities of these models lead to sub-optimal controls. In our work, we formulate this problem as a sequential decision making task to achieve the vision-based motion capture objectives, and solve it using a deep neural network-based RL method. We leverage proximal policy optimization (PPO) to train a stochastic decentralized control policy for formation control. The neural network is trained in a parallelized setup in synthetic environments. We performed extensive simulation experiments to validate our approach. Finally, real-robot experiments demonstrate that our policies generalize to real world conditions. Video Link: https://bit.ly/38SJfjo Supplementary: https://bit.ly/3evfo1O
Rahul Tallamraju, Nitin Saini, Elia Bonetto, Michael Pabst, Yu Tang Liu, Michael J. Black, Aamir Ahmad [pdf]
-
Magnon Blockade in a PT‐Symmetric‐Like Cavity Magnomechanical System -
Abstract
- We investigate the magnon blockade effect in a parity-time (PT) symmetric-like three-mode cavity magnomechanical system involving the magnon-photon and magnon-phonon interactions. In the broken and unbroken PT-symmetric regions, we respectively calculate the second-order correlation function analytically and numerically and further determine the optimal value of detuning. By adjusting different system parameters, we study the different blockade mechanisms and find that the perfect magnon blockade effect can be observed under the weak parameter mechanism. Our work paves a way to achieve the magnon blockade in experiment.
Liang Wang, Zhi-Xin Yang, Yu-Mu Liu, Cheng-Hua Bai, Dong-Yang Wang, Shou Zhang, Hong-Fu Wang Journal reference: Annalen der Physik 2020, 2000028 [pdf] DOI: 10.1002/andp.202000028
-
Light charged pion in ultra-strong magnetic field -
Abstract
- In this work, the mass of charged pions is investigated in the presence of background magnetic fields stronger than the energy scale of QCD. We introduce an anomaly magnetic momentum term in the Dirac equation and obtain the quark propagator as consequence. We find a novel finite Landau level, denoted as $tl$LL, becoming dominant rather than the conventional lowest Landau level. We examine that, due to the shifting of Landau level, it drives a mass decreasing around $eB\sim 0.8~\mathrm{GeV}^2$ for charged pions and their masses drastically limit to the neutral one at ultra-strong magnetic field, $eB\sim 1.6~\mathrm{GeV}^2$, which is consistent with the recent lattice simulation.
Jingyi Chao, Yu-Xin Liu, Lei Chang [pdf]
-
Deep Reinforcement Learning for Dynamic Spectrum Sensing and Aggregation
in Multi-Channel Wireless Networks -
Abstract
- In this paper, the problem of dynamic spectrum sensing and aggregation is investigated in a wireless network containing N correlated channels, where these channels are occupied or vacant following an unknown joint 2-state Markov model. At each time slot, a single cognitive user with certain bandwidth requirement either stays idle or selects a segment comprising C (C < N) contiguous channels to sense. Then, the vacant channels in the selected segment will be aggregated for satisfying the user requirement. The user receives a binary feedback signal indicating whether the transmission is successful or not (i.e., ACK signal) after each transmission, and makes next decision based on the sensing channel states. Here, we aim to find a policy that can maximize the number of successful transmissions without interrupting the primary users (PUs). The problem can be considered as a partially observable Markov decision process (POMDP) due to without full observation of system environment. We implement a Deep Q-Network (DQN) to address the challenge of unknown system dynamics and computational expenses. The performance of DQN, Q-Learning, and the Improvident Policy with known system dynamics is evaluated through simulations. The simulation results show that DQN can achieve near-optimal performance among different system scenarios only based on partial observations and ACK signals.
Yunzeng Li, Wensheng Zhang, Cheng-Xiang Wang, Jian Sun, Yu Liu [pdf]
-
Lifting heptagon symbols to functions -
Abstract
- Seven-point amplitudes in planar ${\cal N}=4$ super-Yang-Mills theory have previously been constructed through four loops using the Steinmann cluster bootstrap, but only at the level of the symbol. We promote these symbols to actual functions, by specifying their first derivatives and boundary conditions on a particular two-dimensional surface. To do this, we impose branch-cut conditions and construct the entire heptagon function space through weight six. We plot the amplitudes on a few lines in the bulk Euclidean region, and explore the properties of the heptagon function space under the coaction associated with multiple polylogarithms.
Lance J. Dixon, Yu-Ting Liu [pdf] DOI: 10.1007/JHEP10(2020)031 2007.12966v1 [pdf]
-
Born–Infeld black holes in 4D Einstein–Gauss–Bonnet gravity -
Abstract
- A novel four-dimensional Einstein-Gauss-Bonnet gravity was formulated by D. Glavan and C. Lin [Phys. Rev. Lett. 124, 081301 (2020)], which is intended to bypass the Lovelock's theorem and to yield a non-trivial contribution to the four-dimensional gravitational dynamics. However, the validity and consistency of this theory has been called into question recently. We study a static and spherically symmetric black hole charged by a Born-Infeld electric field in the novel four-dimensional Einstein-Gauss-Bonnet gravity. It is found that the black hole solution still suffers the singularity problem, since particles incident from infinity can reach the singularity. It is also demonstrated that the Born-Infeld charged black hole may be superior to the Maxwell charged black hole to be a charged extension of the Schwarzschild-AdS-like black hole in this new gravitational theory. Some basic thermodynamics of the black hole solution is also analyzed. Besides, we regain the black hole solution in the regularized four-dimensional Einstein-Gauss-Bonnet gravity proposed by H. L\"u and Y. Pang [arXiv:2003.11552].
Ke Yang, Bao-Min Gu, Shao-Wen Wei, Yu-Xiao Liu Journal reference: Eur. Phys. J. C 80, 662 (2020) [pdf] DOI: 10.1140/epjc/s10052-020-8246-6
-
Learning Where to Focus for Efficient Video Object Detection -
Abstract
- Transferring existing image-based detectors to the video is non-trivial since the quality of frames is always deteriorated by part occlusion, rare pose, and motion blur. Previous approaches exploit to propagate and aggregate features across video frames by using optical flow-warping. However, directly applying image-level optical flow onto the high-level features might not establish accurate spatial correspondences. Therefore, a novel module called Learnable Spatio-Temporal Sampling (LSTS) has been proposed to learn semantic-level correspondences among adjacent frame features accurately. The sampled locations are first randomly initialized, then updated iteratively to find better spatial correspondences guided by detection supervision progressively. Besides, Sparsely Recursive Feature Updating (SRFU) module and Dense Feature Aggregation (DFA) module are also introduced to model temporal relations and enhance per-frame features, respectively. Without bells and whistles, the proposed method achieves state-of-the-art performance on the ImageNet VID dataset with less computational complexity and real-time speed. Code will be made available at https://github.com/jiangzhengkai/LSTS.
Zhengkai Jiang, Yu Liu, Ceyuan Yang, Jihao Liu, Peng Gao, Qian Zhang, Shiming Xiang, Chunhong Pan [pdf]
-
Explaining Deep Neural Networks using Unsupervised Clustering -
Abstract
- We propose a novel method to explain trained deep neural networks (DNNs), by distilling them into surrogate models using unsupervised clustering. Our method can be applied flexibly to any subset of layers of a DNN architecture and can incorporate low-level and high-level information. On image datasets given pre-trained DNNs, we demonstrate the strength of our method in finding similar training samples, and shedding light on the concepts the DNNs base their decisions on. Via user studies, we show that our model can improve the user trust in model's prediction.
Yu-han Liu, Sercan O. Arik [pdf]
-
Anisotropic magnetocaloric effect and critical behavior in
-
Abstract
- We report anisotropic magnetocaloric effect and critical behavior in quasi-one-dimensional ferromagnetic CrSbSe$_3$ single crystal. The maximum magnetic entropy change $-\Delta S_M^{max}$ is 2.16 J kg$^{-1}$ K$^{-1}$ for easy $a$ axis (2.03 J kg$^{-1}$ K$^{-1}$ for hard $b$ axis) and the relative cooling power $RCP$ is 163.1 J kg$^{-1}$ for easy $a$ axis (142.1 J kg$^{-1}$ for hard $b$ axis) near $T_c$ with a magnetic field change of 50 kOe. The magnetocrystalline anisotropy constant $K_u$ is estimated to be 148.5 kJ m$^{-3}$ at 10 K, decreasing to 39.4 kJ m$^{-3}$ at 70 K. The rescaled $\Delta S_M(T,H)$ curves along all three axes collapse onto a universal curve, respectively, confirming the second order ferromagnetic transition. Further critical behavior analysis around $T_c \sim$ 70 K gives that the critical exponents $\beta$ = 0.26(1), $\gamma$ = 1.32(2), and $\delta$ = 6.17(9) for $H\parallel a$, while $\beta$ = 0.28(2), $\gamma$ = 1.02(1), and $\delta$ = 4.14(16) for $H\parallel b$. The determined critical exponents suggest that the anisotropic magnetic coupling in CrSbSe$_3$ is strongly dependent on orientations of the applied magnetic field.
Yu Liu, Zhixiang Hu, C. Petrovic Journal reference: Phys. Rev. B 102, 014425 (2020) [pdf] DOI: 10.1103/PhysRevB.102.014425
-
Anisotropic magnetocaloric effect and critical behavior in
-
Abstract
- We report anisotropic magnetocaloric effect and magnetic critical behavior in van der Waals crystal CrCl$_3$. The maximum magnetic entropy change $-\Delta S_M^{max} \sim 14.6$ J kg$^{-1}$ K$^{-1}$ and the relative cooling power $RCP \sim 340.3$ J kg$^{-1}$ near $T_c$ with a magnetic field change of 5 T are much larger when compared to CrI$_{3}$ or CrBr$_{3}$. The rescaled $\Delta S_M(T,H)$ curves collapse onto a universal curve, confirming the second order ferromagnetic transition. Further critical behavior analysis around $T_c$ presents a set of critical exponents $\beta$ = 0.28(1) with $T_c$ = 19.4(2) K, $\gamma$ = 0.89(1) with $T_c$ = 18.95(8) K, and $\delta$ = 4.6(1) at $T_c$ = 19 K, which are close to those of theoretical tricritical mean field model.
Yu Liu, C. Petrovic Journal reference: Phys. Rev. B 102, 014424 (2020) [pdf] DOI: 10.1103/PhysRevB.102.014424
-
DRWR: A Differentiable Renderer without Rendering for Unsupervised 3D
Structure Learning from Silhouette Images -
Abstract
- Differentiable renderers have been used successfully for unsupervised 3D structure learning from 2D images because they can bridge the gap between 3D and 2D. To optimize 3D shape parameters, current renderers rely on pixel-wise losses between rendered images of 3D reconstructions and ground truth images from corresponding viewpoints. Hence they require interpolation of the recovered 3D structure at each pixel, visibility handling, and optionally evaluating a shading model. In contrast, here we propose a Differentiable Renderer Without Rendering (DRWR) that omits these steps. DRWR only relies on a simple but effective loss that evaluates how well the projections of reconstructed 3D point clouds cover the ground truth object silhouette. Specifically, DRWR employs a smooth silhouette loss to pull the projection of each individual 3D point inside the object silhouette, and a structure-aware repulsion loss to push each pair of projections that fall inside the silhouette far away from each other. Although we omit surface interpolation, visibility handling, and shading, our results demonstrate that DRWR achieves state-of-the-art accuracies under widely used benchmarks, outperforming previous methods both qualitatively and quantitatively. In addition, our training times are significantly lower due to the simplicity of DRWR.
Zhizhong Han, Chao Chen, Yu-Shen Liu, Matthias Zwicker [pdf]
-
Relative rigid subcategories and $τ$-tilting theory -
Abstract
- Let $\mathcal B$ be an extriangulated category with enough projectives $\mathcal P$ and enough injectives $\mathcal I$, and let $\mathcal R$ be a contravariantly finite rigid subcategory of $\mathcal B$ which contains $\mathcal P$. We have an abelian quotient category $\mathcal H/\mathcal R\subseteq \mathcal B/\mathcal R$ which is equivalent ${\rm mod}(\mathcal R/\mathcal P)$. In this article, we find a one-to-one correspondence between support $\tau$-tilting (resp. $\tau$-rigid) subcategories of $\mathcal H/\mathcal R$ and maximal relative rigid (resp. relative rigid) subcategories of $\mathcal H$, and show that support tilting subcategories in $\mathcal H/\mathcal R$ is a special kind of support $\tau$-tilting subcategories. We also study the relation between tilting subcategories of $\mathcal B/\mathcal R$ and cluster tilting subcategories of $\mathcal B$ when $\mathcal R$ is cluster tilting.
Yu Liu, Panyue Zhou [pdf]
-
Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases -
Abstract
- With the rapid development of knowledge bases (KBs), link prediction task, which completes KBs with missing facts, has been broadly studied in especially binary relational KBs (a.k.a knowledge graph) with powerful tensor decomposition related methods. However, the ubiquitous n-ary relational KBs with higher-arity relational facts are paid less attention, in which existing translation based and neural network based approaches have weak expressiveness and high complexity in modeling various relations. Tensor decomposition has not been considered for n-ary relational KBs, while directly extending tensor decomposition related methods of binary relational KBs to the n-ary case does not yield satisfactory results due to exponential model complexity and their strong assumptions on binary relations. To generalize tensor decomposition for n-ary relational KBs, in this work, we propose GETD, a generalized model based on Tucker decomposition and Tensor Ring decomposition. The existing negative sampling technique is also generalized to the n-ary case for GETD. In addition, we theoretically prove that GETD is fully expressive to completely represent any KBs. Extensive evaluations on two representative n-ary relational KB datasets demonstrate the superior performance of GETD, significantly improving the state-of-the-art methods by over 15\%. Moreover, GETD further obtains the state-of-the-art results on the benchmark binary relational KB datasets.
Yu Liu, Quanming Yao, Yong Li [pdf]
-
Kohn-Luttinger Mechanism Driven Exotic Topological Superconductivity on the Penrose Lattice -
Abstract
- The Kohn-Luttinger mechanism for unconventional superconductivity (SC) driven by weak repulsive electron-electron interactions on a periodic lattice is generalized to the quasicrystal (QC) via a real-space perturbative approach. The repulsive Hubbard model on the Penrose lattice is studied as an example, on which a classification of the pairing symmetries is performed and a pairing phase diagram is obtained. Two remarkable properties of these pairing states are revealed, due to the combination of the presence of the point-group symmetry and the lack of translation symmetry on this lattice. Firstly, the spin and spacial angular momenta of a Cooper pair is de-correlated: for each pairing symmetry, both spin-singlet and spin-triplet pairings are possible even in the weak-pairing limit. Secondly, the pairing states belonging to the 2D irreducible representations of the $D_5$ point group can be time-reversal-symmetry-breaking topological SCs carrying spontaneous bulk super current and spontaneous vortices. These two remarkable properties are general for the SCs on all QCs, and are rare on periodic lattices. Our work starts the new area of unconventional SCs driven by repulsive interactions on the QC.
Ye Cao, Yongyou Zhang, Yu-Bo Liu, Cheng-Cheng Liu, Wei-Qiang Chen, Fan Yang Journal reference: Phys. Rev. Lett. 125, 017002 (2020) [pdf] DOI: 10.1103/PhysRevLett.125.017002
-
Spectrum and rearrangement decays of tetraquark states with four different flavors -
Abstract
- We have systematically investigated the mass spectrum and rearrangement decay properties of the exotic tetraquark states with four different flavors using a color-magnetic interaction model. Their masses are estimated by assuming that the $X(4140)$ is a $cs\bar{c}\bar{s}$ tetraquark state and their decay widths are obtained by assuming that the Hamiltonian for decay is a constant. According to the adopted method, we find that the most stable states are probably the isoscalar $bs\bar{u}\bar{d}$ and $cs\bar{u}\bar{d}$ with $J^P=0^+$ and $1^+$. The width for most unstable tetraquarks is about tens of MeVs, but that for unstable $cu\bar{s}\bar{d}$ and $cs\bar{u}\bar{d}$ can be around 100 MeV. For the $X(5568)$, our method cannot give consistent mass and width if it is a $bu\bar{s}\bar{d}$ tetraquark state. For the $I(J^P)=0(0^+),0(1^+)$ double-heavy $T_{bc}=bc\bar{u}\bar{d}$ states, their widths can be several MeVs.
Jian-Bo Cheng, Shi-Yuan Li, Yan-Rui Liu, Yu-Nan Liu, Zong-Guo Si, Tao Yao Journal reference: Phys. Rev. D 101, 114017 (2020) [pdf] DOI: 10.1103/PhysRevD.101.114017
-
Flavor dependence of the thermal dissociations of vector and axial-vector mesons -
Abstract
- The in-medium behavior of ground-state $q\bar{q}$ mesons, where $q \in \{u,d,s,c\}$, in vector and axial-vector channels is studied based on the spectral analysis for mesonic correlators at finite temperature and zero chemical potential. We first compute the correlators by solving the quark gap equations and the inhomogeneous Bethe-Salpeter equations in the rainbow-ladder approximation. Using a phenomenological ansatz, the spectral functions are extracted by fitting the correlators. By analyzing the evolution of the spectral functions with the temperature, we obtain the dissociation temperatures of mesons and discuss their relations to the critical temperature of the chiral symmetry restoration. The results show a pattern of the flavor dependence of the thermal dissociation of the mesons.
Ling-feng Chen, Si-Xue Qin, Yu-xin Liu Journal reference: Phys. Rev. D 102, 054015 (2020) [pdf] DOI: 10.1103/PhysRevD.102.054015
-
1st place solution for AVA-Kinetics Crossover in AcitivityNet Challenge
2020 -
Abstract
- This technical report introduces our winning solution to the spatio-temporal action localization track, AVA-Kinetics Crossover, in ActivityNet Challenge 2020. Our entry is mainly based on Actor-Context-Actor Relation Network. We describe technical details for the new AVA-Kinetics dataset, together with some experimental results. Without any bells and whistles, we achieved 39.62 mAP on the test set of AVA-Kinetics, which outperforms other entries by a large margin. Code will be available at: https://github.com/Siyu-C/ACAR-Net.
Siyu Chen, Junting Pan, Guanglu Song, Manyuan Zhang, Hao Shao, Ziyi Lin, Jing Shao, Hongsheng Li, Yu Liu [pdf]
-
Formal Foundations of Continuous Graph Processing -
Abstract
- With the growing need for online and iterative graph processing, software systems that continuously process large-scale graphs become widely deployed. With optimizations inherent as part of their design, these systems are complex, and have unique features beyond conventional graph processing. This paper describes CG Calculus, the first semantic foundation for continuous graph processing. The calculus captures the essential behavior of both the backend graph processing engine and the frontend application, with a focus on two essential features: temporal locality optimization (TLO) and incremental operation processing (IOP). A key design insight is that the operations continuously applied to the graph can be captured by a semantics defined over the operation stream flowing through the graph nodes. CG Calculus is a systematic study on the correctness of building continuous graph processing systems and applications. The most important result is result determinism: despite significant non-deterministic executions introduced by TLO and IOP, the results produced by CG Calculus are the same as conventional graph processing without TLO or IOP. The metatheory of CG Calculus is mechanized in Coq.
Philip Dexter, Yu David Liu, Kenneth Chiu [pdf]
-
Kondo scenario of the γ-α phase transition in single
crystalline Cerium thin films -
Abstract
- The physical mechanism driving the $\gamma$-$\alpha$ phase transition of face-centre-cubic (fcc) cerium (Ce) remains controversial until now. In this work, high quality single crystalline fcc-Ce thin films were grown on Graphene/6$H$-SiC(0001) substrate, and explored by XRD and ARPES measurement. XRD spectra showed a clear $\gamma$-$\alpha$ phase transition at $T_{\gamma-\alpha}\approx$ 50 K, which is retarded by strain effect from substrate comparing with $T_{\gamma-\alpha}$ (about 140 K) of the bulk Ce metal. However, APRES spectra did not show any signature of $\alpha$-phase emerging in the surface-layer from 300 K to 17 K, which implied that $\alpha$-phase might form at the bulk-layer of our Ce thin films. Besides, an evident Kondo dip near Fermi energy was observed in the APRES spectrum at 80 K, indicting the formation of Kondo singlet states in $\gamma$-Ce. Furthermore, the DFT+DMFT calculations were performed to simulate the electronic structures and the theoretical spectral functions agreed well with the experimental ARPES spectra. In $\gamma$-Ce, the behavior of the self-energy's imaginary part at low frequency not only confirmed that the Kondo singlet states emerged at $T_{\rm KS} \geq 80$ K, but also implied that they became coherent states at a lower characteristic temperature ($T_{\rm coh}\sim 40$ K) due to the indirect RKKY interaction among $f$-$f$ electrons. Besides, $T_{\rm coh}$ from the theoretical simulation was close to $T_{\gamma-\alpha}$ from the XRD spectra. These issues suggested that the Kondo scenario might play an important role in the $\gamma$-$\alpha$ phase transition of cerium thin films.
-
TMD soft function from large-momentum effective theory -
Abstract
- We study Euclidean formulations of the transverse-momentum-dependent (TMD) soft function, which is a cross section for soft gluon radiations involving color charges moving in two conjugate lightcone directions in quantum chromodynamics. We show it is related to a special form factor of a pair of color sources traveling with nearly-lightlike velocities, which can be matched to TMD physical observables in semi-inclusive deep-inelastic scattering and Drell-Yan process in the framework of large momentum effective theory. It can also be extracted by combining a large-momentum form factor of light meson and its leading TMD wave function. These formulations are useful for initiating nonperturbative calculations of this useful quantity.
Xiangdong Ji, Yizhuang Liu, Yu-Sheng Liu [pdf] DOI: 10.1016/j.nuclphysb.2020.115054 1910.11415v3 [pdf]
-
Constraint on the radius of five-dimensional dS spacetime with GW170817 and GRB 170817A -
Abstract
- The recent detections of the gravitational wave (GW) event GW170817 and its electromagnetic counterpart GRB 170817A produced by a binary neutron star (NS) merger is a new milestone of multimessenger astronomy. The time interval between these two signals has attracted widespread attention from physicists. In the braneworld scenario, GWs could propagate through the bulk while electromagnetic waves (EMWs) are bounded on the brane, i.e., our Universe. Therefore, the trajectories of GWs and EMWs may follow different pathes. If GWs and EMWs are originated simultaneously from the same source on the brane, they are expected to arrive at the observer successively. Consequently, the time delay between GW170817 and GRB 170817A may carry the information of the extra dimension. In this paper, we try to investigate the phenomenon in the context of a five-dimensional dS ($\text{dS}_5$) spacetime. We first study two special Universe models, i.e., de Sitter and Einstein-de Sitter models, and calculate the gravitation horizon radius in each case. For the real Universe, we then consider the $\Lambda$CDM model. Our results show that for the de Sitter model of the Universe, the $\text{dS}_5$ radius could not contribute to the time delay. With the data of the observation, we constrain the $\text{dS}_5$ radius to $\ell\gtrsim7.5\times10^{2}\,\text{Tpc}$ for the Einstein-de Sitter model and $\ell\gtrsim2.4\times10^{3}\,\text{Tpc}$ for the $\Lambda$CDM model. After considering the uncertainty in the source redshift and the time-lags given by different astrophysical processes of the binary NS merger, we find that our constraints are not sensitive to the redshift in the range of (0.005, 0.01) and the time-lag in the range of (-100s, 1.734s).
Zi-Chao Lin, Hao Yu, Yu-Xiao Liu Journal reference: Phys.Rev.D 101 (2020) 10, 104058 [pdf] DOI: 10.1103/PhysRevD.101.104058
-
PulseGAN: Learning to generate realistic pulse waveforms in remote
photoplethysmography -
Abstract
- Remote photoplethysmography (rPPG) is a non-contact technique for measuring cardiac signals from facial videos. High-quality rPPG pulse signals are urgently demanded in many fields, such as health monitoring and emotion recognition. However, most of the existing rPPG methods can only be used to get average heart rate (HR) values due to the limitation of inaccurate pulse signals. In this paper, a new framework based on generative adversarial network, called PulseGAN, is introduced to generate realistic rPPG pulse signals through denoising the chrominance signals. Considering that the cardiac signal is quasi-periodic and has apparent time-frequency characteristics, the error losses defined in time and spectrum domains are both employed with the adversarial loss to enforce the model generating accurate pulse waveforms as its reference. The proposed framework is tested on the public UBFC-RPPG database in both within-database and cross-database configurations. The results show that the PulseGAN framework can effectively improve the waveform quality, thereby enhancing the accuracy of HR, the heart rate variability (HRV) and the interbeat interval (IBI). The proposed method achieves the best performance compared to the denoising autoencoder (DAE) and CHROM, with the mean absolute error of AVNN (the average of all normal-to-normal intervals) improving 20.85% and 41.19%, and the mean absolute error of SDNN (the standard deviation of all NN intervals) improving 20.28% and 37.53%, respectively, in the cross-database test. This framework can be easily extended to other existing deep learning based rPPG methods, which is expected to expand the application scope of rPPG techniques.
Rencheng Song, Huan Chen, Juan Cheng, Chang Li, Yu Liu, Xun Chen [pdf]
-
Kink-antikink collision in a Lorentz-violating ϕ4 model -
Abstract
- In this work, kink-antikink collision in a two-dimensional Lorentz-violating $\phi^4$ model is considered. It is shown that the Lorentz-violating term in the proposed model does not affect the structure of the linear perturbation spectrum of the standard $\phi^4$ model, and thus there exists only one vibrational mode. The Lorentz-violating term impacts, however, the frequency and spatial wave function of the vibrational mode. As a consequence, the well-known results on $\phi^4$ kink-antikink collision will also change. Collisions of kink-antikink pairs with different values of initial velocities and Lorentz-violating parameters are simulated using the Fourier spectral method. Our results indicate that models with larger Lorentz-violating parameters would have smaller critical velocities $v_c$ and smaller widths of bounce windows. Interesting fractal structures existing in the curves of maximal energy densities of the scalar field are also found.
Haobo Yan, Yuan Zhong, Yu-Xiao Liu, Kei-ichi Maeda [pdf] DOI: 10.1016/j.physletb.2020.135542 2004.13329v2 [pdf]
-
Lattice study of two-photon decay widths for scalar and pseudo-scalar charmonium -
Abstract
- In this exploratory study, two photon decay widths of pseudo-scalar ($\eta_c$) and scalar ($\chi_{c0}$) charmonium are computed using two ensembles of $N_f=2$ twisted mass lattice QCD gauge configurations. The simulation is performed two lattice ensembles with lattice spacings $a=0.067$ fm with size $32^3\times{64}$ and $a=0.085$ fm with size $24^3\times{48}$, respectively. The results for the decay widths for the two charmonia are obtained which are in the right ballpark however smaller than the experimental ones. Possible reasons for these discrepancies are discussed.
Ying Chen, Ming Gong, Ning Li, Chuan Liu, Yu-Bin Liu, Zhaofeng Liu, Jian-Ping Ma, Yu Meng, Chao Xiong, Ke-Long Zhang [pdf] DOI: 10.1088/1674-1137/44/8/083108 2003.09817v2 [pdf]
-
Anomalous chiral transports and spin polarization in heavy-ion collisions -
Abstract
- Relativistic heavy-ion collisions create hot quark-gluon plasma as well as very strong electromagnetic (EM) and fluid vortical fields. The strong EM field and vorticity can induce intriguing macroscopic quantum phenomena such as chiral magnetic, chiral separation, chiral electric separation, and chiral vortical effects as well as the spin polarization of hadrons. These phenomena provide us with experimentally feasible means to study the nontrivial topological sector of quantum chromodynamics, the possible parity violation of strong interaction at high temperature, and the subatomic spintronics of quark-gluon plasma. These studies, both in theory and in experiments, are strongly connected with other subfields of physics such as condensed matter physics, astrophysics, and cold atomic physics, and thus form an emerging interdisciplinary research area. We give an introduction to the aforementioned phenomena induced by the EM field and vorticity and an overview of the current status of their experimental research in heavy-ion collisions. We also briefly discuss spin hydrodynamics as well as chiral and spin kinetic theories.
Yu-Chen Liu, Xu-Guang Huang Journal reference: Nucl. Sci. Tech. 31, 56 (2020) [pdf] DOI: 10.1007/s41365-020-00764-z
-
Point Cloud Completion by Skip-attention Network with Hierarchical
Folding -
Abstract
- Point cloud completion aims to infer the complete geometries for missing regions of 3D objects from incomplete ones. Previous methods usually predict the complete point cloud based on the global shape representation extracted from the incomplete input. However, the global representation often suffers from the information loss of structure details on local regions of incomplete point cloud. To address this problem, we propose Skip-Attention Network (SA-Net) for 3D point cloud completion. Our main contributions lie in the following two-folds. First, we propose a skip-attention mechanism to effectively exploit the local structure details of incomplete point clouds during the inference of missing parts. The skip-attention mechanism selectively conveys geometric information from the local regions of incomplete point clouds for the generation of complete ones at different resolutions, where the skip-attention reveals the completion process in an interpretable way. Second, in order to fully utilize the selected geometric information encoded by skip-attention mechanism at different resolutions, we propose a novel structure-preserving decoder with hierarchical folding for complete shape generation. The hierarchical folding preserves the structure of complete point cloud generated in upper layer by progressively detailing the local regions, using the skip-attentioned geometry at the same resolution. We conduct comprehensive experiments on ShapeNet and KITTI datasets, which demonstrate that the proposed SA-Net outperforms the state-of-the-art point cloud completion methods.
Xin Wen, Tianyang Li, Zhizhong Han, Yu-Shen Liu [pdf]
-
Different asymptotic behaviors of thick branes in mimetic gravity -
Abstract
- In this paper, thick branes generated by mimetic scalar field with Lagrange multiplier formulation are investigated. We give three typical thick brane background solutions with different asymptotic behaviors and show that all the solutions are stable under tensor perturbations. The effective potentials of the tensor perturbations exhibit as volcano potential, P\"{o}schl-Teller potential, and harmonic oscillator potential for the three background solutions, respectively. All the tensor zero modes (massless gravitons) of the three cases can be localized on the brane. We also calculate the corrections to the Newtonian potential. On a large scale, the corrections to the Newtonian potential can be ignored. While on a small scale, the correction from the volcano-like potential is more pronounced than the other two cases. Combining the latest results of short-range gravity experiments that the usual Newtonian potential $\propto1/r$ holds down to a length scale at $52\mu$m, we get the constraint on the scale parameter as $k\gtrsim 10^{-4}$eV, and constraint on the corresponding five-dimensional fundamental scale as $bM_\ast \gtrsim10^5$TeV.
Tao-Tao Sui, Yu-Peng Zhang, Bao-Min Gu, Yu-Xiao Liu [pdf]
-
Bond-breaking induced Lifshitz transition in robust Dirac semimetal VAI
-
Abstract
- Topological electrons in semimetals are usually vulnerable to chemical doping and environment change, which restricts their potential application in future electronic devices. In this paper we report that the type-II Dirac semimetal $\mathbf{VAl_3}$ hosts exceptional, robust topological electrons which can tolerate extreme change of chemical composition. The Dirac electrons remain intact even after a substantial part of V atoms have been replaced in the $\mathbf{V_{1-x}Ti_xAl_3}$ solid solutions. This Dirac semimetal state ends at $x=0.35$ where a Lifshitz transition to $p$-type trivial metal occurs. The V-Al bond is completely broken in this transition as long as the bonding orbitals are fully depopulated by the holes donated from Ti substitution. In other words, the Dirac electrons in $\mathbf{VAl_3}$ are protected by the V-Al bond whose molecular orbital is their bonding gravity center. Our understanding on the interrelations among electron count, chemical bond and electronic properties in topological semimetals suggests a rational approach to search robust, chemical-bond-protected topological materials.
Yiyuan Liu, Yu-Fei Liu, Xin Gui, Cheng Xiang, Hui-bin Zhou, Chuang-Han Hsu, HsinLin, Tay-RongChang, WeiweiXie, ShuangJia [pdf] DOI: 10.1073/pnas.1917697117 2005.07970v1 [pdf]
-
Frobenius $n$-exangulated categories -
Abstract
- Herschend-Liu-Nakaoka introduced the notion of $n$-exangulated categories as higher dimensional analogues of extriangulated categories defined by Nakaoka-Palu. The class of $n$-exangulated categories contains $n$-exact categories and $(n+2)$-angulated categories as examples. In this article, we introduce a notion of Frobenius $n$-exangulated categories which are a generalization of Frobenius $n$-exact categories. We show that the stable category of a Frobenius $n$-exangulated category is an $(n+2)$-angulated category. As an application, this result generalizes the work by Jasso. We provide a class of $n$-exangulated categories which are neither $n$-exact categories nor $(n+2)$-angulated categories. Finally, we discuss an application of the main results and give some examples illustrating it.
Yu Liu, Panyue Zhou [pdf]
-
Excited states of holographic superconductors -
Abstract
- In this paper we re-investigate the model of the anti-de Sitter gravity coupled to Maxwell and charged scalar fields, which has been studied as the gravitational dual to a superconductor for a long time since the famous work [Phys.\ Rev.\ Lett.\ {\bf 101}, 031601 (2008)]. By numerical method, we present a novel family of solutions of holographical superconductor with excited states, and find there exists a lower critical temperature in the corresponding excited state. Moreover, we study the condensate and conductivity in the excited states. It is very interesting that the conductivity $\sigma$ of each excited state has an additional pole in $\text{Im}[\sigma]$ and a delta function in $\text{Re}[\sigma]$ arising at the low temperature inside the gap, which is just the evidence of the existence of excited states.
Yong-Qiang Wang, Tong-Tong Hu, Yu-Xiao Liu, Jie Yang, Li Zhao [pdf] DOI: 10.1007/JHEP06(2020)013 1910.07734v2 [pdf]
-
Extended thermodynamics and microstructures of four-dimensional charged Gauss-Bonnet black hole in AdS space -
Abstract
- The discovery of new four-dimensional black hole solutions presents a new approach to understand the Gauss-Bonnet gravity in low dimensions. In this paper, we test the Gauss-Bonnet gravity by studying the phase transition and microstructures for the four-dimensional charged AdS black hole. In the extended phase space, where the cosmological constant and the Gauss-Bonnet coupling parameter are treated as thermodynamic variables, we find that the thermodynamic first law and the corresponding Smarr formula are satisfied. Both in the canonical ensemble and grand canonical ensemble, we observe the small-large black hole phase transition, which is similar to the case of the van der Walls fluid. This phase transition can also appear in the neutral black hole system. Furthermore, we construct the Ruppeiner geometry, and find that besides the attractive interaction, the repulsive interaction can also dominate among the microstructures for the small black hole with high temperature in a charged or neutral black hole system. This is quite different from the five-dimensional neutral black hole, for which only dominant attractive interaction can be found. The critical behaviors of the normalized scalar curvature are also examined. These results will shed new light into the characteristic property of four-dimensional Gauss-Bonnet gravity.
Shao-Wen Wei, Yu-Xiao Liu Journal reference: Phys. Rev. D 101, 104018 (2020) [pdf] DOI: 10.1103/PhysRevD.101.104018
-
Modeling Event Propagation via Graph Biased Temporal Point Process -
Abstract
- Temporal point process is widely used for sequential data modeling. In this paper, we focus on the problem of modeling sequential event propagation in graph, such as retweeting by social network users, news transmitting between websites, etc. Given a collection of event propagation sequences, conventional point process model consider only the event history, i.e. embed event history into a vector, not the latent graph structure. We propose a Graph Biased Temporal Point Process (GBTPP) leveraging the structural information from graph representation learning, where the direct influence between nodes and indirect influence from event history is modeled respectively. Moreover, the learned node embedding vector is also integrated into the embedded event history as side information. Experiments on a synthetic dataset and two real-world datasets show the efficacy of our model compared to conventional methods and state-of-the-art.
Weichang Wu, Huanxi Liu, Xiaohu Zhang, Yu Liu, Hongyuan Zha [pdf]
-
A First Look at Commercial 5G Performance on Smartphones -
Abstract
- We conduct to our knowledge a first measurement study of commercial 5G performance on smartphones by closely examining 5G networks of three carriers (two mmWave carriers, one mid-band carrier) in three U.S. cities. We conduct extensive field tests on 5G performance in diverse urban environments. We systematically analyze the handoff mechanisms in 5G and their impact on network performance. We explore the feasibility of using location and possibly other environmental information to predict the network performance. We also study the app performance (web browsing and HTTP download) over 5G. Our study consumes more than 15 TB of cellular data. Conducted when 5G just made its debut, it provides a "baseline" for studying how 5G performance evolves, and identifies key research directions on improving 5G users' experience in a cross-layer manner. We have released the data collected from our study (referred to as 5Gophers) at https://fivegophers.umn.edu/www20.
Arvind Narayanan, Eman Ramadan, Jason Carpenter, Qingxu Liu, Yu Liu, Feng Qian, Zhi-Li Zhang Journal reference: Proceedings of The Web Conference 2020 (WWW'20) [pdf] DOI: 10.1145/3366423.3380169
-
A novel multimodal approach for hybrid brain-computer interface -
Abstract
- Brain-computer interface (BCI) technologies have been widely used in many areas. In particular, non-invasive technologies such as electroencephalography (EEG) or near-infrared spectroscopy (NIRS) have been used to detect motor imagery, disease, or mental state. It has been already shown in literature that the hybrid of EEG and NIRS has better results than their respective individual signals. The fusion algorithm for EEG and NIRS sources is the key to implement them in real-life applications. In this research, we propose three fusion methods for the hybrid of the EEG and NIRS-based brain-computer interface system: linear fusion, tensor fusion, and $p$th-order polynomial fusion. Firstly, our results prove that the hybrid BCI system is more accurate, as expected. Secondly, the $p$th-order polynomial fusion has the best classification results out of the three methods, and also shows improvements compared with previous studies. For a motion imagery task and a mental arithmetic task, the best detection accuracy in previous papers were 74.20\% and 88.1\%, whereas our accuracy achieved was 77.53\% and 90.19\% . Furthermore, unlike complex artificial neural network methods, our proposed methods are not as computationally demanding.
Zhe Sun, Zihao Huang, Feng Duan, Yu Liu [pdf]
-
Cost-effectiveness Analysis of Antiepidemic Policies and Global
Situation Assessment of COVID-19 -
Abstract
- With a two-layer contact-dispersion model and data in China, we analyze the cost-effectiveness of three types of antiepidemic measures for COVID-19: regular epidemiological control, local social interaction control, and inter-city travel restriction. We find that: 1) intercity travel restriction has minimal or even negative effect compared to the other two at the national level; 2) the time of reaching turning point is independent of the current number of cases, and only related to the enforcement stringency of epidemiological control and social interaction control measures; 3) strong enforcement at the early stage is the only opportunity to maximize both antiepidemic effectiveness and cost-effectiveness; 4) mediocre stringency of social interaction measures is the worst choice. Subsequently, we cluster countries/regions into four groups based on their control measures and provide situation assessment and policy suggestions for each group.
-
Donaldson-Thomas theory of quantum Fermat quintic threefolds I -
Abstract
- In this paper, we study non-commutative projective schemes whose associated non-commutative graded algebras are finite over their centers. We study their moduli spaces of stable sheaves, and construct a symmetric obstruction theory in the Calabi-Yau-3 case. This allows us to define Donaldson-Thomas type invariants. We also discuss the simplest examples, called quantum Fermat quintic threefolds.
Yu-Hsiang Liu [pdf]
-
Donaldson-Thomas theory of quantum Fermat quintic threefolds II -
Abstract
- This paper is a continuation of author's previous work arXiv:1911.07949, where we defined Donaldson-Thomas invariants of quantum Fermat threefolds. In this paper, we study the generic quantum Fermat threefold. We give explicit local models for Hilbert schemes of points as quivers with potential, and compute degree zero Donaldson-Thomas invariants. The result is expressed in terms of certain colored plane partitions.
Yu-Hsiang Liu [pdf]
-
Change Detection in Heterogeneous Optical and SAR Remote Sensing Images Via Deep Homogeneous Feature Fusion -
Abstract
- Change detection in heterogeneous remote sensing images is crucial for disaster damage assessment. Recent methods use homogenous transformation, which transforms the heterogeneous optical and SAR remote sensing images into the same feature space, to achieve change detection. Such transformations mainly operate on the low-level feature space and may corrupt the semantic content, deteriorating the performance of change detection. To solve this problem, this paper presents a new homogeneous transformation model termed deep homogeneous feature fusion (DHFF) based on image style transfer (IST). Unlike the existing methods, the DHFF method segregates the semantic content and the style features in the heterogeneous images to perform homogeneous transformation. The separation of the semantic content and the style in homogeneous transformation prevents the corruption of image semantic content, especially in the regions of change. In this way, the detection performance is improved with accurate homogeneous transformation. Furthermore, we present a new iterative IST (IIST) strategy, where the cost function in each IST iteration measures and thus maximizes the feature homogeneity in additional new feature subspaces for change detection. After that, change detection is accomplished accurately on the original and the transformed images that are in the same feature space. Real remote sensing images acquired by SAR and optical satellites are utilized to evaluate the performance of the proposed method. The experiments demonstrate that the proposed DHFF method achieves significant improvement for change detection in heterogeneous optical and SAR remote sensing images, in terms of both accuracy rate and Kappa index.
Xiao Jiang, Gang Li, Yu Liu, Xiao-Ping Zhang, You He [pdf] DOI: 10.1109/JSTARS.2020.2983993 2004.03830v1 [pdf]
-
Spinning test particle in four-dimensional Einstein-Gauss-Bonnet Black
Hole -
Abstract
- In this paper, we investigate the motion of a classical spinning test particle orbiting around a static spherically symmetric black hole in a novel four-dimensional Einstein-Gauss-Bonnet gravity [D. Glavan and C. Lin, Phys. Rev. Lett. 124, 081301 (2020)]. We find that the effective potential of a spinning test particle in the background of the black hole has two minima when the Gauss-Bonnet coupling parameter $\alpha$ is nearly in a special range $-6.1<\alpha/M^2<-2$ ($M$ is the mass of the black hole), which means such particle can be in two separate orbits with the same spin angular momentum and orbital angular momentum. We also investigate the innermost stable circular orbits of the spinning test particle and find that the effect of the particle spin on the the innermost stable circular is similar to the case of the four-dimensional black hole in general relativity.
Yu-Peng Zhang, Shao-Wen Wei, Yu-Xiao Liu [pdf]
-
Anisotropic Convolutional Networks for 3D Semantic Scene Completion -
Abstract
- As a voxel-wise labeling task, semantic scene completion (SSC) tries to simultaneously infer the occupancy and semantic labels for a scene from a single depth and/or RGB image. The key challenge for SSC is how to effectively take advantage of the 3D context to model various objects or stuffs with severe variations in shapes, layouts and visibility. To handle such variations, we propose a novel module called anisotropic convolution, which properties with flexibility and power impossible for the competing methods such as standard 3D convolution and some of its variations. In contrast to the standard 3D convolution that is limited to a fixed 3D receptive field, our module is capable of modeling the dimensional anisotropy voxel-wisely. The basic idea is to enable anisotropic 3D receptive field by decomposing a 3D convolution into three consecutive 1D convolutions, and the kernel size for each such 1D convolution is adaptively determined on the fly. By stacking multiple such anisotropic convolution modules, the voxel-wise modeling capability can be further enhanced while maintaining a controllable amount of model parameters. Extensive experiments on two SSC benchmarks, NYU-Depth-v2 and NYUCAD, show the superior performance of the proposed method. Our code is available at https://waterljwant.github.io/SSC/
Jie Li, Kai Han, Peng Wang, Yu Liu, Xia Yuan [pdf]
-
Synchronization in PT-symmetric optomechanical resonators -
Abstract
- Synchronization has great impacts in various fields such as self-clocking, communication, neural networks, etc. Here we present a mechanism of synchronization for two mechanical modes in two coupled optomechanical resonators by introducing the so-called PT-symmetric structure. It is shown that the degree of synchronization between the two far-off-resonant mechanical modes can be increased by decreasing the coupling strength between the two optomechanical resonators. Additionally, when we consider the stochastic noises in the optomechanical resonators, we find that more noises can enhance the degree of synchronization of the system under particular parameter regime. Our results open up the new dimension of research for PT-symmetric systems and synchronization.
Chang-long Zhu, Yu-long Liu, Lan Yang, Yu-xi Liu, Jing Zhang [pdf]
-
Learning to See Through Obstructions -
Abstract
- We present a learning-based approach for removing unwanted obstructions, such as window reflections, fence occlusions or raindrops, from a short sequence of images captured by a moving camera. Our method leverages the motion differences between the background and the obstructing elements to recover both layers. Specifically, we alternate between estimating dense optical flow fields of the two layers and reconstructing each layer from the flow-warped images via a deep convolutional neural network. The learning-based layer reconstruction allows us to accommodate potential errors in the flow estimation and brittle assumptions such as brightness consistency. We show that training on synthetically generated data transfers well to real images. Our results on numerous challenging scenarios of reflection and fence removal demonstrate the effectiveness of the proposed method.
Yu-Lun Liu, Wei-Sheng Lai, Ming-Hsuan Yang, Yung-Yu Chuang, Jia-Bin Huang [pdf]
-
Single-Image HDR Reconstruction by Learning to Reverse the Camera
Pipeline -
Abstract
- Recovering a high dynamic range (HDR) image from a single low dynamic range (LDR) input image is challenging due to missing details in under-/over-exposed regions caused by quantization and saturation of camera sensors. In contrast to existing learning-based methods, our core idea is to incorporate the domain knowledge of the LDR image formation pipeline into our model. We model the HDRto-LDR image formation pipeline as the (1) dynamic range clipping, (2) non-linear mapping from a camera response function, and (3) quantization. We then propose to learn three specialized CNNs to reverse these steps. By decomposing the problem into specific sub-tasks, we impose effective physical constraints to facilitate the training of individual sub-networks. Finally, we jointly fine-tune the entire model end-to-end to reduce error accumulation. With extensive quantitative and qualitative experiments on diverse image datasets, we demonstrate that the proposed method performs favorably against state-of-the-art single-image HDR reconstruction algorithms.
Yu-Lun Liu, Wei-Sheng Lai, Yu-Sheng Chen, Yi-Lung Kao, Ming-Hsuan Yang, Yung-Yu Chuang, Jia-Bin Huang [pdf]
-
Higgs boson decay h → Zγ and muon magnetic dipole moment in the μνSSM -
Abstract
- To solve the $\mu$ problem and generate three tiny neutrino masses in the MSSM, the $\mu$ from $\nu$ Supersymmetric Standard Model ($\mu\nu$SSM) introduces three singlet right-handed neutrino superfields, which lead to the mixing of the Higgs doublets with the sneutrinos. The mixing affects the lightest Higgs boson mass and the Higgs couplings. The present observed 95\% CL upper limit on signal strength of the 125 GeV Higgs boson decay $h\rightarrow Z\gamma$ is 6.6, which still is plenty of space to prove the existence of new physics. In this work, we investigate the signal strength of the 125 GeV Higgs boson decay channel $h\rightarrow Z\gamma$ in the $\mu\nu$SSM. Besides, we consider the two-loop electroweak corrections of muon anomalous magnetic dipole moment (MDM) in the model, which also make important contributions compared with one-loop electroweak corrections.
Chang-Xin Liu, Hai-Bin Zhang, Jin-Lei Yang, Shu-Min Zhao, Yu-Bin Liu, Tai-Fu Feng Journal reference: JHEP04(2020)002 [pdf] DOI: 10.1007/JHEP04(2020)002
-
DPGN: Distribution Propagation Graph Network for Few-shot Learning -
Abstract
- Most graph-network-based meta-learning approaches model instance-level relation of examples. We extend this idea further to explicitly model the distribution-level relation of one example to all other examples in a 1-vs-N manner. We propose a novel approach named distribution propagation graph network (DPGN) for few-shot learning. It conveys both the distribution-level relations and instance-level relations in each few-shot learning task. To combine the distribution-level relations and instance-level relations for all examples, we construct a dual complete graph network which consists of a point graph and a distribution graph with each node standing for an example. Equipped with dual graph architecture, DPGN propagates label information from labeled examples to unlabeled examples within several update generations. In extensive experiments on few-shot learning benchmarks, DPGN outperforms state-of-the-art results by a large margin in 5% $\sim$ 12% under supervised setting and 7% $\sim$ 13% under semi-supervised setting. Code will be released.
Ling Yang, Liangliang Li, Zilun Zhang, Xinyu Zhou, Erjin Zhou, Yu Liu [pdf]
-
Spin-Triplet Excitonic Insulator: The Case of Semihydrogenated Graphene -
Abstract
- While various excitonic insulators have been studied in the literature, due to the perceived too-small spin splitting, spin-triplet excitonic insulator is rare. In two-dimensional systems such as a graphone, however, it is possible, as revealed by first-principles calculations coupled with Bethe-Salpeter equation. The critical temperature, given by an effective Hamiltonian, is 11.5 K. While detecting excitonic insulators is still a daunting challenge, the condensation of triplet excitons will result in spin superfluidity, which can be directly measured by a transport experiment. Nonlocal dielectric screening also leads to an unexpected phenomenon, namely, an indirect-to-direct transition crossover between single-particle band and exciton dispersion in graphone, which offers yet another test by experiment.
Zeyu Jiang, Wenkai Lou, Yu Liu, Yuanchang Li, Haifeng Song, Kai Chang, Wenhui Duan, Shengbai Zhang Journal reference: Phys. Rev. Lett. 124, 166401 (2020) [pdf] DOI: 10.1103/PhysRevLett.124.166401
-
On the relation between relative rigid and support tilting -
Abstract
- Let B be an extriangulated category with enough projectives and enough injectives. Let C be a fully rigid subcategory of B which admits a twin cotorsion pair ((C,K),(K,D)). The quotient category B/K is abelian, we assume that it is hereditary and has finite length. In this article, we study the relation between support tilting subcategories of B/K and maximal relative rigid subcategories of B. More precisely, we show that the image of any cluster tilting subcategory of B is support tilting in B/K and any support tilting subcategory in B/K can be lifted to a unique relative maximal rigid subcategory in B. We also give a bijection between these two classes of subcategories if C is generated by an object.
Yu Liu, Panyue Zhou [pdf]
-
Vortex-Meissner phase transition induced by a two-tone-drive-engineered artificial gauge potential in the fermionic ladder constructed by superconducting qubit circuits -
Abstract
- We propose to periodically modulate the onsite energy via two-tone drives, which can be furthermore used to engineer artificial gauge potential. As an example, we show that the fermionic ladder model penetrated with effective magnetic flux can be constructed by superconducting flux qubits using such two-tone-drive-engineered artificial gauge potential. In this superconducting system, the single-particle ground state can range from vortex phase to Meissner phase due to the competition between the interleg coupling strength and the effective magnetic flux. We also present the method to experimentally measure the chiral currents by the single-particle Rabi oscillations between adjacent qubits. In contrast to previous methods of generating artifical gauge potential, our proposal does not need the aid of auxiliary couplers and in principle remains valid only if the qubit circuit maintains enough anharmonicity. The fermionic ladder model with effective magnetic flux can also be interpreted as one-dimensional spin-orbit-coupled model, which thus lay a foundation towards the realization of quantum spin Hall effect.
Yan-Jun Zhao, Xun-Wei Xu, Hui Wang, Yu-xi Liu, Wu-Ming Liu [pdf] DOI: 10.1103/PhysRevA.102.053722 2003.10638v1 [pdf]
-
A Statistical Study of the Plasma and Composition Distribution inside Magnetic Clouds: 1998–2011 -
Abstract
- A comprehensive analysis of plasma and composition characteristics inside magnetic clouds (MCs) observed by the Advanced Composition Explorer (ACE) spacecraft from 1998 February to 2011 August is presented. The results show that MCs have specific interior structures, and MCs of different speeds show differences in composition and structure. Compared with the slow MCs, fast MCs have enhanced mean charge states of iron, oxygen, silicon, magnesium, $\mathrm{O^{7+}/O^{6+}}$, $\mathrm{C^{6+}/C^{5+}}$, $\mathrm{C^{6+}/C^{4+}}$ and $\mathrm{Fe^{\geq16+}/Fe_{total}}$ values. For ionic species in fast MCs, a higher atomic number represents a greater enhancement of mean charge state than slow MCs. We also find that both the fast and slow MCs display bimodal structure distribution in the mean iron charge state ($\mathrm{\langle Q\rangle Fe}$), which suggests that the existence of flux rope prior to the eruption is common. Furthermore, the $\mathrm{\langle Q\rangle Fe} $, $\mathrm{Fe^{\geq16+}/Fe_{total}}$, and $\mathrm{O^{7+}/O^{6+}}$ ratio distribution inside fast MCs have the feature that the posterior peak is higher than the anterior one. This result agrees with the "standard model" for CME/flares, by which magnetic reconnection occurs beneath the flux rope, thereby ionizing the ions of the posterior part of flux rope sufficiently by high-energy electron collisions or by direct heating in the reconnection region.
Jin Huang, Yu Liu, Hengqiang Feng, Ake Zhao, Z. Z. Abidin, Yuandeng Shen, Oloketuyi Jacob [pdf] DOI: 10.3847/1538-4357/ab7a28 2003.09965v1 [pdf]
-
LRC-Net: Learning Discriminative Features on Point Clouds by Encoding
Local Region Contexts -
Abstract
- Learning discriminative feature directly on point clouds is still challenging in the understanding of 3D shapes. Recent methods usually partition point clouds into local region sets, and then extract the local region features with fixed-size CNN or MLP, and finally aggregate all individual local features into a global feature using simple max pooling. However, due to the irregularity and sparsity in sampled point clouds, it is hard to encode the fine-grained geometry of local regions and their spatial relationships when only using the fixed-size filters and individual local feature integration, which limit the ability to learn discriminative features. To address this issue, we present a novel Local-Region-Context Network (LRC-Net), to learn discriminative features on point clouds by encoding the fine-grained contexts inside and among local regions simultaneously. LRC-Net consists of two main modules. The first module, named intra-region context encoding, is designed for capturing the geometric correlation inside each local region by novel variable-size convolution filter. The second module, named inter-region context encoding, is proposed for integrating the spatial relationships among local regions based on spatial similarity measures. Experimental results show that LRC-Net is competitive with state-of-the-art methods in shape classification and shape segmentation applications.
Xinhai Liu, Zhizhong Han, Fangzhou Hong, Yu-Shen Liu, Matthias Zwicker [pdf]
-
Neutrino effects on the morphology of cosmic large-scale structure -
Abstract
- In this work, we propose a powerful probe of neutrino effects on the large-scale structure (LSS) of the Universe, i.e., Minkowski functionals (MFs). The morphology of LSS can be fully described by four MFs. This tool, with strong statistical power, is robust to various systematics and can comprehensively probe all orders of N-point statistics. By using a pair of high-resolution N-body simulations, for the first time, we comprehensively studied the subtle neutrino effects on the morphology of LSS. For an ideal LSS survey of volume $\sim1.73$ Gpc$^3$/$h^3$, neutrino signals are mainly detected from void regions with a significant level up to $\thicksim 10\sigma$ and $\thicksim 300\sigma$ for CDM and total matter density fields, respectively. This demonstrates its enormous potential for much improving the neutrino mass constraint in the data analysis of up-coming ambitious LSS surveys.
Yu Liu, Yu Yu, Hao-Ran Yu, Pengjie Zhang Journal reference: Phys.Rev.D 101,063515 (2020) [pdf] DOI: 10.1103/PhysRevD.101.063515
-
Saturating the quantum Cramér-Rao bound and measuring the related
quantum Fisher information in a nitrogen-vacancy center in diamond -
Abstract
- The quantum Cram\'er-Rao bound sets a fundamental limit on the accuracy of unbiased parameter estimation in quantum systems, relating the uncertainty in determining a parameter to the inverse of the quantum Fisher information. We experimentally demonstrate near saturation of the quantum Cram\'er-Rao bound in the phase estimation of a solid-state spin system, provided by a nitrogen-vacancy center in diamond. This is achieved by comparing the experimental uncertainty in phase estimation with an independent measurement of the related quantum Fisher information. The latter is finely extracted from coherent dynamical responses of the system under weak parametric modulations, without performing any quantum-state tomography. Our method offers a versatile and powerful tool to explore the fundamental role of the quantum Fisher information in quantum technologies.
Yu Liu, Min Yu, Pengcheng Yang, Musang Gong, Qingyun Cao, Shaoliang Zhang, Haibin Liu, Markus Heyl, Tomoki Ozawa, Nathan Goldman, Jianming Cai [pdf]
-
Rotate-and-Render: Unsupervised Photorealistic Face Rotation from
Single-View Images -
Abstract
- Though face rotation has achieved rapid progress in recent years, the lack of high-quality paired training data remains a great hurdle for existing methods. The current generative models heavily rely on datasets with multi-view images of the same person. Thus, their generated results are restricted by the scale and domain of the data source. To overcome these challenges, we propose a novel unsupervised framework that can synthesize photo-realistic rotated faces using only single-view image collections in the wild. Our key insight is that rotating faces in the 3D space back and forth, and re-rendering them to the 2D plane can serve as a strong self-supervision. We leverage the recent advances in 3D face modeling and high-resolution GAN to constitute our building blocks. Since the 3D rotation-and-render on faces can be applied to arbitrary angles without losing details, our approach is extremely suitable for in-the-wild scenarios (i.e. no paired data are available), where existing methods fall short. Extensive experiments demonstrate that our approach has superior synthesis quality as well as identity preservation over the state-of-the-art methods, across a wide range of poses and domains. Furthermore, we validate that our rotate-and-render framework naturally can act as an effective data augmentation engine for boosting modern face recognition systems even on strong baseline models.
Hang Zhou, Jihao Liu, Ziwei Liu, Yu Liu, Xiaogang Wang [pdf]
-
1st Place Solutions for OpenImage2019 -- Object Detection and Instance
Segmentation -
Abstract
- This article introduces the solutions of the two champion teams, `MMfruit' for the detection track and `MMfruitSeg' for the segmentation track, in OpenImage Challenge 2019. It is commonly known that for an object detector, the shared feature at the end of the backbone is not appropriate for both classification and regression, which greatly limits the performance of both single stage detector and Faster RCNN \cite{ren2015faster} based detector. In this competition, we observe that even with a shared feature, different locations in one object has completely inconsistent performances for the two tasks. \textit{E.g. the features of salient locations are usually good for classification, while those around the object edge are good for regression.} Inspired by this, we propose the Decoupling Head (DH) to disentangle the object classification and regression via the self-learned optimal feature extraction, which leads to a great improvement. Furthermore, we adjust the soft-NMS algorithm to adj-NMS to obtain stable performance improvement. Finally, a well-designed ensemble strategy via voting the bounding box location and confidence is proposed. We will also introduce several training/inferencing strategies and a bag of tricks that give minor improvement. Given those masses of details, we train and aggregate 28 global models with various backbones, heads and 3+2 expert models, and achieves the 1st place on the OpenImage 2019 Object Detection Challenge on the both public and private leadboards. Given such good instance bounding box, we further design a simple instance-level semantic segmentation pipeline and achieve the 1st place on the segmentation challenge.
Yu Liu, Guanglu Song, Yuhang Zang, Yan Gao, Enze Xie, Junjie Yan, Chen Change Loy, Xiaogang Wang [pdf]
-
KPNet: Towards Minimal Face Detector -
Abstract
- The small receptive field and capacity of minimal neural networks limit their performance when using them to be the backbone of detectors. In this work, we find that the appearance feature of a generic face is discriminative enough for a tiny and shallow neural network to verify from the background. And the essential barriers behind us are 1) the vague definition of the face bounding box and 2) tricky design of anchor-boxes or receptive field. Unlike most top-down methods for joint face detection and alignment, the proposed KPNet detects small facial keypoints instead of the whole face by in a bottom-up manner. It first predicts the facial landmarks from a low-resolution image via the well-designed fine-grained scale approximation and scale adaptive soft-argmax operator. Finally, the precise face bounding boxes, no matter how we define it, can be inferred from the keypoints. Without any complex head architecture or meticulous network designing, the KPNet achieves state-of-the-art accuracy on generic face detection and alignment benchmarks with only $\sim1M$ parameters, which runs at 1000fps on GPU and is easy to perform real-time on most modern front-end chips.
Guanglu Song, Yu Liu, Yuhang Zang, Xiaogang Wang, Biao Leng, Qingsheng Yuan [pdf]
-
Revisiting the Sibling Head in Object Detector -
Abstract
- The ``shared head for classification and localization'' (sibling head), firstly denominated in Fast RCNN~\cite{girshick2015fast}, has been leading the fashion of the object detection community in the past five years. This paper provides the observation that the spatial misalignment between the two object functions in the sibling head can considerably hurt the training process, but this misalignment can be resolved by a very simple operator called task-aware spatial disentanglement (TSD). Considering the classification and regression, TSD decouples them from the spatial dimension by generating two disentangled proposals for them, which are estimated by the shared proposal. This is inspired by the natural insight that for one instance, the features in some salient area may have rich information for classification while these around the boundary may be good at bounding box regression. Surprisingly, this simple design can boost all backbones and models on both MS COCO and Google OpenImage consistently by ~3% mAP. Further, we propose a progressive constraint to enlarge the performance margin between the disentangled and the shared proposals, and gain ~1% more mAP. We show the \algname{} breaks through the upper bound of nowadays single-model detector by a large margin (mAP 49.4 with ResNet-101, 51.2 with SENet154), and is the core model of our 1st place solution on the Google OpenImage Challenge 2019.
Guanglu Song, Yu Liu, Xiaogang Wang [pdf]
-
Search to Distill: Pearls are Everywhere but not the Eyes -
Abstract
- Standard Knowledge Distillation (KD) approaches distill the knowledge of a cumbersome teacher model into the parameters of a student model with a pre-defined architecture. However, the knowledge of a neural network, which is represented by the network's output distribution conditioned on its input, depends not only on its parameters but also on its architecture. Hence, a more generalized approach for KD is to distill the teacher's knowledge into both the parameters and architecture of the student. To achieve this, we present a new Architecture-aware Knowledge Distillation (AKD) approach that finds student models (pearls for the teacher) that are best for distilling the given teacher model. In particular, we leverage Neural Architecture Search (NAS), equipped with our KD-guided reward, to search for the best student architectures for a given teacher. Experimental results show our proposed AKD consistently outperforms the conventional NAS plus KD approach, and achieves state-of-the-art results on the ImageNet classification task under various latency settings. Furthermore, the best AKD student architecture for the ImageNet classification task also transfers well to other tasks such as million level face recognition and ensemble learning.
Yu Liu, Xuhui Jia, Mingxing Tan, Raviteja Vemulapalli, Yukun Zhu, Bradley Green, Xiaogang Wang [pdf]
-
SeqXY2SeqZ: Structure Learning for 3D Shapes by Sequentially Predicting
1D Occupancy Segments From 2D Coordinates -
Abstract
- Structure learning for 3D shapes is vital for 3D computer vision. State-of-the-art methods show promising results by representing shapes using implicit functions in 3D that are learned using discriminative neural networks. However, learning implicit functions requires dense and irregular sampling in 3D space, which also makes the sampling methods affect the accuracy of shape reconstruction during test. To avoid dense and irregular sampling in 3D, we propose to represent shapes using 2D functions, where the output of the function at each 2D location is a sequence of line segments inside the shape. Our approach leverages the power of functional representations, but without the disadvantage of 3D sampling. Specifically, we use a voxel tubelization to represent a voxel grid as a set of tubes along any one of the X, Y, or Z axes. Each tube can be indexed by its 2D coordinates on the plane spanned by the other two axes. We further simplify each tube into a sequence of occupancy segments. Each occupancy segment consists of successive voxels occupied by the shape, which leads to a simple representation of its 1D start and end location. Given the 2D coordinates of the tube and a shape feature as condition, this representation enables us to learn 3D shape structures by sequentially predicting the start and end locations of each occupancy segment in the tube. We implement this approach using a Seq2Seq model with attention, called SeqXY2SeqZ, which learns the mapping from a sequence of 2D coordinates along two arbitrary axes to a sequence of 1D locations along the third axis. SeqXY2SeqZ not only benefits from the regularity of voxel grids in training and testing, but also achieves high memory efficiency. Our experiments show that SeqXY2SeqZ outperforms the state-ofthe-art methods under widely used benchmarks.
Zhizhong Han, Guanhui Qiao, Yu-Shen Liu, Matthias Zwicker [pdf]
-
Universal thermodynamic relations with constant corrections for rotating AdS black holes -
Abstract
- In [Phys. Rev. Lett. 124, 101103 (2020)], a universal relation between corrections to entropy and extremality was proposed. The relation was also found to exactly hold for the four-dimensional charged AdS black hole. In this paper, we extend the study to the rotating BTZ and Kerr-AdS black holes when a constant correction to General Relativity is considered for the first time. The entropy and extremality bound are calculated, and they have a closely dependent behavior with the coupling parameter of the constant correction. We confirm the universal relation for the rotating AdS black holes. Furthermore, taking into consideration of the shift of the angular momentum, we confirm one more new universal relation for the rotating cases. In particular, we state a conjecture on a universal relation, which gives a universal conjecture relation between the shifted thermodynamic quantities for arbitrary black hole background. We believe that these universal relations will shed new light on the region of the quantum gravity.
Shao-Wen Wei, Ke Yang, Yu-Xiao Liu [pdf] DOI: 10.1016/j.nuclphysb.2020.115279 2003.06785v1 [pdf]
-
Hearts of cotorsion pairs are functor categories over cohearts -
Abstract
- We study hearts of cotorsion pairs in triangulated and exact categories.We give a sufficient and necessary condition when the hearts have enough projectives. We also show in such condition they are equivalent to functor categories over cohearts of the cotorsion pairs.
Yu Liu [pdf]
-
Top-1 Solution of Multi-Moments in Time Challenge 2019 -
Abstract
- In this technical report, we briefly introduce the solutions of our team 'Efficient' for the Multi-Moments in Time challenge in ICCV 2019. We first conduct several experiments with popular Image-Based action recognition methods TRN, TSN, and TSM. Then a novel temporal interlacing network is proposed towards fast and accurate recognition. Besides, the SlowFast network and its variants are explored. Finally, we ensemble all the above models and achieve 67.22\% on the validation set and 60.77\% on the test set, which ranks 1st on the final leaderboard. In addition, we release a new code repository for video understanding which unifies state-of-the-art 2D and 3D methods based on PyTorch. The solution of the challenge is also included in the repository, which is available at https://github.com/Sense-X/X-Temporal.
Manyuan Zhang, Hao Shao, Guanglu Song, Yu Liu, Junjie Yan [pdf]
-
An Empirical “High-confidence” Candidate Zone for
-
Abstract
- In the third catalog of active galactic nuclei detected by the $Fermi$ Large Area Telescope Clean (3LAC) sample, there are 402 blazars candidates of uncertain type (BCU). The proposed analysis will help to evaluate the potential optical classification flat spectrum radio quasars (FSRQs) versus BL Lacertae (BL Lacs) objects of BCUs, which can help to understand which is the most elusive class of blazar hidden in the Fermi sample. By studying the 3LAC sample, we found some critical values of $\gamma$-ray photon spectral index ($\Gamma_{\rm ph}$), variability index (VI) and radio flux (${\rm F_R}$) of the sources separate known FSRQs and BL Lac objects. We further utilize those values to defined an empirical "high-confidence" candidate zone that can be used to classify the BCUs. Within such a zone ($\Gamma_{\rm ph}<2.187$, log${\rm F_R}<2.258$ and ${ \rm logVI <1.702}$), we found that 120 BCUs can be classified BL Lac candidates with a higher degree of confidence (with a misjudged rate $<1\%$). Our results suggest that an empirical "high confidence" diagnosis is possible to distinguish the BL Lacs from the Fermi observations based on only on the direct observational data of $\Gamma_{\rm ph}$, VI and ${\rm F_R}$.
Shi-Ju Kang, Kerui Zhu, Jianchao Feng, Qingwen Wu, Bin-Bin Zhang, Yue Yin, Fei-Fei Wang, Yu Liu, Tian-Yuan Zheng [pdf] DOI: 10.3847/1538-4357/ab722d 2003.05942v1 [pdf]
-
Transparent Gatable Superconducting Shadow Junctions -
Abstract
- Gate tunable junctions are key elements in quantum devices based on hybrid semiconductor-superconductor materials. They serve multiple purposes ranging from tunnel spectroscopy probes to voltage-controlled qubit operations in gatemon and topological qubits. Common to all is that junction transparency plays a critical role. In this study, we grow single crystalline InAs, InSb and $\mathrm{InAs_{1-x}Sb_x}$ nanowires with epitaxial superconductors and in-situ shadowed junctions in a single-step molecular beam epitaxy process. We investigate correlations between fabrication parameters, junction morphologies, and electronic transport properties of the junctions and show that the examined in-situ shadowed junctions are of significantly higher quality than the etched junctions. By varying the edge sharpness of the shadow junctions we show that the sharpest edges yield the highest junction transparency for all three examined semiconductors. Further, critical supercurrent measurements reveal an extraordinarily high $I_\mathrm{C} R_\mathrm{N}$, close to the KO$-$2 limit. This study demonstrates a promising engineering path towards reliable gate-tunable superconducting qubits.
-
Bandgap-assisted quantum control of topological edge states in a cavity -
Abstract
- Quantum matter with exotic topological order has potential applications in quantum computation. However, in present experiments, the manipulations on topological states are still challenging. We here propose an architecture for optical control of topological matter. We consider a topological superconducting qubit array with Su-Schrieffer-Heeger (SSH) Hamiltonian which couples to a microwave cavity. Based on parity properties of the topological qubit array, we propose an optical spectroscopy method to observe topological phase transition, i.e., edge-to-bulk transition. This new method can be achieved by designing cavity-qubit couplings. A main purpose of this work is to understand how topological phase transition affects light-matter interaction. We find that topological bandgap plays an essential role on this issue. In topological phase, the resonant vacuum Rabi splitting of degenerate edge states coupling to the cavity field is protected from those of bulk states by the bandgap. In dispersive regime, the cavity induced coupling between edge states is dominant over couplings between edge and bulk states, due to the topological bandgap. As a result, quantum interference between topological edge states occures and enables single-photon transport through boundaries of the topological qubit array. Our work may pave a way for topological quantum state engineering.
Wei Nie, Yu-xi Liu Journal reference: Phys. Rev. Research 2, 012076 (2020) [pdf] DOI: 10.1103/PhysRevResearch.2.012076
-
New insights into thermodynamics and microstructure of AdS black holes -
Abstract
- Recently, black hole thermodynamics and phase transition have been studied in the extended phase space. Besides the VdW-like phase transition, more interesting phase transitions were found. More interestingly, combining with the thermodynamic geometry, the microstructure of black holes was investigated.In this paper, we give a brief review of recent progress on this subject.
Shao-Wen Wei, Yu-Xiao Liu Journal reference: Science Bulletin 65 (2020) 259-261 [pdf] DOI: 10.1016/j.scib.2019.11.020
-
Intriguing microstructures of five-dimensional neutral Gauss-Bonnet AdS black hole -
Abstract
- In this paper, we analytically study the phase structure and construct the Ruppeiner geometry in the extended phase space for the five-dimensional neutral Gauss-Bonnet AdS black hole. Through calculating the scalar curvature of the Ruppeiner geometry and combining the phase transition, we show that the attractive interaction is dominant in the microstructure of the black hole system. More significantly, there is an intriguing property that the normalized scalar curvature has the same expression for the saturated small and large black hole curves. This implies that although the microstructure is different before and after the small-large black hole phase transition, the interaction between the microscopic constituents keeps unchanged. These results are quite valuable on further understanding the microstructure of the AdS black hole in modified gravity.
Shao-Wen Wei, Yu-Xiao Liu Journal reference: Phys.Lett. B 803, 135287 (2020) [pdf] DOI: 10.1016/j.physletb.2020.135287
-
High-temperature Anomalous Hall Effect in Transition Metal
Dichalcogenide-Ferromagnetic Insulator Heterostructure -
Abstract
- Integration of transition metal dichalcogenides (TMDs) on ferromagnetic materials (FM) may yield fascinating physics and promise for electronics and spintronic applications. In this work, high-temperature anomalous Hall effect (AHE) in the TMD ZrTe2 thin film using heterostructure approach by depositing it on ferrimagnetic insulator YIG (Y3Fe5O12, yttrium iron garnet) is demonstrated. In this heterostructure, significant anomalous Hall effect can be observed at temperatures up to at least 400 K, which is a record high temperature for the observation of AHE in TMDs, and the large RAHE is more than one order of magnitude larger than those previously reported value in topological insulators or TMDs based heterostructures. The magnetization of interfacial reaction-induced ZrO2 between YIG and ZrTe2 is believed to play a crucial role for the induced high-temperature anomalous Hall effect in the ZrTe2. These results reveal a promising system for the room-temperature spintronic device applications, and it may also open a new avenue toward introducing magnetism to TMDs and exploring the quantum AHE at higher temperatures considering the prediction of nontrivial topology in ZrTe2.
Sheung Mei Ng, Hui Chao Wang, Yu Kuai Liu, Hon Fai Wong, Hei Man Yau, Chun Hung Suen, Ze Han Wu, Chi Wah Leung, Ji Yan Dai [pdf]
-
Quantifying urban areas with multi-source data based on percolation theory -
Abstract
- Quantifying urban areas is crucial for addressing associated urban issues such as environmental and sustainable problems. Remote sensing data, especially the nighttime light images, have been widely used to delineate urbanized areas across the world. Meanwhile, some emerging urban data, such as volunteered geographical information (e.g., OpenStreetMap) and social sensing data (e.g., mobile phone and social media), have also shown great potential in revealing urban boundaries and dynamics. However, consistent and robust methods to quantify urban areas from these multi-source data have remained elusive. Here, we propose a percolation-based method to extract urban areas from these multi-source urban data. We derive the optimal urban/non-urban threshold by considering the critical nature of urban systems with the support of the percolation theory. Furthermore, we apply the method with three open-source datasets - population, road, and nighttime light - to 28 countries. We show that the proposed method captures the similar urban characteristics in terms of urban areas from multi-source data, and Zipf's law holds well in most countries. The accuracy of the derived urban areas by different datasets has been validated with the Landsat-based reference data in 10 cities, and the accuracy can be further improved through data fusion ($\kappa=0.69-0.85$, mean $\kappa=0.78$). Our study not only provides an efficient method to quantify urban areas with open-source data, but also deepens the understanding of urban systems and sheds some light on multi-source data fusion in geographical fields.
Wenpu Cao, Lei Dong, Lun Wu, Yu Liu Journal reference: Remote Sensing of Environment, (2020) [pdf] DOI: 10.1016/j.rse.2020.111730
-
Photo-excitation of long-lived transient intermediates in ultracold reactions -
Abstract
- Controlling the pathways and outcomes of reactions is a broadly pursued goal in chemistry. In gas phase reactions, this is typically achieved by manipulating the properties of the reactants, including their translational energy, orientation, and internal quantum state. In contrast, here we influence the pathway of a reaction via its intermediate complex, which is generally too short-lived to be affected by external processes. In particular, the ultracold preparation of potassium-rubidium (KRb) reactants leads to a long-lived intermediate complex (K$_2$Rb$_2^*$), which allows us to steer the reaction away from its nominal ground-state pathway onto a newly identified excited-state pathway using a laser source at 1064 nm, a wavelength commonly used to confine ultracold molecules. Furthermore, by monitoring the change in the complex population after the sudden removal of the excitation light, we directly measure the lifetime of the complex to be $360 \pm 30$ ns, in agreement with our calculations based on the Rice-Ramsperger-Kassel-Marcus (RRKM) statistical theory. Our results shed light on the origin of the two-body loss widely observed in ultracold molecule experiments. Additionally, the long complex lifetime, coupled with the observed photo-excitation pathway, opens up the possibility to spectroscopically probe the structure of the complex with high resolution, thus elucidating the reaction dynamics.
Yu Liu, Ming-Guang Hu, Matthew A. Nichols, David D. Grimes, Tijs Karman, Hua Guo, Kang-Kuen Ni Journal reference: Nature Physics, volume 16, pages 1132-1136 (2020) [pdf] DOI: 10.1038/s41567-020-0968-8
-
3D Gated Recurrent Fusion for Semantic Scene Completion -
Abstract
- This paper tackles the problem of data fusion in the semantic scene completion (SSC) task, which can simultaneously deal with semantic labeling and scene completion. RGB images contain texture details of the object(s) which are vital for semantic scene understanding. Meanwhile, depth images capture geometric clues of high relevance for shape completion. Using both RGB and depth images can further boost the accuracy of SSC over employing one modality in isolation. We propose a 3D gated recurrent fusion network (GRFNet), which learns to adaptively select and fuse the relevant information from depth and RGB by making use of the gate and memory modules. Based on the single-stage fusion, we further propose a multi-stage fusion strategy, which could model the correlations among different stages within the network. Extensive experiments on two benchmark datasets demonstrate the superior performance and the effectiveness of the proposed GRFNet for data fusion in SSC. Code will be made available.
Yu Liu, Jie Li, Qingsen Yan, Xia Yuan, Chunxia Zhao, Ian Reid, Cesar Cadena [pdf]
-
Hyperspectral Classification Based on 3D Asymmetric Inception Network
with Data Fusion Transfer Learning -
Abstract
- Hyperspectral image(HSI) classification has been improved with convolutional neural network(CNN) in very recent years. Being different from the RGB datasets, different HSI datasets are generally captured by various remote sensors and have different spectral configurations. Moreover, each HSI dataset only contains very limited training samples and thus it is prone to overfitting when using deep CNNs. In this paper, we first deliver a 3D asymmetric inception network, AINet, to overcome the overfitting problem. With the emphasis on spectral signatures over spatial contexts of HSI data, AINet can convey and classify the features effectively. In addition, the proposed data fusion transfer learning strategy is beneficial in boosting the classification performance. Extensive experiments show that the proposed approach beat all of the state-of-art methods on several HSI benchmarks, including Pavia University, Indian Pines and Kennedy Space Center(KSC). Code can be found at: https://github.com/UniLauX/AINet.
Haokui Zhang, Yu Liu, Bei Fang, Ying Li, Lingqiao Liu, Ian Reid [pdf]
-
The Accurate Modification of Tunneling Radiation of Fermions with
Arbitrary Spin in Kerr-de Sitter Black Hole Space-time -
Abstract
- The quantum tunneling radiation of fermions with arbitrary spin at the event horizon of Kerr-de Sitter black hole is accurately modified by using the dispersion relation proposed in the study of string theory and quantum gravitational theory. The derived tunneling rate and temperature at the black hole horizons are analyzed and studied.
Bei Sha, Zhi-E Liu, Xia Tan, Yu-Zhen Liu, Jie Zhang [pdf]
-
Accurate correction of arbitrary spin fermion quantum tunneling from non-stationary Kerr-de Sitter black hole based on corrected Lorentz dispersion relation -
Abstract
- According to a corrected dispersion relation proposed in the study on string theory and quantum gravity theory, Rarita-Schwinger equation has been precisely modified, which results in a Rarita-Schwinger-Hamilton-Jacobi equation, and through which, the characteristics of arbitrary spin fermions quantum tunneling radiation from non-stationary Kerr-de Sitter black hole are researched. A series of accurately corrected physical quantities such as surface gravity, chemical potential, tunneling probability and Hawking temperature that describe the properties of the black hole are derived. This research has enriched the research methods and made precision of the research contents of black hole physics.
Bei Sha, Zhi-E Liu, Yu-Zhen Liu, Xia Tan, Jie Zhang, Shu-Zheng Yang [pdf] DOI: 10.1088/1674-1137/abb4d6 2002.03368v1 [pdf]
-
On the Fairness of Name-Based Rationing System for Purchases of Masks
Policy -
Abstract
- In this paper, mathematical model and condition are built for the analysis of fairness of name-based rationing system for purchases of masks policy announced and launched in Taiwan.
Yu-Ting Liu [pdf]
-
Long-Range Gesture Recognition Using Millimeter Wave Radar -
Abstract
- Millimeter wave (mmWave) based gesture recognition technology provides a good human computer interaction (HCI) experience. Prior works focus on the close-range gesture recognition, but fall short in range extension, i.e., they are unable to recognize gestures more than one meter away from considerable noise motions. In this paper, we design a long-range gesture recognition model which utilizes a novel data processing method and a customized artificial Convolutional Neural Network (CNN). Firstly, we break down gestures into multiple reflection points and extract their spatial-temporal features which depict gesture details. Secondly, we design a CNN to learn changing patterns of extracted features respectively and output the recognition result. We thoroughly evaluate our proposed system by implementing on a commodity mmWave radar. Besides, we also provide more extensive assessments to demonstrate that the proposed system is practical in several real-world scenarios.
Yu Liu, Yuheng Wang, Haipeng Liu, Anfu Zhou, Jianhua Liu, Ning Yang [pdf]
-
Lorentz symmetry violation and the tunneling radiation of fermions with
spin $1/2$ for Kerr Anti-de-Sitter black hole -
Abstract
- We studied the correction of the quantum tunneling radiation of fermions with spin $1/2$ in Kerr Anti-de-Sitter black hole. First, the dynamic equation of spin $1/2$ fermions was corrected using Lorentz's violation theory. Second, the new expressions of the fermions quantum tunneling rate, the Hawking temperature of the black hole and the entropy of the black hole were obtained according to the corrected fermions dynamic equation. At last, some comments are made on the results of our work.
Zhi-E Liu, Xia Tan, Yu-Zhen Liu, Bei Sha, Jie Zhang, Shu-Zheng Yang [pdf]
-
Site testing campaign for the Large Optical/infrared Telescope of China: overview -
Abstract
- The Large Optical/infrared Telescope (LOT) is a ground-based 12m diameter optical/infrared telescope which is proposed to be built in the western part of China in the next decade. Based on satellite remote sensing data, along with geographical, logistical and political considerations, three candidate sites were chosen for ground-based astronomical performance monitoring. These sites include: Ali in Tibet, Daocheng in Sichuan, and Muztagh Ata in Xinjiang. Up until now, all three sites have continuously collected data for two years. In this paper, we will introduce this site testing campaign, and present its monitoring results obtained during the period between March 2017 and March 2019.
Lu Feng, Jin-Xin Hao, Zi-Huang Cao, Jin-Min Bai, Ji Yang, Xu Zhou, Yong-Qiang Yao, Jin-Liang Hou, Yong-Heng Zhao, Yu Liu, Teng-Fei Song, Li-Yong Liu, Jia Yin, Hua-Lin Chen, Chong Pei, Ali Esamdin, Lu Ma, Chun-Hai Bai, Peng Wei, Jing Xu, Guang-Xin Pu, Guo-Jie Feng, Xuan Zhang, Liang Ming, Abudusaimaitijiang Yisikandee, Jian-Rong Shi, Jian Li, Yuan Tian, Zheng Wang, Xia Wang, Xiao-Jun Jiang, Jian-Feng Wang, Jian-Feng Tian, Yan-Jie Xue, Jian-Sheng Chen, Jing-Yao Hu, Zhi-Xia Shen, Yun-Ying Jiang [pdf] DOI: 10.1088/1674-4527/20/6/80 2001.11378v2 [pdf]
-
MVDLite: A Light-weight Model View Definition Representation with Fast
Validation for Building Information Model -
Abstract
- Model View Definition (MVD) is the standard methodology to define the exchange requirements and data constraints for Building Information Model (BIM). In this paper, MVDLite is proposed as a novel light-weight representation for MVD. Compared with mvdXML, MVDLite is more concise and could be used in more flexible scenarios. MVDLite introduces a "rule chain" structure to combine the subgraph templates and value constants, based on which a fast MVD validation algorithm is proposed. It is also compatible with the current mvdXML format, and supports bi-directional conversion with mvdXML. A case study is provided to show the workflow for developing an enterprise-level MVD based on MVDLite, and its applications in MVD validation and partial model extraction. The outperforming experimental results show that our method is much faster than the state-of-the-art methods on large real-world models.
Han Liu, Ge Gao, Hehua Zhang, Yu-Shen Liu, Yan Song, Ming Gu [pdf]
-
Depth Based Semantic Scene Completion with Position Importance Aware
Loss -
Abstract
- Semantic Scene Completion (SSC) refers to the task of inferring the 3D semantic segmentation of a scene while simultaneously completing the 3D shapes. We propose PALNet, a novel hybrid network for SSC based on single depth. PALNet utilizes a two-stream network to extract both 2D and 3D features from multi-stages using fine-grained depth information to efficiently captures the context, as well as the geometric cues of the scene. Current methods for SSC treat all parts of the scene equally causing unnecessary attention to the interior of objects. To address this problem, we propose Position Aware Loss(PA-Loss) which is position importance aware while training the network. Specifically, PA-Loss considers Local Geometric Anisotropy to determine the importance of different positions within the scene. It is beneficial for recovering key details like the boundaries of objects and the corners of the scene. Comprehensive experiments on two benchmark datasets demonstrate the effectiveness of the proposed method and its superior performance. Models and Video demo can be found at: https://github.com/UniLauX/PALNet.
Yu Liu, Jie Li, Xia Yuan, Chunxia Zhao, Roland Siegwart, Ian Reid, Cesar Cadena [pdf]
-
Number of constituent quark scaling of elliptic flows in high multiplicity p-Pb collisions at
-
Abstract
- We briefly summarize our recent study on the number of constituent quark (NCQ) scaling of hadron elliptic flows in high multiplicity p-Pb collisions at $\sqrt{s_{NN}}=$ 5.02 TeV. With the inclusion of hadron production via the quark coalescence model at intermediate $p_T$, the viscous hydrodynamics at low $p_T$, and jet fragmentation at high $p_T$, our $Hydro-Coal-Frag$ model provides a nice description of the $p_T$-spectra and differential elliptic flow $v_2(p_T)$ of pions, kaons and protons over the $p_T$ range from 0 to 6 GeV. Our results demonstrate that including the quark coalescence is essential for reproducing the observed approximate NCQ scaling of hadron $v_2$ at intermediate $p_T$ in experiments, indicating strongly the existence of partonic degrees of freedom and the formation of quark-gluon plasma in high multiplicity p--Pb collisions at the LHC.
Wenbin Zhao, Che Ming Ko, Yu-Xin Liu, Guang-You Qin, Huichao Song [pdf] DOI: 10.1016/j.nuclphysa.2020.121876 2001.10689v1 [pdf]
-
Topologically Protected Quantum Coherence in a Superatom -
Abstract
- Exploring the properties and applications of topological quantum states is essential to better understand topological matter. Here, we theoretically study a quasi-one-dimensional topological atom array. In the low-energy regime, the atom array is equivalent to a topological superatom. Driving the superatom in a cavity, we study the interaction between light and topological quantum states. We find that the edge states exhibit topology-protected quantum coherence, which can be characterized from the photon transmission. This quantum coherence helps us to find a superradiance-subradiance transition, and we also study its finite-size scaling behavior. The superradiance-subradiance transition also exists in symmetry-breaking systems. More importantly, it is shown that the quantum coherence of the subradiant edge state is robust to random noises, allowing the superatom to work as a topologically protected quantum memory. We suggest a relevant experiment with three-dimensional circuit QED. Our study may have applications in quantum computation and quantum optics based on topological edge states.
Wei Nie, Z. H. Peng, Franco Nori, Yu-xi Liu Journal reference: Phys. Rev. Lett. 124, 023603 (2020) [pdf] DOI: 10.1103/PhysRevLett.124.023603
-
Collision of two kinks with inner structure -
Abstract
- In this work, we study kink collisions in a scalar field model with scalar-kinetic coupling. This model supports kink/antikink solutions with inner structure in the energy density. The collision of two such kinks is simulated by using the Fourier spectral method. We numerically calculate how the critical velocity and the widths of the first three two bounce windows vary with the model parameters. After that, we report some interesting collision results including two-bion escape final states, kink-bion-antikink intermediate states and kink or antikink intertwined final states. These results show that kinks with inner structure in the energy density have similar properties as those of the double kinks.
Yuan Zhong, Xiao-Long Du, Zhou-Chao Jiang, Yu-Xiao Liu, Yong-Qiang Wang Journal reference: JHEP02(2020)153 [pdf] DOI: 10.1007/JHEP02(2020)153
-
Low-Complexity LSTM Training and Inference with FloatSD8 Weight
Representation -
Abstract
- The FloatSD technology has been shown to have excellent performance on low-complexity convolutional neural networks (CNNs) training and inference. In this paper, we applied FloatSD to recurrent neural networks (RNNs), specifically long short-term memory (LSTM). In addition to FloatSD weight representation, we quantized the gradients and activations in model training to 8 bits. Moreover, the arithmetic precision for accumulations and the master copy of weights were reduced from 32 bits to 16 bits. We demonstrated that the proposed training scheme can successfully train several LSTM models from scratch, while fully preserving model accuracy. Finally, to verify the proposed method's advantage in implementation, we designed an LSTM neuron circuit and showed that it achieved significantly reduced die area and power consumption.
Yu-Tung Liu, Tzi-Dar Chiueh [pdf]
-
Temporal Interlacing Network -
Abstract
- For a long time, the vision community tries to learn the spatio-temporal representation by combining convolutional neural network together with various temporal models, such as the families of Markov chain, optical flow, RNN and temporal convolution. However, these pipelines consume enormous computing resources due to the alternately learning process for spatial and temporal information. One natural question is whether we can embed the temporal information into the spatial one so the information in the two domains can be jointly learned once-only. In this work, we answer this question by presenting a simple yet powerful operator -- temporal interlacing network (TIN). Instead of learning the temporal features, TIN fuses the two kinds of information by interlacing spatial representations from the past to the future, and vice versa. A differentiable interlacing target can be learned to control the interlacing process. In this way, a heavy temporal model is replaced by a simple interlacing operator. We theoretically prove that with a learnable interlacing target, TIN performs equivalently to the regularized temporal convolution network (r-TCN), but gains 4% more accuracy with 6x less latency on 6 challenging benchmarks. These results push the state-of-the-art performances of video understanding by a considerable margin. Not surprising, the ensemble model of the proposed TIN won the $1^{st}$ place in the ICCV19 - Multi Moments in Time challenge. Code is made available to facilitate further research at https://github.com/deepcs233/TIN
Hao Shao, Shengju Qian, Yu Liu [pdf]
-
Weak cosmic censorship conjecture for a Kerr-Taub-NUT black hole with a test scalar field and particle -
Abstract
- Motivated by the recent researches of black holes with NUT charge, we investigate the validity of the weak cosmic censorship conjecture for Kerr-Taub-NUT black hole with a test massive scalar field and a test particle, respectively. For the scalar field scattering gedanken experiment, we consider an infinitesimal time interval process. The result shows that both extremal and near-extremal Kerr-Taub-NUT black holes cannot be over-spun. For the test particle thought experiment, the study suggests that extremal Kerr-Taub-NUT black hole cannot be over-spun; while near-extremal Kerr-Taub-NUT black hole can be over-spun. By comparing the two methods, the results indicate the time interval for particles crossing the black hole horizon might be important for consideration of the weak cosmic censorship conjecture.
Si-Jiang Yang, Jing Chen, Jun-Jie Wan, Shao-Wen Wei, Yu-Xiao Liu Journal reference: Phys. Rev. D 101, 064048 (2020) [pdf] DOI: 10.1103/PhysRevD.101.064048
-
Generalized geometrical coupling for vector field localization on thick brane in asymptotic anti–de Sitter spacetime -
Abstract
- It is known that a five-dimensional free vector field $A_{M}$ cannot be localized on Randall-Sundrum (RS)-like thick branes, namely, the thick branes embedded in asymptotic Anti-de Sitter (AdS) spacetime. In order to localize a vector field on the RS-like thick brane, an extra coupling term should be introduced. In this paper, we generalize the geometrical coupling mechanism by adding two mass terms ($\alpha Rg^{MN}A_{M}A_{N}+\beta R^{MN}A_{M}A_{N}$) into the action. We decompose the fundamental vector field $A_{M}$ into three parts: transverse vector part $\hat{A}_{\mu}$, scalar parts $\phi$ and $A_{5}$. Then, we find that the transverse vector part $\hat{A}_{\mu}$ decouples from the scalar parts. In order to eliminate the tachyonic modes of $\hat{A}_{\mu}$, the two coupling parameters $\alpha$ and $\beta$ should satisfy a relation. Combining the restricted condition, we can get a combination parameter as $\gamma=\frac{3}{2}\pm\sqrt{1+12\alpha}$. Only if $\gamma>1/2$, the zero mode of $\hat{A}_{\mu}$ can be localized on the RS-like thick brane. We also investigate the resonant character of the vector part $\hat{A}_{\mu}$ for the general RS-like thick brane with the warp factor $A(z)=-\ln(1+k^2z^2)/2$ by choosing the relative probability method. The result shows that, only for $\gamma>3$, the massive resonant Kaluza-Klein modes can exist. The number of resonant Kaluza-Klein states increases with the combination parameter $\gamma$, and the lifetime of the first resonant state can be long enough as the age of our universe. This indicates that the vector resonances might be considered as one of the candidates of dark matter.
Tao-Tao Sui, Wen-Di Guo, Qun-Ying Xie, Yu-Xiao Liu Journal reference: Phys. Rev. D 101, 055031 (2020) [pdf] DOI: 10.1103/PhysRevD.101.055031
-
-
Abstract
- We predict the masses of the lowlying $B_c$ mesons with $J^P = 0^-,\,1^-,\,0^+,\,1^+,\,2^+$, using a flavor dependent interaction pattern which gives an unified successful description of the light, heavy-light and heavy mesons and is also appliable to the radial excited heavy mesons. The errors are controlled carefully. With the errors from the RL approximation subduced, our predictions are consistent with the lQCD and quark model results, which supports strongly that the flavor dependent interaction pattern is reasonable. Our predictions provide significant guides to the experiment search of the $B_c$ mesons.
Muyang Chen, Lei Chang, Yu-xin Liu Journal reference: Phys. Rev. D 101, 056002 (2020) [pdf] DOI: 10.1103/PhysRevD.101.056002
-
Heavy-light mesons beyond the ladder approximation -
Abstract
- The heavy-light mesons are studied within the framework of Dyson-Schwinger equations of QCD. Inspired by the axial-vector Ward-Takahashi identity resulting from the chiral symmetry, we propose a truncation scheme beyond the ladder approximation without introducing any additional parameter. For the pseudoscalar and vector heavy-light mesons, the obtained mass spectrum has the level of relative errors at $5\%$ compared with experimental data and lattice-QCD results. For the leptonic decay constants, our results are comparable with those from experiments and/or lattice QCD. For some channels, the discrepancies are sizable but significantly smaller than those using the equal spacing rule. The truncation scheme proposed in this work is simple and could be improved and applied to study other open flavor hadrons including both mesons and baryons.
Pianpian Qin, Si-xue Qin, Yu-xin Liu Journal reference: Phys. Rev. D 101, 114014 (2020) [pdf] DOI: 10.1103/PhysRevD.101.114014
-
Unpolarized isovector quark distribution function from lattice QCD: A systematic analysis of renormalization and matching -
Abstract
- We present a detailed Lattice QCD study of the unpolarized isovector quark Parton Distribution Function (PDF) using large-momentum effective theory framework. We choose a quasi-PDF defined by a spatial correlator which is free from mixing with other operators of the same dimension. In the lattice simulation, we use a Gaussian-momentum-smeared source at $M_\pi=356$ MeV and $P_z \in \{1.8,2.3\}$ GeV. To control the systematics associated with the excited states, we explore {five different source-sink separations}. The nonperturbative renormalization is conducted in a regularization-independent momentum subtraction scheme, and the matching between the renormalized quasi-PDF and $\bar{\rm MS}$ PDF is calculated based on perturbative QCD up to one-loop order. Systematic errors due to renormalization and perturbative matching are also analyzed in detail. Our results for lightcone PDF are in reasonable agreement with the latest phenomenological analysis.
Yu-Sheng Liu, Jiunn-Wei Chen, Yi-Kai Huo, Luchang Jin, Maximilian Schlemmer, Andreas Schäfer, Peng Sun, Wei Wang, Yi-Bo Yang, Jian-Hui Zhang, Qi-An Zhang, Kuan Zhang, Yong Zhao Journal reference: Phys. Rev. D 101, 034020 (2020) [pdf] DOI: 10.1103/PhysRevD.101.034020
-
Quantum numbers of the pentaquark states ${{\rm{P}}}_{{\rm{c}}}^{+}$ via symmetry analysis -
Abstract
- We investigate the quantum numbers of the pentaquark states $\textrm{P}_{\textrm{c}}^{+}$, which are composed of four (three flavors) quarks and an antiquark, by analyzing their inherent nodal structure in this paper. Assuming that the four quarks form a tetrahedron or a square, and the antiquark locates at the center of the four quark cluster, we determine the nodeless structure of the states with orbital angular moment $L \leq 3$, and in turn, the accessible low-lying states. Since the inherent nodal structure depends only on the inherent geometric symmetry, we propose the quantum numbers $J^{P}$ of the low-lying pentaquark states $\textrm{P}_{c}^{+}$ may be ${\frac{3}{2}}^{-}$, ${\frac{5}{2}}^{-} $, ${\frac{3}{2}}^{+}$, ${\frac{5}{2}}^{+} $, independent of dynamical models.
Chong-yao Chen, Muyang Chen, Yu-xin Liu Journal reference: Commun. Theor. Phys. 72, 125202 (2020) [pdf] DOI: 10.1088/1572-9494/abb7cd
-
Critical behavior and magnetocaloric effect in
-
Abstract
- Layered van der Waals ferromagnets are promising candidates for designing new spintronic devices. Here we investigated the critical properties and magnetocaloric effect connected with ferromagnetic transition in layered van der Waals VI$_3$ single crystals. The critical exponents $\beta = 0.244(5)$ with a critical temperature $T_c = 50.10(2)$ K and $\gamma = 1.028(12)$ with $T_c = 49.97(5)$ K are obtained from the modified Arrott plot, whereas $\delta = 5.24(2)$ is obtained from a critical isotherm analysis at $T_c = 50$ K. The magnetic entropy change $-\Delta S_M(T,H)$ features a maximum at $T_c$, i.e., $-\Delta S_M^{max} \sim$ 2.64 (2.27) J kg$^{-1}$ K$^{-1}$ with out-of-plane (in-plane) field change of 5 T. This is consistent with $-\Delta S_M^{max}$ $\sim$ 2.80 J kg$^{-1}$ K$^{-1}$ deduced from heat capacity and the corresponding adiabatic temperature change $\Delta T_{ad}$ $\sim$ 0.96 K with out-of-plane field change of 5 T. The critical analysis suggests that the ferromagnetic phase transition in VI$_3$ is situated close to a three- to two-dimensional critical point. The rescaled $\Delta S_M(T,H)$ curves collapse onto a universal curve, confirming a second-order type of the magnetic transition and reliability of the obtained critical exponents.
Yu Liu, Milinda Abeykoon, C. Petrovic Journal reference: Phys. Rev. Research 2, 013013 (2020) [pdf] DOI: 10.1103/PhysRevResearch.2.013013
-
Generation of macroscopic entangled cat states in a longitudinally coupled cavity-QED model -
Abstract
- Macroscopic entangled cat states not only are significant in the demonstration of the fundamentals of quantum physics, but also have wide applications in modern quantum technologies such as continuous-variable quantum information processing and quantum metrology. Here we propose a scheme for generation of macroscopic entangled cat states in a molecular cavity-QED system, which is composed of an organic molecule (including electronic and vibrational states) coupled to a single-mode cavity field. By simultaneously modulating the resonance frequencies of the molecular vibration and the cavity field, the molecular vibrational displacement can be enhanced significantly and hence macroscopic entangled cat states between the molecular vibrational mode and the cavity mode can be created. We also study quantum coherence effects in the generated states by calculating the joint Wigner function and the degree of entanglement. The dissipation effects are included by considering the state generation in the open-system case. Our results will pave the way to the study of quantum physics and quantum chemistry in molecular cavity-QED systems.
Jian Huang, Yu-Hong Liu, Jin-Feng Huang, Jie-Qiao Liao Journal reference: Phys. Rev. A 101, 043841 (2020) [pdf] DOI: 10.1103/PhysRevA.101.043841
-
New insight about the effective restoration of
-
Abstract
- The effective restoration of the U_{A}(1) symmetry is revisited by implementing the functional renormalization group approach combining with the 2+1 flavor Polyakov-loop quark-meson model. A temperature-dependent 't Hooft term is taken to imitate the restoration of the U_{A}(1) symmetry. Order parameters, meson spectrum and mixing angles, especially the pressure and the entropy density of the system are calculated to explore the effects of different U_{A}(1) symmetry restoration patterns. We show then that the temperature for the restoration of the U_{A}(1) symmetry is much higher than that for the chiral symmetry SU_{A}(3).
Xiang Li, Wei-jie Fu, Yu-xin Liu Journal reference: Phys. Rev. D 101, 054034 (2020) [pdf] DOI: 10.1103/PhysRevD.101.054034
-
Quantum Sensing with a Single-Qubit Pseudo-Hermitian System -
Abstract
- Quantum sensing exploits fundamental features of quantum system to achieve highly efficient measurement of physical quantities. Here, we propose a strategy to realize a single-qubit pseudo-Hermitian sensor from a dilated two-qubit Hermitian system. The pseudo-Hermitian sensor exhibits divergent susceptibility in dynamical evolution that does not necessarily involve exceptional point. We demonstrate its potential advantages to overcome noises that cannot be averaged out by repetitive measurements. The proposal is feasible with the state-of-art experimental capability in a variety of qubit systems, and represents a step towards the application of non-Hermitian physics in quantum sensing.
Yaoming Chu, Yu Liu, Haibin Liu, Jianming Cai Journal reference: Phys. Rev. Lett. 124, 020501 (2020) [pdf] DOI: 10.1103/PhysRevLett.124.020501
-
Observation of Anti-
-
Abstract
- As the counterpart of PT symmetry, abundant phenomena and potential applications of anti-PT symmetry have been predicted or demonstrated theoretically. However, experimental realization of the coupling required in the anti-PT symmetry is difficult. Here, by coupling two YIG spheres to a microwave cavity, the large cavity dissipation rate makes the magnons coupled dissipatively with each other, thereby obeying a two-dimensional anti-PT Hamiltonian. In terms of the magnon-readout method, a new method adopted here, we demonstrate the validity of our method in constructing an anti-PT system and present the counterintuitive level attraction process. Our work provides a new platform to explore the anti-PT symmetry properties and paves the way to study multi-magnoncavity-polariton systems.
Jie Zhao, Yulong Liu, Longhao Wu, Chang-Kui Duan, Yu-xi Liu, Jiangfeng Du Journal reference: Phys. Rev. Applied 13, 014053 (2020) [pdf] DOI: 10.1103/PhysRevApplied.13.014053
-
2D honeycomb borophene oxide: a promising anode material offering super high capacity for Li/Na-ion batteries -
Abstract
- Rational design of novel two-dimensional (2D) electrode materials with high capacity is crucial for the further development of Li-ion and Na-ion batteries. Herein, based on first-principles calculations, we systemically investigate Li and Na storage behaviors in the recently discovered 2D topological nodal-loop metal - the honeycomb borophene oxide (h-B2O). We show that h-B2O is an almost ideal anode material. It has good conductivity before and after Li/Na adsorption, fast ion diffusion with diffusion barrier less than 0.5 eV, low open-circuit voltage (less than 1 V), and small lattice change (less than 6.2%) during intercalation. Most remarkably, its theoretical storage capacity is extremely high, reaching up to 2137 mAh/g for Li and 1425 mAh/g for Na. Its Li storage capacity is more than six times higher than graphite (372 mAh/g), and is actually the highest among all 2D materials discovered to date. Our results strongly suggest that 2D h-B2O is an exceedingly promising anode material for both Li- and Na-ion batteries with super high capacity.
Junping Hu, Chengyong Zhong, Weikang Wu, Ning Liu, Yu Liu, Shengyuan A. Yang, Chuying Ouyang Journal reference: J. Phys.: Condens. Matter 32 (2020) 065001 [pdf] DOI: 10.1088/1361-648X/ab4f4d
-
Excited
-
Abstract
- We study the most recently observed excited $B_{c}$ states with the Dyson-Schwinger equation and the Bethe-Salpeter equation approach of continuum QCD. The obtained $M_{B^+_{c}(2S)}=6.813(16)\text{GeV}$, $M_{B^{*+}_{c}(2S)}=6.841(18)\text{GeV}$ and the mass splitting $M_{B_c^+(2S)}-M^{\text{rec}}_{B_c^{*+}(2S)} \approx 0.039 \text{GeV}$ agree with the observations very well. Moreover we predict the leptonic decay constant $f_{B^+_{c}(2S)}=-0.165(10)\text{GeV}$, $f_{B^{*+}_{c}(2S)}=-0.161(7)\text{GeV}$ respectively.
Lei Chang, Muyang Chen, Yu-xin Liu Journal reference: Phys. Rev. D 102, 074010 (2020) [pdf] DOI: 10.1103/PhysRevD.102.074010
-
Imaging emergent heavy Dirac fermions of a topological Kondo insulator -
Abstract
- Kondo insulators are primary candidates in the search for strongly correlated topological quantum phases, which may host topological order, fractionalization, and non-Abelian statistics. Within some Kondo insulators, the hybridization gap is predicted to protect a nontrivial topological invariant and to harbor emergent heavy Dirac fermion surface modes. We use high-energy-resolution spectroscopic imaging in real and momentum space on the Kondo insulator, SmB$_6$. On cooling through $T^*_{\Delta}\approx$ 35 K we observe the opening of an insulating gap that expands to $\Delta\approx$ 10 meV at 2 K. Within the gap, we image the formation of linearly dispersing surface states with effective masses reaching $m^* = (410\pm20)m_e$. We thus demonstrate existence of a strongly correlated topological Kondo insulator phase hosting the heaviest known Dirac fermions.
Harris Pirie, Yu Liu, A. Soumyanarayanan, Pengcheng Chen, Yang He, M. M. Yee, P. F. S. Rosa, J. D. Thompson, Dae-Jeong Kim, Z. Fisk, Xiangfeng Wang, J. Paglione, Dirk K. Morr, M. H. Hamidian, Jennifer E. Hoffman Journal reference: Nat. Phys. 16, 52 (2020) [pdf] DOI: 10.1038/s41567-019-0700-8
-
A modification of Faddeev–Popov approach free from Gribov ambiguity -
Abstract
- We propose a modified version of the Faddeev-Popov quantization approach for non-Abelian gauge field theory to avoid the Gribov ambiguity. We show that by means of introducing a new method to insert the correct identity into the Yang-Mills generating functional and considering the identity generated by an integral through a subgroup of the gauge group, the problem of the Gribov ambiguity can be removed naturally. Meanwhile by handling the absolute value of the Faddeev-Popov determinant with the method introduced by Williams and collaborators, we lift the Jacobian determinant together with the absolute value and obtain a local Lagrangian. The new Lagrangian have a nilpotent symmetry which can be viewed as an analogue of the BRST symmetry.
Chong-yao Chen, Fei Gao, Yu-xin Liu Journal reference: Commun. Theor. Phys. 72, 125201 (2020) [pdf] DOI: 10.1088/1572-9494/abb7cb
-
Zero-bias peaks at zero magnetic field in ferromagnetic hybrid nanowires -
Abstract
- We report transport measurements and tunneling spectroscopy in hybrid nanowires with epitaxial layers of superconducting Al and the ferromagnetic insulator EuS, grown on semiconducting InAs nanowires. In devices where the Al and EuS covered facets overlap, we infer a remanent effective Zeeman field of order 1 T, and observe stable zero-bias conductance peaks in tunneling spectroscopy into the end of the nanowire, consistent with topological superconductivity at zero applied field. Hysteretic features in critical current and tunneling spectra as a function of applied magnetic field support this picture. Nanowires with non-overlapping Al and EuS covered facets do not show comparable features. Topological superconductivity in zero applied field allows new device geometries and types of control.
S. Vaitiekėnas, Y. Liu, P. Krogstrup, C. M. Marcus [pdf] DOI: 10.1038/s41567-020-1017-3 2004.02226v1 [pdf]
-
Covariant spin kinetic theory I: collisionless limit -
Abstract
- 2019
-
The Sariçiçek howardite fall in Turkey: Source crater of
-
Abstract
- The Sari\c{c}i\c{c}ek howardite meteorite shower consisting of 343 documented stones occurred on 2 September 2015 in Turkey and is the first documented howardite fall. Cosmogenic isotopes show that Sari\c{c}i\c{c}ek experienced a complex cosmic ray exposure history, exposed during ~12-14 Ma in a regolith near the surface of a parent asteroid, and that an ca.1 m sized meteoroid was launched by an impact 22 +/- 2 Ma ago to Earth (as did one third of all HED meteorites). SIMS dating of zircon and baddeleyite yielded 4550.4 +/- 2.5 Ma and 4553 +/- 8.8 Ma crystallization ages for the basaltic magma clasts. The apatite U-Pb age of 4525 +/- 17 Ma, K-Ar age of ~3.9 Ga, and the U,Th-He ages of 1.8 +/- 0.7 and 2.6 +/- 0.3 Ga are interpreted to represent thermal metamorphic and impact-related resetting ages, respectively. Petrographic, geochemical and O-, Cr- and Ti- isotopic studies confirm that Sari\c{c}i\c{c}ek belongs to the normal clan of HED meteorites. Petrographic observations and analysis of organic material indicate a small portion of carbonaceous chondrite material in the Sari\c{c}i\c{c}ek regolith and organic contamination of the meteorite after a few days on soil. Video observations of the fall show an atmospheric entry at 17.3 +/- 0.8 kms-1 from NW, fragmentations at 37, 33, 31 and 27 km altitude, and provide a pre-atmospheric orbit that is the first dynamical link between the normal HED meteorite clan and the inner Main Belt. Spectral data indicate the similarity of Sari\c{c}i\c{c}ek with the Vesta asteroid family spectra, a group of asteroids stretching to delivery resonances, which includes (4) Vesta. Dynamical modeling of meteoroid delivery to Earth shows that the disruption of a ca.1 km sized Vesta family asteroid or a ~10 km sized impact crater on Vesta is required to provide sufficient meteoroids <4 m in size to account for the influx of meteorites from this HED clan.
-
Low-Temperature Thermopower in CoSbS -
Abstract
- We report giant thermopower S = 2.5 mV/K in CoSbS single crystals, a material that shows strong high-temperature thermoelectric performance when doped with Ni or Se. Changes of low temperature thermopower induced by magnetic field point to mechanism of electronic diffusion of carriers in the heavy valence band. Intrinsic magnetic susceptibility is consistent with the Kondo- Insulator-like accumulation of electronic states around the gap edges. This suggests that giant thermopower stems from temperature-dependent renormalization of the non-interacting bands and buildup of the electronic correlations on cooling.
Qianheng Du, Milinda Abeykoon, Yu Liu, G. Kotliar, C. Petrovic Journal reference: Physical Review Letters 123, 076602 (2019) [pdf] DOI: 10.1103/PhysRevLett.123.076602
-
Probing ultracold chemistry using ion spectrometry -
Abstract
- Rapid progress in atomic, molecular, and optical (AMO) physics techniques enabled the creation of ultracold samples of molecular species and opened opportunities to explore chemistry in the ultralow temperature regime. In particular, both the external and internal quantum degrees of freedom of the reactant atoms and molecules are controlled, allowing studies that explored the role of the long range potential in ultracold reactions. The kinetics of these reactions have typically been determined using the loss of reactants as proxies. To extend such studies into the short-range, we developed an experimental apparatus that combines the production of quantum-state-selected ultracold KRb molecules with ion mass and kinetic energy spectrometry, and directly observed KRb + KRb reaction intermediates and products [Science, 2019, 366, 1111]. Here, we present the apparatus in detail. For future studies that aim for detecting the quantum states of the reaction products, we demonstrate a photodissociation based scheme to calibrate the ion kinetic energy spectrometer at low energies.
Yu Liu, David D. Grimes, Ming-Guang Hu, Kang-Kuen Ni Journal reference: Phys. Chem. Chem. Phys., 2020,22, 4861-4874 [pdf] DOI: 10.1039/C9CP07015J
-
Ruppeiner geometry, phase transitions, and the microstructure of charged AdS black holes -
Abstract
- Originally considered for van der Waals fluids and charged black holes [Phys. Rev. Lett. 123, 071103 (2019)], we extend and generalize our approach to higher-dimensional charged AdS black holes. Beginning with thermodynamic fluctuations, we construct the line element of the Ruppeiner geometry and obtain a universal formula for the scalar curvature $R$. We first review the thermodynamics of a van der Waals fluid and calculate the coexistence and spinodal curves. From this we are able to clearly display the phase diagram. Notwithstanding the invalidity of the equation of state in the coexistence phase regions, we find that the scalar curvature is always negative for the van der Waals fluid, indicating that attractive interactions dominate amongst the fluid microstructures. Along the coexistence curve, the scalar curvature $R$ decreases with temperature, and goes to negative infinity at a critical temperature. We then numerically study the critical phenomena associated with the scalar curvature. We next consider four-dimensional charged AdS black holes. Vanishing of the heat capacity at constant volume yields a divergent scalar curvature. In order to extract the corresponding information, we define a new scalar curvature that has behaviour similar to that of a van der Waals fluid. We analytically confirm that at the critical point of the small/large black hole phase transition, the scalar curvature has a critical exponent 2, and $R(1-\tilde{T})^{2}C_{v}=1/8$, the same as that of a van der Waals fluid. However we also find that the scalar curvature can be positive for the small charged AdS black hole, implying that repulsive interactions dominate among the black hole microstructures. We then generalize our study to higher-dimensional charged AdS black holes.
Shao-Wen Wei, Yu-Xiao Liu, Robert B. Mann Journal reference: Phys. Rev. D 100, 124033 (2019) [pdf] DOI: 10.1103/PhysRevD.100.124033
-
Photon sphere and reentrant phase transition of charged Born-Infeld-AdS black holes -
Abstract
- In this paper, we extend the study of the relationship between the photon sphere and the thermodynamic phase transition, especially the reentrant phase transition, to this black hole background. According to the number of the thermodynamic critical points, the black hole systems are divided into four cases with different values of Born-Infeld parameter b, where the black hole systems can have no phase transition, reentrant phase transition, or Van der Waals-like phase transition. For these different cases, we obtain the corresponding phase structures in pressure-temperature diagram and temperature-specific volume diagram. The tiny differences between these cases are clearly displayed. On the other hand, the radius rps and the minimal impact parameter ups of the photon sphere are calculated via the effective potential of the radial motion of photons. For different cases, rps and ups are found to have different behaviors. In particular, with the increase of rps or ups, the temperature possesses a decrease-increase-decrease-increase behavior for fixed pressure if there exists the reentrant phase transition. While for fixed temperature, the pressure will show an increase-decrease-increase-decrease behavior instead. These behaviors are quite different from that of the Van der Waals-like phase transition. Near the critical point, the changes of rps and ups among the black hole phase transition confirm an universal critical exponent 12. Therefore, all the results indicate that, for the charged Born-Infeld-AdS black holes, not only the Van der Waals-like phase transition, but also the reentrant phase transition can be reflected through the photon sphere.
Yu-Meng Xu, Hui-Min Wang, Yu-Xiao Liu, Shao-Wen Wei Journal reference: Phys. Rev. D 100, 104044 (2019) [pdf] DOI: 10.1103/PhysRevD.100.104044
-
Quantum Fourier Transform in Oscillating Modes -
Abstract
- Quantum Fourier transform (QFT) is a key ingredient of many quantum algorithms. In typical applications such as phase estimation, a considerable number of ancilla qubits and gates are used to form a Hilbert space large enough for high-precision results. Qubit recycling reduces the number of ancilla qubits to one, but it is only applicable to semi-classical QFT and requires repeated measurements and feedforward within the coherence time of the qubits. In this work, we explore a novel approach based on resonators that forms a high-dimensional Hilbert space for the realization of QFT. By employing the perfect state-transfer method, we map an unknown multi-qubit state to a single resonator, and obtain the QFT state in the second oscillator through cross-Kerr interaction and projective measurement. A quantitive analysis shows that our method allows for high-dimensional and fully-quantum QFT employing the state-of-the-art superconducting quantum circuits. This paves the way for implementing various QFT related quantum algorithms.
Qi-Ming Chen, Frank Deppe, Re-Bing Wu, Luyan Sun, Yu-xi Liu, Yuki Nojiri, Stefan Pogorzalek, Michael Renger, Matti Partanen, Kirill G. Fedorov, Achim Marx, Rudolf Gross [pdf]
-
A Bridge from Euclidean Nonperturbative approach to Minkowskian
Distribution Functions -
Abstract
- We give out a simple way to connect the parton distribution functions defined in Minkowskian space and the nonperturbative QCD methods grounded in Euclidean space (e.g., lattice QCD(LQCD), Dyson-Schwinger (DS) equations, functional renormalization group (FRG) approach) in this work. We combine the MIT bag model with the DS equation approach to calculate the longitudinal distribution function, transverse distribution function and scalar distribution function in a proton at renormalization point $\mu = 2\,\text{GeV}$. We look then insight into the dressed effects on the axial, tensor and scalar charges in a nucleon to some extent. This method can be regard as a new bridge between the Euclidean non-perturbative approaches and the Minkowskian space physics.
Langtian Liu, Lei Chang, Yu-xin Liu [pdf]
-
Direct observation of bimolecular reactions of ultracold KRb molecules -
Abstract
- Femtochemistry techniques have been instrumental in accessing the short time scales necessary to probe transient intermediates in chemical reactions. Here we take the contrasting approach of prolonging the lifetime of an intermediate by preparing reactant molecules in their lowest ro-vibronic quantum state at ultralow temperatures, thereby drastically reducing the number of exit channels accessible upon their mutual collision. Using ionization spectroscopy and velocity-map imaging of a trapped gas of potassium-rubidium molecules at a temperature of 500~nK, we directly observe reactants, intermediates, and products of the reaction $^{40}$K$^{87}$Rb + $^{40}$K$^{87}$Rb $\rightarrow$ K$_2$Rb$^*_2$ $\rightarrow$ K$_2$ + Rb$_2$. Beyond observation of a long-lived energy-rich intermediate complex, this technique opens the door to further studies of quantum-state resolved reaction dynamics in the ultracold regime.
Ming-Guang Hu, Yu Liu, David D. Grimes, Yen-Wei Lin, Andrei H. Gheorghe, Romain Vexiau, Nadia Bouloufa-Maafa, Olivier Dulieu, Till Rosenband, Kang-Kuen Ni Journal reference: Science 366, 1111-1115 (2019) [pdf] DOI: 10.1126/science.aay9531
-
Optimization of heterogeneous ternary Li3PO4-Li3BO3-Li2SO4 mixture for
Li-ion conductivity by machine learning -
Abstract
- Mixing heterogeneous Li-ion conductive materials is one of potential ways to enhance the Li-ion conductivity more than that of the parent materials. However, the development of the mixtures had not exhibited significant progress because it is a formidable task to cover the vast possible composition of the parent materials using traditional ways. Here, we introduce a fashion based on machine learning to optimize the composition ratio of ternary Li3PO4-Li3BO3-Li2SO4 mixture for its Li-ion conductivity. According to our results, the optimum composition of the ternary mixture system is 25:14:61 (Li3PO4: Li3BO3: Li2SO4 in mol%), whose Li-ion conductivity is measured as 4.9 x 10E-4 S/cm at 300 {\deg}C. Our X-ray structure analysis indicates that Li-ion conductivity in the mixing systems is enhanced by virtue of the coexistence of two or more phases. Although the mechanism enhancing Li-ion conductivity is not simple, our results demonstrate the effectiveness of machine learning for the development of materials.
Kenji Homma, Yu Liu, Masato Sumita, Ryo Tamura, Naoki Fushimi, Junichi Iwata, Koji Tsuda, Chioko Kaneta [pdf]
-
Magnetic anisotropy and entropy change in trigonal
-
Abstract
- We present a comprehensive investigation on anisotropic magnetic and magnetocaloric properties of the quasi-two-dimensional weak itinerant ferromagnet trigonal Cr$_{0.62}$Te single crystals. Magnetic-anisotropy-induced satellite transition $T^*$ is observed at low fields applied parallel to the $ab$ plane below $T_c$. The $T^*$ is featured by an anomalous magnetization downturn, similar to that in structurally related CrI$_3$, and shows a monotonous shift towards lower temperature with increasing field. Magnetocrystalline anisotropy is also reflected in magnetic entropy change $\Delta S_M(T,H)$ and relative cooling power RCP. Given the high $T_c$, Cr$_{0.62}$Te crystals are materials of interest for nanofabrication in basic science and applied technology.
Yu Liu, Milinda Abeykoon, Eli Stavitski, Klaus Attenkofer, C. Petrovic Journal reference: Physical Review B 100, 245114 (2019) [pdf] DOI: 10.1103/PhysRevB.100.245114
-
Local electric field induced spin photocurrent in ReS2 -
Abstract
- Circular polarized photocurrent is observed near the electrodes on a few-layer ReS2sample at room temperature. For both electrodes, the spatial distribution of the circular polarized photocurrent shows a feature of two wings, with one positive and the other negative. We suggest that this phenomenon arises from the inverse spin Hall effect due to local electric field near the electrode. Bias voltage that modulates this field further controls the sign and magnitude of the inverse spin Hall effect photocurrent. Our research shows that electric field near electrodes has a significant impact on spin transmission operation, hence it could be taken into account for manufacturing spintronic devices in future.
Yang Zhang, Yu Wang, Yu Liu, Xiao-Lin Zeng, Jing Wu, Jin ling Yu, Tian-Jun Cao, Shi-Jun Liang, Yong-Hai Chen [pdf]
-
Motion deviation of test body induced by spin and cosmological constant in extreme mass ratio inspiral binary system -
Abstract
- The future space-borne detectors will provide the possibility to detect gravitational waves emitted from extreme mass ratio inspirals of stellar-mass compact objects into supermassive black holes. It is natural to expect that the spin of the compact object and cosmological constant will affect the orbit of the inspiral process and hence lead to the considerable phase shift of the corresponding gravitational waves. In this paper, we investigate the motion of a spinning test particle in the spinning black hole background with a cosmological constant and give the order of motion deviation induced by the particle's spin and the cosmological constant by considering the corresponding innermost stable circular orbit. By taking the neutron star or kerr black hole as the small body, the deviations of the innermost stable circular orbit parameters induced by the particle's spin and cosmological constant are given. Our results show that the deviation induced by particle's spin is much larger than that induced by cosmological constant when the test particle locates not very far away from the black hole, the accumulation of phase shift during the inspiral from the cosmological constant can be ignored when compared to the one induced by the particle's spin. However when the test particle locates very far away from the black hole, the impact from the cosmological constant will increase dramatically. Therefore the accumulation of phase shift for the whole process of inspiral induced by the cosmological constant and the particle's spin should be handled with caution.
Yu-Peng Zhang, Shao-Wen Wei, Pau Amaro-Seoane, Jie Yang, Yu-Xiao Liu Journal reference: Eur.Phys.J. C79 (2019) 856 [pdf] DOI: 10.1140/epjc/s10052-019-7334-y
-
Topological Magnetic-Spin Textures in Two-Dimensional van der Waals Cr
-
Abstract
- Two-dimensional (2D) van der Waals (vdW) materials show a range of profound physical properties that can be tailored through their incorporation in heterostructures and manipulated with external forces. The recent discovery of long-range ferromagnetic order down to atomic layers provides an additional degree of freedom in engineering 2D materials and their heterostructure devices for spintronics, valleytronics and magnetic tunnel junction switches. Here, using direct imaging by cryo-Lorentz transmission electron microscopy we show that topologically nontrivial magnetic-spin states, skyrmionic bubbles, can be realized in exfoliated insulating 2D vdW Cr2Ge2Te6. Due to the competition between dipolar interactions and uniaxial magnetic anisotropy, hexagonally-packed nanoscale bubble lattices emerge by field cooling with magnetic field applied along the out-of-plane direction. Despite a range of topological spin textures in stripe domains arising due to pair formation and annihilation of Bloch lines, bubble lattices with single chirality are prevalent. Our observation of topologically-nontrivial homochiral skyrmionic bubbles in exfoliated vdW materials provides a new avenue for novel quantum states in atomically-thin insulators for magneto-electronic and quantum devices.
Myung-Geun Han, Joseph A. Garlow, Yu Liu, Huiqin Zhang, Jun Li, Donald DiMarzio, Mark Knight, Cedomir Petrovic, Deep Jariwala, Yimei Zhu Journal reference: Nano Letters, 2019 [pdf] DOI: 10.1021/acs.nanolett.9b02849
-
Excited states of holographic superconductors with backreaction -
Abstract
- In this paper we investigate the model of the anti-de Sitter gravity coupled to a Maxwell field and a free, complex scalar field, and construct a fully back-reacted holographic model of superconductor with excited states. With the fixed charge $q$, there exist a series of excited states of holographic superconductor with the corresponding critical chemical potentials. The condensates as functions of the temperature for the two operators $\mathcal{O}_1$ and $\mathcal{O}_2$ of excited states are also studied. For the optical conductivity in the excited states, we find that there exist the additional peaks in the imaginary and real parts of the conductivity. Moreover, the number of peaks corresponding to $n$-th excited state is equal to $n$.
Yong-Qiang Wang, Hong-Bo Li, Yu-Xiao Liu, Yin Zhong [pdf]
-
A game method for improving the interpretability of convolution neural
network -
Abstract
- Real artificial intelligence always has been focused on by many machine learning researchers, especially in the area of deep learning. However deep neural network is hard to be understood and explained, and sometimes, even metaphysics. The reason is, we believe that: the network is essentially a perceptual model. Therefore, we believe that in order to complete complex intelligent activities from simple perception, it is necessary to con-struct another interpretable logical network to form accurate and reasonable responses and explanations to external things. Researchers like Bolei Zhou and Quanshi Zhang have found many explanatory rules for deep feature extraction aimed at the feature extraction stage of convolution neural network. However, although researchers like Marco Gori have also made great efforts to improve the interpretability of the fully connected layers of the network, the problem is also very difficult. This paper firstly analyzes its reason. Then a method of constructing logical network based on the fully connected layers and extracting logical relation between input and output of the layers is proposed. The game process between perceptual learning and logical abstract cognitive learning is implemented to improve the interpretable performance of deep learning process and deep learning model. The benefits of our approach are illustrated on benchmark data sets and in real-world experiments.
Jinwei Zhao, Qizhou Wang, Fuqiang Zhang, Wanli Qiu, Yufei Wang, Yu Liu, Guo Xie, Weigang Ma, Bin Wang, Xinhong Hei [pdf]
-
Phase-controlled single-photon nonreciprocal transmission in a one-dimensional waveguide -
Abstract
- We study the controllable single-photon scattering via a one-dimensional waveguide which is coupled to a two-level emitter and a single-mode cavity simultaneously. The emitter and the cavity are also coupled to each other and form a three-level system with cyclic transitions within the zero- and single-excitation subspaces. As a result, the phase of emitter-cavity coupling strength serves as a sensitive control parameter. When the emitter and cavity locate at the same point of the waveguide, we demonstrate the Rabi splitting and quasidark-state--induced perfect transmission for the incident photons. More interestingly, when they locate at different points of the waveguide, a controllable nonreciprocal transmission can be realized and the non-reciprocity is robust to the weak coupling between the system and environment. Furthermore, we demonstrate that our theoretical model is experimentally feasible with currently available technologies.
Zhihai Wang, Lei Du, Yong Li, Yu-xi Liu Journal reference: Phys. Rev. A 100, 053809 (2019) [pdf] DOI: 10.1103/PhysRevA.100.053809
-
Multilayered Kelvin–Helmholtz Instability in the Solar Corona -
Abstract
- The Kelvin-Helmholtz (KH) instability is commonly found in many astrophysical, laboratory, and space plasmas. It could mix plasma components of different properties and convert dynamic fluid energy from large scale structure to smaller ones. In this study, we combined the ground-based New Vacuum Solar Telescope (NVST) and the Solar Dynamic Observatories (SDO) / Atmospheric Imaging Assembly (AIA) to observe the plasma dynamics associated with active region 12673 on 09 September 2017. In this multi-temperature view, we identified three adjacent layers of plasma flowing at different speeds, and detected KH instabilities at their interfaces. We could unambiguously track a typical KH vortex and measure its motion. We found that the speed of this vortex suddenly tripled at a certain stage. This acceleration was synchronized with the enhancements in emission measure and average intensity of the 193 \AA{} data. We interpret this as evidence that KH instability triggers plasma heating. The intriguing feature in this event is that the KH instability observed in the NVST channel was nearly complementary to that in the AIA 193 \AA{}. Such a multi-thermal energy exchange process is easily overlooked in previous studies, as the cold plasma component is usually not visible in the extreme ultraviolet channels that are only sensitive to high temperature plasma emissions. Our finding indicates that embedded cold layers could interact with hot plasma as invisible matters. We speculate that this process could occur at a variety of length scales and could contribute to plasma heating.
Ding Yuan, Yuandeng Shen, Yu Liu, Xueshang Feng, Rony Keppens [pdf] DOI: 10.3847/2041-8213/ab4bcd 1910.05710v1 [pdf]
-
A Coding-free Software Framework of Developing Web Data Management
Systems -
Abstract
- More and more enterprises recently intend to deploy data management systems in the cloud. Due to the professionalism of software development, it has still been difficult for non-programmers to develop this kind of systems, even a small one. However, the development of SaaS brings forth the more feasibility of coding-free software development than before. Based on the SaaS architecture, this paper presents a set of theory and method for coding-free construction of a data management system, on which our contributions involve in a practical application platform, a set of construction method and a set of interface on data exchange. By abstracting the common features of data management systems, we design a universal web platform to quickly generate and publish customized system instances. Moreover, we propose a kind of method to develop a data management system using a specific requirements table in spreadsheet. The corresponding platform maps the requirements table into a system instance through parsing the table model and implementing the objective system in the running stage. Finally, we implement the proposed framework and deploy it on web. The empirical result demonstrates the feasibility and availability of the coding-free method in developing web data management systems.
Can Yang, Shiying Pan, Runmin Li, Yu Liu, Lizhang Peng [pdf]
-
Gradient Information Guided Deraining with A Novel Network and
Adversarial Training -
Abstract
- In recent years, deep learning based methods have made significant progress in rain-removing. However, the existing methods usually do not have good generalization ability, which leads to the fact that almost all of existing methods have a satisfied performance on removing a specific type of rain streaks, but may have a relatively poor performance on other types of rain streaks. In this paper, aiming at removing multiple types of rain streaks from single images, we propose a novel deraining framework (GRASPP-GAN), which has better generalization capacity. Specifically, a modified ResNet-18 which extracts the deep features of rainy images and a revised ASPP structure which adapts to the various shapes and sizes of rain streaks are composed together to form the backbone of our deraining network. Taking the more prominent characteristics of rain streaks in the gradient domain into consideration, a gradient loss is introduced to help to supervise our deraining training process, for which, a Sobel convolution layer is built to extract the gradient information flexibly. To further boost the performance, an adversarial learning scheme is employed for the first time to train the proposed network. Extensive experiments on both real-world and synthetic datasets demonstrate that our method outperforms the state-of-the-art deraining methods quantitatively and qualitatively. In addition, without any modifications, our proposed framework also achieves good visual performance on dehazing.
Yinglong Wang, Haokui Zhang, Yu Liu, Qinfeng Shi, Bing Zeng [pdf]
-
Semiconductor–Ferromagnetic Insulator–Superconductor Nanowires: Stray Field and Exchange Field -
Abstract
- Nanowires can serve as flexible substrates for hybrid epitaxial growth on selected facets, allowing for design of heterostructures with complex material combinations and geometries. In this work we report on hybrid epitaxy of semiconductor - ferromagnetic insulator - superconductor (InAs/EuS/Al) nanowire heterostructures. We study the crystal growth and complex epitaxial matching of wurtzite InAs / rock-salt EuS interfaces as well as rock-salt EuS / face-centered cubic Al interfaces. Because of the magnetic anisotropy originating from the nanowire shape, the magnetic structure of the EuS phase are easily tuned into single magnetic domains. This effect efficiently ejects the stray field lines along the nanowires. With tunnel spectroscopy measurements of the density of states, we show the material has a hard induced superconducting gap, and magnetic hysteretic evolution which indicates that the magnetic exchange fields are not negligible. These hybrid nanowires fulfil key material requirements for serving as a platform for spin-based quantum applications, such as scalable topological quantum computing.
Yu Liu, Saulius Vaitiekenas, Sara Marti-Sanchez, Christian Koch, Sean Hart, Zheng Cui, Thomas Kanne, Sabbir A. Khan, Rawa Tanta, Shivendra Upadhyay, Martin Espineira Cachaza, Charles M. Marcus, Jordi Arbiol, Kathryn A. Moler, Peter Krogstrup [pdf] DOI: 10.1021/acs.nanolett.9b04187 1910.03364v1 [pdf]
-
How to improve the interpretability of kernel learning -
Abstract
- In recent years, machine learning researchers have focused on methods to construct flexible and interpretable prediction models. However, an interpretability evaluation, a relationship between generalization performance and an interpretability of the model and a method for improving the interpretability have to be considered. In this paper, a quantitative index of the interpretability is proposed and its rationality is proved, and equilibrium problem between the interpretability and the generalization performance is analyzed. Probability upper bound of the sum of the two performances is analyzed. For traditional supervised kernel machine learning problem, a universal learning framework is put forward to solve the equilibrium problem between the two performances. The condition for global optimal solution based on the framework is deduced. The learning framework is applied to the least-squares support vector machine and is evaluated by some experiments.
Jinwei Zhao, Qizhou Wang, Yufei Wang, Yu Liu, Zhenghao Shi, Xinhong Hei [pdf]
-
Meta Learning with Differentiable Closed-form Solver for Fast Video
Object Segmentation -
Abstract
- This paper tackles the problem of video object segmentation. We are specifically concerned with the task of segmenting all pixels of a target object in all frames, given the annotation mask in the first frame. Even when such annotation is available this remains a challenging problem because of the changing appearance and shape of the object over time. In this paper, we tackle this task by formulating it as a meta-learning problem, where the base learner grasping the semantic scene understanding for a general type of objects, and the meta learner quickly adapting the appearance of the target object with a few examples. Our proposed meta-learning method uses a closed form optimizer, the so-called "ridge regression", which has been shown to be conducive for fast and better training convergence. Moreover, we propose a mechanism, named "block splitting", to further speed up the training process as well as to reduce the number of learning parameters. In comparison with the-state-of-the art methods, our proposed framework achieves significant boost up in processing speed, while having very competitive performance compared to the best performing methods on the widely used datasets.
Yu Liu, Lingqiao Liu, Haokui Zhang, Hamid Rezatofighi, Ian Reid [pdf]
-
Null geodesics, quasinormal modes, and thermodynamic phase transition for charged black holes in asymptotically flat and dS spacetimes -
Abstract
- The numerical study indicates that there exists a relation between the quasinormal modes and the Davies point for a black hole. In this paper, we analytically study this relation for the charged Reissner-Nordstr\"{o}m black holes in asymptotically flat and dS spacetimes. In the eikonal limit, the angular velocity $\Omega$ and the Lyapunov exponent $\lambda$ of the photon sphere, respectively, corresponding to the real and imaginary parts of the quasinormal modes are obtained from the null geodesics. Both in asymptotically flat and dS spacetimes, we observe the spiral-like shapes in the complex quasinormal mode plane. However, the starting point of the shapes do not coincide with the Davies point. Nevertheless, we find a new relation that the Davies point exactly meet the maximum of the temperature $T$ in the $T$-$\Omega$ and $T$-$\lambda$ planes. In higher dimensional asymptotically flat spacetime, even there is no the spiral-like shape, such relation still holds. Therefore, we provide a new relation between the black hole thermodynamics and dynamics. Applying this relation, we can test the black hole thermodynamic property by the quasinormal modes.
Shao-Wen Wei, Yu-Xiao Liu [pdf] DOI: 10.1088/1674-1137/abae54 1909.11911v1 [pdf]
-
Reduced thermodynamics and an exact phase transition of five-dimensional Kerr-AdS black holes with equal spin parameters -
Abstract
- Multi-spinning higher dimensional Kerr-AdS black holes admit the stable small-large black hole phase transition of van der Waals type. In this paper, we study the exact critical phenomena and phase structure in five-dimensional spacetime. First, we examine the thermodynamic laws in the reduced parameter space and find that they are quite different from the conventional thermodynamic laws. Then based on the reduced laws, the phase structure in different parameter spaces is investigated. The stable and metastable black hole phases are clearly displayed. We present a highly accurate fitting formula for the coexistence curve of small and large black hole phases. Using this fitting formula, we examine the critical exponents when the black hole system approaches the critical point along the coexistence curve. Moreover, employing the dimensional analysis and symmetry analysis, we also give a numerical study of the critical point for the unequal spinning black holes. These results are very useful on further understanding the microstructure of the multi-spinning black holes in higher dimensional spacetime.
Shao-Wen Wei, Yu-Xiao Liu Journal reference: Phys. Rev. D 100, 064004 (2019) [pdf] DOI: 10.1103/PhysRevD.100.064004
-
Curvature radius and Kerr black hole shadow -
Abstract
- We consider applications of the curvature radius of a Kerr black hole shadow and propose three new approaches to simultaneously determine the black hole spin and inclination angle of the observer. The first one uses only two symmetric characteristic points, i.e., the top and the bottom points of the shadow, and is the smallest amount of data employed to extract information about spin and inclination angle amongst all current treatments. The second approach shows that only measuring the curvature radius at the characteristic points can also yield the black hole spin and the inclination angle. The observables used in the third approach have large changes to the spin and the inclination angle, which may give us a more accurate way to determine these parameters. Moreover, by modeling the supermassive black hole M87* with a Kerr black hole, we calculate the angular size for these curvature radii of the shadow. Some novel properties are found and analyzed. The results may shine new light on the relationship between the curvature radius and the black hole shadow, and provide several different approaches to test the nature of the black hole through the shadow.
Shao-Wen Wei, Yuan-Chuan Zou, Yu-Xiao Liu, Robert B. Mann Journal reference: JCAP 1908 (2019) 030 [pdf] DOI: 10.1088/1475-7516/2019/08/030
-
Stable halogen 2D materials: the case of iodine and astatine -
Abstract
- Two-dimensional (2D) materials have wide applications towards electronic devices, energy storages, and catalysis, et al. So far, most of the pure element 2D materials are composed of group IIIA,IVA, and VA elements. Beyond the scope, the orbit hybrid configuration becomes a key fact to influence 2D structure stably. Here we show a sp2d3 hybridization in the outmost electrons with O-shell for Iodine and P-shell for astatine element, builds up triangle configuration (beta-type) to form 2D structures beta-iodiene and beta-astatiene. Each atom is connected by pi bonds, and surrounded by 6 atoms. The pi bonds become possible, and band gap approaches zero because of interaction of unpaired single electron to each atom, depending on reducing bond length. By applying compression strain or spin orbit coupling (SOC), the Dirac points or topological nontrivial points can be available in the beta-iodiene and beta-astatiene. Our discovery has paved a new way to construction of 2D materials.
Xinyue Zhang, Yu Liu, Qingsong Huang [pdf] DOI: 10.1088/1361-648X/ab87cf 1909.11643v1 [pdf]
-
Blind Channel Estimation and Data Detection with Unknown Modulation and
Coding Scheme -
Abstract
- This paper investigates a complete blind receiver approach in an unknown multipath fading channel, which has multiple tasks including blind channel estimation, noise power estimation, modulation classification, channel coding recognition, and data detection. Each of these tasks has been sufficiently studied in the literature. However, to the best of our knowledge, this overall problem has not been investigated previously. This paper is the first attempt to address this overall problem jointly. We propose a complete blind receiver approach that jointly estimates the unknown channel state information and noise power, recognizes the unknown modulation and coding scheme, detects the data of interest, and thus named BERD receiver. Another merit of the proposed BERD receiver is that it can be implemented for both a single receiver and multiple receivers, which ensures successful estimation, recognition, and detection for such an extremely difficult problem. In addition, numerical results show the performance of the proposed receiver in three folds: a) the BERD receiver outperforms the linear minimum mean squared error (LMMSE) pilot-based channel estimator by over 3.5 dB at the MSE of 0.01; b) the correct modulation/coding recognition performance of the BERD receiver is within 0.3 dB as close to the recognition benchmark when the perfect channel state information (CSI) is available; c) the BERD receiver is within 0.5 dB at the bit error rate of 0.001 compared to the benchmark when the modulation, the channel coding, and the CSI are perfectly known. Finally, the BERD receiver finds many applications in both civilian and military scenarios, such as the interference cancelation in spectrum sharing, real-time signal interception, and processing in electronic warfare operations, automatic recognition of a detect signal in software-defined radio.
Yu Liu, Fanggang Wang [pdf]
-
Fast Low-rank Metric Learning for Large-scale and High-dimensional Data -
Abstract
- Low-rank metric learning aims to learn better discrimination of data subject to low-rank constraints. It keeps the intrinsic low-rank structure of datasets and reduces the time cost and memory usage in metric learning. However, it is still a challenge for current methods to handle datasets with both high dimensions and large numbers of samples. To address this issue, we present a novel fast low-rank metric learning (FLRML) method.FLRML casts the low-rank metric learning problem into an unconstrained optimization on the Stiefel manifold, which can be efficiently solved by searching along the descent curves of the manifold.FLRML significantly reduces the complexity and memory usage in optimization, which makes the method scalable to both high dimensions and large numbers of samples.Furthermore, we introduce a mini-batch version of FLRML to make the method scalable to larger datasets which are hard to be loaded and decomposed in limited memory. The outperforming experimental results show that our method is with high accuracy and much faster than the state-of-the-art methods under several benchmarks with large numbers of high-dimensional data. Code has been made available at https://github.com/highan911/FLRML
Han Liu, Zhizhong Han, Yu-Shen Liu, Ming Gu [pdf]
-
G4.8+6.2, a possible kilonova remnant? -
Abstract
- Kilonova explosions typically release $\sim 10^{50-51}$ erg in kinetic energy, which is sufficient to constitute a kilonova remnant (KNR); however, it has not yet been confirmed. In this work, we investigate the probable association between G4.8+6.2 and the guest star of AD 1163, which is recorded by the Korea ancient astronomers. Although the evidence available is insufficient to draw a definite conclusion, it is at least theoretically self-consistent that the guest star of AD 1163 was a historical kilonova associated with G4.8+6.2, considering the possible short visible timescale of AD 1163, the relatively high Galactic latitude of G4.8+6.2, and that G4.8+6.2 is spatially coincident with the guest star of AD 1163. Further observation of G4.8+6.2 is needed to test our hypothesis. If our interpretation is correct, our results indicate that young KNRs should have a large diameter and low surface brightness, unlike other young supernova remnants.
Yu Liu, Yuan-Chuan Zou, Bing Jiang, He Gao, Shuai-Bing Ma, Bin Liao [pdf] DOI: 10.1093/mnrasl/slz141 1909.05714v1 [pdf]
-
Boosting Throughput and Efficiency of Hardware Spiking Neural
Accelerators using Time Compression Supporting Multiple Spike Codes -
Abstract
- Spiking neural networks (SNNs) are the third generation of neural networks and can explore both rate and temporal coding for energy-efficient event-driven computation. However, the decision accuracy of existing SNN designs is contingent upon processing a large number of spikes over a long period. Nevertheless, the switching power of SNN hardware accelerators is proportional to the number of spikes processed while the length of spike trains limits throughput and static power efficiency. This paper presents the first study on developing temporal compression to significantly boost throughput and reduce energy dissipation of digital hardware SNN accelerators while being applicable to multiple spike codes. The proposed compression architectures consist of low-cost input spike compression units, novel input-and-output-weighted spiking neurons, and reconfigurable time constant scaling to support large and flexible time compression ratios. Our compression architectures can be transparently applied to any given pre-designed SNNs employing either rate or temporal codes while incurring minimal modification of the neural models, learning algorithms, and hardware design. Using spiking speech and image recognition datasets, we demonstrate the feasibility of supporting large time compression ratios of up to 16x, delivering up to 15.93x, 13.88x, and 86.21x improvements in throughput, energy dissipation, the tradeoffs between hardware area, runtime, energy, and classification accuracy, respectively based on different spike codes on a Xilinx Zynq-7000 FPGA. These results are achieved while incurring little extra hardware overhead.
Changqing Xu, Wenrui Zhang, Yu Liu, Peng Li [pdf]
-
Tensor stability in Born-Infeld determinantal gravity -
Abstract
- We consider the transverse-traceless tensor perturbation of a spatial flat homogeneous and isotropic spacetime in Born-Infeld determinantal gravity, and investigate the evolution of the tensor mode for two solutions in the early universe. For the first solution where the initial singularity is replaced by a regular geometric de Sitter inflation of infinite duration, the evolution of the tensor mode is stable for the parameter spaces $\alpha<-1$, $\omega\geq-1/3$ and $\alpha=-1$, $\omega>0$. For the second solution where the initial singularity is replaced by a primordial brusque bounce, which suffers a sudden singularity at the bouncing point, the evolution of the tensor mode is stable for all regions of the parameter space. Our calculation suggests that the tensor evolution can hold stability in large parameter spaces, which is a remarkable property of Born-Infeld determinantal gravity. We also constrain the theoretical parameter $|\lambda|\geq 10^{-38} \text{m}^{-2}$ by resorting to the current bound on the speed of the gravitational waves.
Ke Yang, Yu-Peng Zhang, Yu-Xiao Liu Journal reference: Eur. Phys. J. C (2019) 79: 736 [pdf] DOI: 10.1140/epjc/s10052-019-7253-y
-
Towards Flops-constrained Face Recognition -
Abstract
- Large scale face recognition is challenging especially when the computational budget is limited. Given a \textit{flops} upper bound, the key is to find the optimal neural network architecture and optimization method. In this article, we briefly introduce the solutions of team 'trojans' for the ICCV19 - Lightweight Face Recognition Challenge~\cite{lfr}. The challenge requires each submission to be one single model with the computational budget no higher than 30 GFlops. We introduce a searched network architecture `Efficient PolyFace' based on the Flops constraint, a novel loss function `ArcNegFace', a novel frame aggregation method `QAN++', together with a bag of useful tricks in our implementation (augmentations, regular face, label smoothing, anchor finetuning, etc.). Our basic model, `Efficient PolyFace', takes 28.25 Gflops for the `deepglint-large' image-based track, and the `PolyFace+QAN++' solution takes 24.12 Gflops for the `iQiyi-large' video-based track. These two solutions achieve 94.198\% @ 1e-8 and 72.981\% @ 1e-4 in the two tracks respectively, which are the state-of-the-art results.
Yu Liu, Guanglu Song, Manyuan Zhang, Jihao Liu, Yucong Zhou, Junjie Yan [pdf]
-
Point2SpatialCapsule: Aggregating Features and Spatial Relationships of Local Regions on Point Clouds Using Spatial-Aware Capsules -
Abstract
- Learning discriminative shape representation directly on point clouds is still challenging in 3D shape analysis and understanding. Recent studies usually involve three steps: first splitting a point cloud into some local regions, then extracting corresponding feature of each local region, and finally aggregating all individual local region features into a global feature as shape representation using simple max pooling. However, such pooling-based feature aggregation methods do not adequately take the spatial relationships between local regions into account, which greatly limits the ability to learn discriminative shape representation. To address this issue, we propose a novel deep learning network, named Point2SpatialCapsule, for aggregating features and spatial relationships of local regions on point clouds, which aims to learn more discriminative shape representation. Compared with traditional max-pooling based feature aggregation networks, Point2SpatialCapsule can explicitly learn not only geometric features of local regions but also spatial relationships among them. It consists of two modules. To resolve the disorder problem of local regions, the first module, named geometric feature aggregation, is designed to aggregate the local region features into the learnable cluster centers, which explicitly encodes the spatial locations from the original 3D space. The second module, named spatial relationship aggregation, is proposed for further aggregating clustered features and the spatial relationships among them in the feature space using the spatial-aware capsules developed in this paper. Compared to the previous capsule network based methods, the feature routing on the spatial-aware capsules can learn more discriminative spatial relationships among local regions for point clouds, which establishes a direct mapping between log priors and the spatial locations through feature clusters.
Xin Wen, Zhizhong Han, Xinhai Liu, Yu-Shen Liu [pdf] DOI: 10.1109/TIP.2020.3019925 1908.11026v1 [pdf]
-
Thickness-dependent magnetic order in CrI3 single crystals -
Abstract
- Two-dimensional (2D) materials with intrinsic ferromagnetism provide unique opportunity to engineer new functionalities in nano-spintronics. One such material is CrI$_3$, showing long-range magnetic order in monolayer with the Curie temperature ($T_c$) of 45 K. Here we study detailed evolution of magnetic transition and magnetic critical properties in response to systematic reduction in crystal thickness down to 50 nm. Bulk $T_c$ of 61 K is gradually suppressed to 57 K, however, the satellite transition at $T^*$ = 45 K is observed layer-independent at fixed magnetic field of 1 kOe. The origin of $T^*$ is proposed to be a crossover from pinning to depinning of magnetic domain walls. The reduction of thickness facilitates a field-driven metamagnetic transition around 20 kOe with out-of-plane field, in contrast to the continuous changes with in-plane field. The critical analysis around $T_c$ elucidates the mean-field type interactions in microscale-thick CrI$_3$.
Yu Liu, Lijun Wu, Xiao Tong, Jun Li, Jing Tao, Yimei Zhu, C. Petrovic Journal reference: Scientific Reports 9, 13599 (2019) [pdf] DOI: 10.1038/s41598-019-50000-x
-
Anisotropic magnetocaloric effect in Fe3−xGeTe2 -
Abstract
- We present a comprehensive study on anisotropic magnetocaloric porperties of the van der Waals weak-itinerant ferromagnet Fe$_{3-x}$GeTe$_2$ that features gate-tunable room-temperature ferromagnetism in few-layer device. Intrinsic magnetocrystalline anisotropy is observed to be temperature-dependent and most likely favors the long-range magnetic order in thin Fe$_{3-x}$GeTe$_2$ crsytal. The magnetic entropy change $-\Delta S_M$ also reveals an anisotropic characteristic between $H // ab$ and $H // c$, which could be well scaled into a universal curve. The peak value $-\Delta S_M^{max}$ of 1.20 J kg$^{-1}$ K$^{-1}$ and the corresponding adiabatic temperature change $\Delta T_{ad}$ of 0.66 K are deduced from heat capacity with out-of-plane field change of 5 T. By fitting of the field-dependent parameters of $-\Delta S_M^{max}$ and the relative cooling power RCP, it gives $-\Delta S_M^{max} \propto H^n$ with $n = 0.603(6)$ and $RCP \propto H^m$ with $m = 1.20(1)$ when $H // c$. Given the high and tunable $T_c$, Fe$_{3-x}$GeTe$_2$ crystals are of interest for fabricating the heterostructure-based spintronics device.
Yu Liu, Jun Li, Jing Tao, Yimei Zhu, C. Petrovic Journal reference: Scientific Reports 9, 13233 (2019) [pdf] DOI: 10.1038/s41598-019-49654-4
-
Nonreciprocal transition between two nondegenerate energy levels -
Abstract
- Stimulated emission and absorption are two fundamental processes of light-matter interaction, and the coefficients of the two processes should be equal in general. However, we will describe a generic method to realize significant difference between the stimulated emission and absorption coefficients of two nondegenerate energy levels, which we refer to as nonreciprocal transition. As a simple implementation, a cyclic three-level atom system, comprising two nondegenerate energy levels and one auxiliary energy level, is employed to show nonreciprocal transition via a combination of synthetic magnetism and reservoir engineering. Moreover, a single-photon nonreciprocal transporter is proposed using two one dimensional semi-infinite coupled-resonator waveguides connected by an atom with nonreciprocal transition effect. Our work opens up a route to design atom-mediated nonreciprocal devices in a wide range of physical systems.
Xun-Wei Xu, Yan-Jun Zhao, Hui Wang, Ai-Xi Chen, Yu-xi Liu [pdf]
-
Fractional heat semigroups on metric measure spaces with finite
densities and applications to fractional dissipative equations -
Abstract
- Let $(\mathbb M, d,\mu)$ be a metric measure space with upper and lower densities: $$ \begin{cases} |||\mu|||_{\beta}:=\sup_{(x,r)\in \mathbb M\times(0,\infty)} \mu(B(x,r))r^{-\beta}<\infty;\\ \mathbb \mu(b(x,r))r^{-\beta^{\star}} m\times(0,\infty)} |||\mu|||_{\beta^{\star}}:="\inf_{(x,r)\in">0, \end{cases} $$ where $\beta, \beta^{\star}$ are two positive constants which are less than or equal to the Hausdorff dimension of $\mathbb M$. Assume that $p_t(\cdot,\cdot)$ is a heat kernel on $\mathbb M$ satisfying Gaussian upper estimates and $\mathcal L$ is the generator of the semigroup associated with $p_t(\cdot,\cdot)$. In this paper, via a method independent of Fourier transform, we establish the decay estimates for the kernels of the fractional heat semigroup $\{e^{-t \mathcal{L}^{\alpha}}\}_{t>0}$ and the operators $\{{\mathcal{L}}^{\theta/2} e^{-t \mathcal{L}^{\alpha}}\}_{t>0}$, respectively. By these estimates, we obtain the regularity for the Cauchy problem of the fractional dissipative equation associated with $\mathcal L$ on $(\mathbb M, d,\mu)$. Moreover, based on the geometric-measure-theoretic analysis of a new $L^p$-type capacity defined in $\mathbb{M}\times(0,\infty)$, we also characterize a nonnegative Randon measure $\nu$ on $\mathbb M\times(0,\infty)$ such that $R_\alpha L^p(\mathbb M)\subseteq L^q(\mathbb M\times(0,\infty),\nu)$ under $(\alpha,p,q)\in (0,1)\times(1,\infty)\times(1,\infty)$, where $u=R_\alpha f$ is the weak solution of the fractional diffusion equation $(\partial_t+ \mathcal{L}^\alpha)u(t,x)=0$ in $\mathbb M\times(0,\infty)$ subject to $u(0,x)=f(x)$ in $\mathbb M$.
Jizheng Huang, Pengtao Li, Yu Liu, Shaoguang Shi [pdf]
-
Capacity & Perimeter from $α$-Hermite Bounded Variation -
Abstract
- Let $\mathcal{H}_{\alpha}=\Delta-(\alpha-1)|x|^{\alpha}$ be an $[1,\infty)\ni\alpha$-Hermite operator for the hydrogen atom located at the origin in $\mathbb R^d$. In this paper, we are motivated by the classical case $\alpha=1$ to investigate the space of functions with $\alpha$-{\it Hermite Bounded Variation} and its functional capacity and geometrical perimeter.
Jizheng Huang, Pengtao Li, Yu Liu [pdf]
-
In defense of OSVOS -
Abstract
- As a milestone for video object segmentation, one-shot video object segmentation (OSVOS) has achieved a large margin compared to the conventional optical-flow based methods regarding to the segmentation accuracy. Its excellent performance mainly benefit from the three-step training mechanism, that are: (1) acquiring object features on the base dataset (i.e. ImageNet), (2) training the parent network on the training set of the target dataset (i.e. DAVIS-2016) to be capable of differentiating the object of interest from the background. (3) online fine-tuning the interested object on the first frame of the target test set to overfit its appearance, then the model can be utilized to segment the same object in the rest frames of that video. In this paper, we argue that for the step (2), OSVOS has the limitation to 'overemphasize' the generic semantic object information while 'dilute' the instance cues of the object(s), which largely block the whole training process. Through adding a common module, video loss, which we formulate with various forms of constraints (including weighted BCE loss, high-dimensional triplet loss, as well as a novel mixed instance-aware video loss), to train the parent network in the step (2), the network is then better prepared for the step (3), i.e. online fine-tuning on the target instance. Through extensive experiments using different network structures as the backbone, we show that the proposed video loss module can improve the segmentation performance significantly, compared to that of OSVOS. Meanwhile, since video loss is a common module, it can be generalized to other fine-tuning based methods and similar vision tasks such as depth estimation and saliency detection.
Yu Liu, Yutong Dai, Anh-Dzung Doan, Lingqiao Liu, Ian Reid [pdf]
-
Coherent Epitaxial Semiconductor-Ferromagnetic Insulator InAs/EuS
Interfaces: Band Alignment and Magnetic Structure -
Abstract
- Hybrid semiconductor-ferromagnetic insulator heterostructures are interesting due to their tunable electronic transport, self-sustained stray field and local proximitized magnetic exchange. In this work, we present lattice matched hybrid epitaxy of semiconductor - ferromagnetic insulator InAs/EuS heterostructures and analyze the atomic-scale structure as well as their electronic and magnetic characteristics. The Fermi level at the InAs/EuS interface is found to be close to the InAs conduction band and in the bandgap of EuS, thus preserving the semiconducting properties. Both neutron and X-ray reflectivity measurements show that the ferromagnetic component is mainly localized in the EuS thin film with a suppression of the Eu moment in the EuS layer nearest the InAs. Induced moments in the adjacent InAs layers were not detected although our ab initio calculations indicate a small exchange field in the InAs layer. This work presents a step towards realizing high quality semiconductor - ferromagnetic insulator hybrids, which is a critical requirement for development of various quantum and spintronic applications without external magnetic fields.
-
Minimax Estimation of Large Precision Matrices with Bandable Cholesky
Factor -
Abstract
- Last decade witnesses significant methodological and theoretical advances in estimating large precision matrices. In particular, there are scientific applications such as longitudinal data, meteorology and spectroscopy in which the ordering of the variables can be interpreted through a bandable structure on the Cholesky factor of the precision matrix. However, the minimax theory has still been largely unknown, as opposed to the well established minimax results over the corresponding bandable covariance matrices. In this paper, we focus on two commonly used types of parameter spaces, and develop the optimal rates of convergence under both the operator norm and the Frobenius norm. A striking phenomenon is found: two types of parameter spaces are fundamentally different under the operator norm but enjoy the same rate optimality under the Frobenius norm, which is in sharp contrast to the equivalence of corresponding two types of bandable covariance matrices under both norms. This fundamental difference is established by carefully constructing the corresponding minimax lower bounds. Two new estimation procedures are developed: for the operator norm, our optimal procedure is based on a novel local cropping estimator targeting on all principle submatrices of the precision matrix while for the Frobenius norm, our optimal procedure relies on a delicate regression-based thresholding rule. Lepski's method is considered to achieve optimal adaptation. We further establish rate optimality in the nonparanormal model. Numerical studies are carried out to confirm our theoretical findings.
Yu Liu, Zhao Ren [pdf]
-
Charged AdS black hole heat engines -
Abstract
- We study the heat engine by a $d$-dimensional charged anti-de Sitter black hole by making a comparison between the small-large black hole phase transition and the liquid-vapour phase transition of water. With the help of the first law and equal-area law, we obtain an exact formula for the efficiency of a black hole engine modeled with a Rankine cycle with or without a back pressure mechanism. When the low temperature is fixed, both the heat and work decreases with the high temperature $T_{1}$. And the efficiency increases with $T_{1}$, while decreases with the charge $q$. For a Rankine cycle with a back pressure mechanism, we find that both the maximum work and efficiency can be approached at the high temperature $T_{1}$. In the reduced parameter space, it also confirms the similar result. Moreover, we observe that the work and efficiency of the black hole heat engine rapidly increase with the number of spacetime dimensions. Thus higher-dimensional charged anti-de Sitter black hole can act as a more efficient power plant producing the mechanical work, and might be a possible source of the power gamma rays and ultrahigh-energy cosmic rays.
Shao-Wen Wei, Yu-Xiao Liu Journal reference: Nucl. Phys. B 946, 114700 (2019) [pdf] DOI: 10.1016/j.nuclphysb.2019.114700
-
Repulsive Interactions and Universal Properties of Charged Anti–de Sitter Black Hole Microstructures -
Abstract
- The Ruppeiner geometry of thermodynamic fluctuations provides a powerful diagnostic of black hole microstructures. We investigate this for charged AdS black holes and find that while an attractive microstructure interaction dominates for most parameter ranges, a weak repulsive interaction dominates for small black holes of high temperature. This unique property distinguishes the black hole system from that of a Van der Waals fluid, where only attractive microstructure interactions are found. We also find two other novel universal properties for charged black holes. One is that the repulsive interaction is independent of the black hole charge and temperature. The other is that the behavior of the Ruppeiner curvature scalar near criticality is characterized by a dimensionless constant that is identical to that for a Van der Waals fluid, providing us with new insight into black hole microstructures.
Shao-Wen Wei, Yu-Xiao Liu, Robert B. Mann Journal reference: Phys. Rev. Lett. 123, 071103 (2019) [pdf] DOI: 10.1103/PhysRevLett.123.071103
-
Stereoscopic Observations of an Erupting Mini-filament-driven Two-sided-loop Jet and the Applications for Diagnosing a Filament Magnetic Field -
Abstract
- The ubiquitous solar jets or jet-like activities are generally regarded as an important source of energy and mass input to the upper solar atmosphere and the solar wind. However, questions about their triggering and driving mechanisms are not completely understood. By taking advantage of high temporal and high spatial resolution stereoscopic observations taken by the Solar Dynamic Observatory (SDO) and the Solar Terrestrial Relations Observatory (STEREO), we report an intriguing two-sided-loop jet occurred on 2013 June 02, which was dynamically associated with the eruption of a mini-filament below an overlying large filament, and two distinct reconnection processes are identified during the formation stage. The SDO observations reveals that the two-sided-loop jet showed a concave shape with a projection speed of about 80 - 136. From the other view angle, the STEREO ahead observations clearly showed that the trajectory of the two arms of the two-sided-loop were along the cavity magnetic field lines hosting the large filament. Contrary to the well-accepted theoretical model, the present observation sheds new light on our understanding of the formation mechanism of two-sided-loop jets. Moreover, the eruption of the two-sided-loop jet not only supplied mass to the overlying large filament, but also provided a rare opportunity to diagnose the magnetic structure of the overlying large filament via the method of three-dimensional reconstruction.
Yuandeng Shen, Zhining Qu, Ding Yuan, Huadong Chen, Yadan Duan, Chengrui Zhou, Zehao Tang, Jin Huang, Yu Liu [pdf] DOI: 10.3847/1538-4357/ab3a4d 1908.03660v2 [pdf]
-
The analytical description of a doped Mott insulator -
Abstract
- With the hierarchical Green's function approach, we study a doped Mott insulator described with the Hubbard model by analytically solving the equations of motion of an one-particle Green's function and related multiple-point correlation functions, and find that the separation of the spin and charge degrees of freedom of the electrons is an intrinsic character of the doped Mott insulator. For enough of large on-site repulsive Coulomb interaction, we show that the spectral weight of the one-particle Green's function is proportional to the hole doping concentration that is mainly produced by the charge fluctuation of electrons, while the excitation spectrum of the electrons is composed of two parts: one is contributed by the spin fluctuation of the electrons which is proportional to the hole doping concentration, and another one is coming from the coupling between the charge and spin fluctuations of the electrons that takes the maximum at undoping. All of these low energy/temperature physical properties originate from the strong on-site Coulomb interaction. The present results are consistent with the spectroscopy observations of the cuprate superconductors, and the numerical calculations in normal state above pseudogap regime.
Yu-Liang Liu [pdf] DOI: 10.1142/S0217979219503557 1908.04453v1 [pdf]
-
A coupled-channel lattice study of the resonance-like structure
-
Abstract
- In this exploratory study, near-threshold scattering of $D$ and $\bar{D}^*$ meson is investigated using lattice QCD with $N_f=2+1+1$ twisted mass fermion configurations. The calculation is performed within the coupled-channel L\"uscher's finite-size formalism. The study focuses on the channel with $I^G(J^{PC})=1^+(1^{+-})$ where the resonance-like structure $Z_c(3900)$ was discovered. We first identify the most relevant two channels of the problem and the lattice study is performed within the two-channel scattering model. Combined with a two-channel Ross-Shaw theory, scattering parameters are extracted from the energy levels by solving the generalized eigenvalue problem. Our results on the scattering length parameters suggest that, at the particular lattice parameters that we studied, the best fitted parameters do not correspond to a peak behavior in the elastic scattering cross section near the threshold. Furthermore, within the zero-range Ross-Shaw theory, the scenario of a narrow resonance close to the threshold is disfavored beyond $3\sigma$ level.
Ting Chen, Ying Chen, Ming Gong, Chuan Liu, Liuming Liu, Yu-Bin Liu, Zhaofeng Liu, Jian-Ping Ma, Markus Werner, Jian-Bo Zhang Journal reference: Chin.Phys. C43 (2019) no.10, 103103 [pdf] DOI: 10.1088/1674-1137/43/10/103103
-
Exploiting temporal consistency for real-time video depth estimation -
Abstract
- Accuracy of depth estimation from static images has been significantly improved recently, by exploiting hierarchical features from deep convolutional neural networks (CNNs). Compared with static images, vast information exists among video frames and can be exploited to improve the depth estimation performance. In this work, we focus on exploring temporal information from monocular videos for depth estimation. Specifically, we take the advantage of convolutional long short-term memory (CLSTM) and propose a novel spatial-temporal CSLTM (ST-CLSTM) structure. Our ST-CLSTM structure can capture not only the spatial features but also the temporal correlations/consistency among consecutive video frames with negligible increase in computational cost. Additionally, in order to maintain the temporal consistency among the estimated depth frames, we apply the generative adversarial learning scheme and design a temporal consistency loss. The temporal consistency loss is combined with the spatial loss to update the model in an end-to-end fashion. By taking advantage of the temporal information, we build a video depth estimation framework that runs in real-time and generates visually pleasant results. Moreover, our approach is flexible and can be generalized to most existing depth estimation frameworks. Code is available at: https://tinyurl.com/STCLSTM
Haokui Zhang, Chunhua Shen, Ying Li, Yuanzhouhan Cao, Yu Liu, Youliang Yan [pdf]
-
Practical scheme from QCD to phenomena via Dyson-Schwinger equations -
Abstract
- We deliver a new scheme to compute the quark propagator and the quark-gluon interaction vertex through the coupled Dyson-Schwinger equations (DSEs) of QCD. We take the three-gluon vertex into account in our calculations, and implement the gluon propagator and the running coupling function fitted by the solutions of their respective DSEs. We obtain the momentum and current mass dependence of the quark propagator and the quark-gluon vertex, and the chiral quark condensate which agrees with previous results excellently. We also compute the quark-photon vertex within this scheme and give the anomalous chromo- and electro-magnetic moment of quark. The obtained results also agree with previous ones very well. These applications manifest that the new scheme is realistic and then practical for explaining the QCD-related phenomena.
Can Tang, Fei Gao, Yu-xin Liu Journal reference: Phys. Rev. D 100, 056001 (2019) [pdf] DOI: 10.1103/PhysRevD.100.056001
-
A Critical Review on the Electromigration Effect, the Electroplastic Effect, and Perspectives on the Effects of Electric Current Upon Alloy Phase Stability -
Abstract
- The electronic interconnections in the state-of-the-art integrated circuit manufacturing have been scaled down to the micron or sub-micron scale. This results in a dramatic increase in the current density passing through interconnections, which means that the electromigration (EM) effect plays a significant role in the reliability of products. Although thorough studies and reviews of EM effects have been continuously conducted in the past 60 years, some parts of EM theories lack clear elucidation of the electric current-induced non-directional effects, including electric current-induced phase equilibrium changes. This review article is intended to provide a broad picture of electric current-induced lattice stability changes and to summarize the existing literature on EM-related phenomena, EM-related theoretical models, and relevant effects of the electroplastic (EP) effect in order to lead to a better understanding of electric current-induced effects on materials. This article also posits that EM is either part of the EP effect or shares the intrinsic electric current-induced plastic deformation associated with the EP effect. This concept appears to contribute to the missing parts of the EM theories.
Yu-chen Liu, Shih-kang Lin Journal reference: JOM (2019) [pdf] DOI: 10.1007/s11837-019-03661-y
-
Valence transition in topological Kondo insulator -
Abstract
- We investigate the valence transition in three-dimensional topological Kondo insulator through slave-boson analysis of periodic Anderson model. By including the effect of intra-atomic Coulomb correlation $U_{fc}$ between conduction and local electrons, we find a first-order valence transition from Kondo region to mixed valence upon ascending of local level above a critical $U_{fc}$, and this valence transition usually occurs very close to or simultaneously with a topological transition. Near the parameter region of zero-temperature valence transition, rise of temperature can generate a thermal valence transition from mixed valence to Kondo region, accompanied by a first-order topological transition. Remarkably, above a critical $U_{fc}$ which is considerable smaller than that generating paramagnetic valence transition, the original continuous antiferromagnetic transition is shifted to first order one, at which a discontinuous valence shift takes place. Upon increased $U_{fc}$, the paramagnetic valence transition approaches then converges with the first-order antiferromagnetic transition, leaving an significant valence shift on the magnetic boundary. The continuous antiferromagnetic transition, first-order antiferromagnetic transition, paramagnetic valence transition and topological transitions are all summarized in a global phase diagram. Our proposed exotic transition processes can help to understand the thermal valence variation as well as the valence shift around the pressure-induced magnetic transition in topological Kondo insulator candidates and in other heavy-fermion systems.
Jia-Tao Zhuang, Xiao-Jun Zheng, Zhi-Yong Wang, Xing Ming, Huan Li, Yu Liu, Hai-Feng Song [pdf] DOI: 10.1088/1361-648X/ab4625 1908.00913v1 [pdf]
-
L2G Auto-encoder -
Abstract
- Auto-encoder is an important architecture to understand point clouds in an encoding and decoding procedure of self reconstruction. Current auto-encoder mainly focuses on the learning of global structure by global shape reconstruction, while ignoring the learning of local structures. To resolve this issue, we propose Local-to-Global auto-encoder (L2G-AE) to simultaneously learn the local and global structure of point clouds by local to global reconstruction. Specifically, L2G-AE employs an encoder to encode the geometry information of multiple scales in a local region at the same time. In addition, we introduce a novel hierarchical self-attention mechanism to highlight the important points, scales and regions at different levels in the information aggregation of the encoder. Simultaneously, L2G-AE employs a recurrent neural network (RNN) as decoder to reconstruct a sequence of scales in a local region, based on which the global point cloud is incrementally reconstructed. Our outperforming results in shape classification, retrieval and upsampling show that L2G-AE can understand point clouds better than state-of-the-art methods.
Xinhai Liu, Zhizhong Han, Xin Wen, Yu-Shen Liu, Matthias Zwicker [pdf] DOI: 10.1145/3343031.3350960 1908.00720v1 [pdf]
-
Scalable Place Recognition Under Appearance Change for Autonomous
Driving -
Abstract
- A major challenge in place recognition for autonomous driving is to be robust against appearance changes due to short-term (e.g., weather, lighting) and long-term (seasons, vegetation growth, etc.) environmental variations. A promising solution is to continuously accumulate images to maintain an adequate sample of the conditions and incorporate new changes into the place recognition decision. However, this demands a place recognition technique that is scalable on an ever growing dataset. To this end, we propose a novel place recognition technique that can be efficiently retrained and compressed, such that the recognition of new queries can exploit all available data (including recent changes) without suffering from visible growth in computational cost. Underpinning our method is a novel temporal image matching technique based on Hidden Markov Models. Our experiments show that, compared to state-of-the-art techniques, our method has much greater potential for large-scale place recognition for autonomous driving.
Anh-Dzung Doan, Yasir Latif, Tat-Jun Chin, Yu Liu, Thanh-Toan Do, Ian Reid [pdf]
-
ShapeCaptioner: Generative Caption Network for 3D Shapes by Learning a
Mapping from Parts Detected in Multiple Views to Sentences -
Abstract
- 3D shape captioning is a challenging application in 3D shape understanding. Captions from recent multi-view based methods reveal that they cannot capture part-level characteristics of 3D shapes. This leads to a lack of detailed part-level description in captions, which human tend to focus on. To resolve this issue, we propose ShapeCaptioner, a generative caption network, to perform 3D shape captioning from semantic parts detected in multiple views. Our novelty lies in learning the knowledge of part detection in multiple views from 3D shape segmentations and transferring this knowledge to facilitate learning the mapping from 3D shapes to sentences. Specifically, ShapeCaptioner aggregates the parts detected in multiple colored views using our novel part class specific aggregation to represent a 3D shape, and then, employs a sequence to sequence model to generate the caption. Our outperforming results show that ShapeCaptioner can learn 3D shape features with more detailed part characteristics to facilitate better 3D shape captioning than previous work.
Zhizhong Han, Chao Chen, Yu-Shen Liu, Matthias Zwicker [pdf]
-
Matching generalized parton quasidistributions in the RI/MOM scheme -
Abstract
- Within the framework of large momentum effective theory (LaMET), genenaralized parton distributions (GPDs) can be extracted from lattice calculations of quasi-GPDs through a perturbative matching relation, up to power corrections that are suppressed by the hadron momentum. In this paper, we focus on isovector quark GPDs, including the unpolarized, longitudinally and transversely polarized cases, and present the one-loop matching that connects the quasi-GPDs renormalized in a regularization-independent momentum subtraction (RI/MOM) scheme to the GPDs in MS scheme. We find that the matching coefficient is independent of the momentum transfer squared. As a consequence, the matching for the quasi-GPD with zero skewness is the same as that for the quasi-PDF. Our results provide a crucial input for the determination of quark GPDs from lattice QCD using LaMET.
Yu-Sheng Liu, Wei Wang, Ji Xu, Qi-An Zhang, Jian-Hui Zhang, Shuai Zhao, Yong Zhao Journal reference: Phys. Rev. D 100, 034006 (2019) [pdf] DOI: 10.1103/PhysRevD.100.034006
-
Multi-Angle Point Cloud-VAE: Unsupervised Feature Learning for 3D Point
Clouds from Multiple Angles by Joint Self-Reconstruction and Half-to-Half
Prediction -
Abstract
- Unsupervised feature learning for point clouds has been vital for large-scale point cloud understanding. Recent deep learning based methods depend on learning global geometry from self-reconstruction. However, these methods are still suffering from ineffective learning of local geometry, which significantly limits the discriminability of learned features. To resolve this issue, we propose MAP-VAE to enable the learning of global and local geometry by jointly leveraging global and local self-supervision. To enable effective local self-supervision, we introduce multi-angle analysis for point clouds. In a multi-angle scenario, we first split a point cloud into a front half and a back half from each angle, and then, train MAP-VAE to learn to predict a back half sequence from the corresponding front half sequence. MAP-VAE performs this half-to-half prediction using RNN to simultaneously learn each local geometry and the spatial relationship among them. In addition, MAP-VAE also learns global geometry via self-reconstruction, where we employ a variational constraint to facilitate novel shape generation. The outperforming results in four shape analysis tasks show that MAP-VAE can learn more discriminative global or local features than the state-of-the-art methods.
Zhizhong Han, Xiyang Wang, Yu-Shen Liu, Matthias Zwicker [pdf]
-
Thick brane in reduced Horndeski theory -
Abstract
- Horndeski theory is the most general scalar-tensor theory retaining second-order field equations, although the action includes higher-order terms. This is achieved by a special choice of coupling constants. In this paper, we investigate thick brane system in reduced Horndeski theory, especially the effect of the non-minimal derivative coupling on thick brane. First, the equations of motion are presented and a set of analytic background solutions are obtained. Then, to investigate the stability of the background scalar profile, we present a novel canonically normalized method, and show that although the original background scalar field is unstable, the canonical one is stable. The stability of the thick brane under tensor perturbation is also considered. It is shown that the tachyon is absent and the graviton zero mode can be localized on the brane. The localized graviton zero mode recovers the four-dimensional Newtonian potential and the presence of the non-minimal derivative coupling results in a splitting of its wave function. The correction of the massive graviton KK modes to the Newtonian potential is also analyzed briefly.
Qi-Ming Fu, Hao Yu, Li Zhao, Yu-Xiao Liu Journal reference: Phys. Rev. D 100, 124057 (2019) [pdf] DOI: 10.1103/PhysRevD.100.124057
-
Relative rigid objects in extriangulated categories -
Abstract
- In this paper, we study a close relationship between relative cluster tilting theory in extriangulated categories and tau-tilting theory in module categories. Our main results show that relative rigid objects are in bijection with $\tau$-rigid pairs, and also relative maximal rigid objects with support tau-tilting pairs under some assumptions. These results generalize their work by Adachi-Iyama-Reiten, Yang-Zhu and Fu-Geng-Liu. Finally, we introduce mutation of relative maximal rigid objects and show that any basic relative almost maximal rigid object has exactly two non-isomorphic indecomposable complements.
Yu Liu, Panyue Zhou [pdf]
-
Lecture Notes in Computer Science -
Abstract
- Pinterest is a popular Web application that has over 250 million active users. It is a visual discovery engine for finding ideas for recipes, fashion, weddings, home decoration, and much more. In the last year, the company adopted Semantic Web technologies to create a knowledge graph that aims to represent the vast amount of content and users on Pinterest, to help both content recommendation and ads targeting. In this paper, we present the engineering of an OWL ontology---the Pinterest Taxonomy---that forms the core of Pinterest's knowledge graph, the Pinterest Taste Graph. We describe modeling choices and enhancements to WebProt\'eg\'e that we used for the creation of the ontology. In two months, eight Pinterest engineers, without prior experience of OWL and WebProt\'eg\'e, revamped an existing taxonomy of noisy terms into an OWL ontology. We share our experience and present the key aspects of our work that we believe will be useful for others working in this area.
Rafael S. Gonçalves, Matthew Horridge, Rui Li, Yu Liu, Mark A. Musen, Csongor I. Nyulas, Evelyn Obamos, Dhananjay Shrouty, David Temple [pdf] DOI: 10.1007/978-3-030-30796-7_26 1907.02106v1 [pdf]
-
Exploring effective charge in electromigration using machine learning -
Abstract
- The effective charge of an element is a parameter characterizing the electromgration effect, which can determine the reliability of interconnection in electronic technologies. In this work, machine learning approaches were employed to model the effective charge (z*) as a linear function of physically meaningful elemental properties. Average 5-fold (leave-out-alloy-group) cross-validation yielded root-mean-square-error divided by whole data set standard deviation (RMSE/$\sigma$) values of 0.37 $\pm$ 0.01 (0.22 $\pm$ 0.18), respectively, and $R^2$ values of 0.86. Extrapolation to z* of totally new alloys showed limited but potentially useful predictive ability. The model was used in predicting z* for technologically relevant host-impurity pairs.
Yu-chen Liu, Benjamin Afflerbach, Ryan Jacobs, Shih-kang Lin, Dane Morgan Journal reference: MRS Communications, 1-9 (2019) [pdf] DOI: 10.1557/mrc.2019.63
-
Super Fast Beam and Channel Tracking in 2D Phased Antenna Arrays -
Abstract
- Millimeter wave (mmWave) is an attractive candidate for high-speed mobile communications in the future. However, due to the propagation characteristics of mmWave, beam and and and and alignment becomes a key challenge for serving users with fast moving speeds. In this paper, we develop a joint beam and channel tracking algorithm that can track beams from the horizontal and vertical directions by using two-dimensional (2D) phased antenna arrays. A general sequence of optimal trial beamforming parameters is obtained to achieve the minimum Cramer-Rao lower bound (CRLB) of joint beam and channel tracking asymptotically as antenna number grows to infinity. This sequence is proved to be asymptotically optimal in different conditions, e.g., channel coefficients, path directions, and antenna array sizes. We prove that the proposed algorithm converges to the minimum CRLB in static scenarios. Simulation results show that our algorithm outperforms several existing algorithms in tracking accuracy and speed band.
Yu Liu, Jiahui Li, Yin Sun, Shidong Zhou [pdf]
-
Lattice dynamics and phase transitions in
-
Abstract
- We present Raman spectroscopy measurements of the van der Waals bonded ferromagnet Fe$_{3-x}$GeTe$_2$, together with lattice dynamics. Four out of eight Raman active modes are observed and assigned, in agreement with numerical calculations. The energies and line-widths of the observed modes display an unconventional temperature dependence at about 150 K and 220 K, followed by the nonmonotonic evolution of the Raman continuum. Whereas the former can be related to the magnetic phase transition, the origin of the latter anomaly remains an open question.
A. Milosavljević, A. Šolajić, S. Djurdjić-Mijin, J. Pešić, B. Višić, Yu Liu, C. Petrovic, N. Lazarević, Z. V. Popović Journal reference: Phys. Rev. B 99, 214304, Published 17 June 2019 [pdf] DOI: 10.1103/PhysRevB.99.214304
-
Implementing Black Hole as Efficient Power Plant -
Abstract
- Treating the black hole molecules as working substance and considering its phase structure, we study the black hole heat engine by a charged anti-de Sitter black hole. In the reduced temperature-entropy chart, it is found that the work, heat, and efficiency of the engine are free of the black hole charge. Applying the Rankine cycle with or without a back pressure mechanism to the black hole heat engine, the compact formula for the efficiency is obtained. And the heat, work and efficiency are worked out. The result shows that the black hole engine working along the Rankine cycle with a back pressure mechanism has a higher efficiency. This provides a novel and efficient mechanism to produce the useful mechanical work, and such black hole heat engine may act as a possible energy source for the high energy astrophysical phenomena near the black hole.
Shao-Wen Wei, Yu-Xiao Liu Journal reference: Commun. Theor. Phys. 71, 711 (2019) [pdf] DOI: 10.1088/0253-6102/71/6/711
-
Quasinormal modes and van der Waals-like phase transition of charged AdS black holes in Lorentz symmetry breaking massive gravity -
Abstract
- Using the quasinormal modes of a massless scalar perturbation, we investigate the small/large black hole phase transition in the Lorentz symmetry breaking massive gravity. We mainly focus on two issues: i) the sign change of slope of the quasinormal mode frequencies in the complex-$\omega$ diagram; ii) the behaviors of the imaginary part of the quasinormal mode frequencies along the isobaric or isothermal processes. For the first issue, our result shows that, at low fixed temperature or pressure, the phase transition can be probed by the sign change of slope. While increasing the temperature or pressure to some certain values near the critical point, there will appear the deflection point, which indicates that such method may not be appropriate to test the phase transition. In particular, the behavior of the quasinormal mode frequencies for the small and large black holes tend to the same at the critical point. For the second issue, it is shown that the non-monotonic behavior is observed only when the small/large black hole phase transition occurs. Therefore, this property can provide us with an additional method to probe the phase transition through the quasinormal modes.
Bin Liang, Shao-Wen Wei, Yu-Xiao Liu Journal reference: Int. J. Mod. Phys. D 28, 1950113 (2019) [pdf] DOI: 10.1142/S021827181950113X
-
From Caesar Cipher to Unsupervised Learning: A New Method for Classifier
Parameter Estimation -
Abstract
- Many important classification problems, such as object classification, speech recognition, and machine translation, have been tackled by the supervised learning paradigm in the past, where training corpora of parallel input-output pairs are required with high cost. To remove the need for the parallel training corpora has practical significance for real-world applications, and it is one of the main goals of unsupervised learning. Recently, encouraging progress in unsupervised learning for solving such classification problems has been made and the nature of the challenges has been clarified. In this article, we review this progress and disseminate a class of promising new methods to facilitate understanding the methods for machine learning researchers. In particular, we emphasize the key information that enables the success of unsupervised learning - the sequential statistics as the distributional prior in the labels. Exploitation of such sequential statistics makes it possible to estimate parameters of classifiers without the need of paired input-output data. In this paper, we first introduce the concept of Caesar Cipher and its decryption, which motivated the construction of the novel loss function for unsupervised learning we use throughout the paper. Then we use a simple but representative binary classification task as an example to derive and describe the unsupervised learning algorithm in a step-by-step, easy-to-understand fashion. We include two cases, one with Bigram language model as the sequential statistics for use in unsupervised parameter estimation, and another with a simpler Unigram language model. For both cases, detailed derivation steps for the learning algorithm are included. Further, a summary table compares computational steps of the two cases in executing the unsupervised learning algorithm for learning binary classifiers.
Yu Liu, Li Deng, Jianshu Chen, Chang Wen Chen [pdf]
-
Constraints on generalized Eddington-inspired Born-Infeld branes -
Abstract
- The Palatini $f(|\hat{\Omega}|)$ gravity is a generalized theory of the Eddington-inspired Born-Infeld gravity, where $\Omega_{~N}^{K}\equiv\delta_{~N}^{K}+bg^{KL}R_{LN}(\Gamma)$ is an auxiliary tensor constructed with the spacetime metric $g$ and independent connection $\Gamma$. In this paper, we study $f(|\hat{\Omega}|)$ theory with $f(|\hat{\Omega}|)=|\hat{\Omega}|^{\frac{1}{2}+n}$ in the thick brane scenario and give some constraints on the brane model. We finally found an analytic solution of the thick brane generated by a single scalar field. The behavior of the negative energy density denotes the localization of the thick brane at the origin of the extra dimension. In our braneworld, the warp factor is divergent at the boundary of the extra dimension while the brane system is asymptotically anti$-$de Sitter. It is shown that the tensor perturbation of the brane is stable and the massless graviton is localized on the thick brane. Therefore, the effective Einstein-Hilbert action on the brane can be rebuilt in the low-energy approximation. According to the recent test of the gravitational inverse-square law, we give some constraints on the $f(|\hat{\Omega}|)$ brane.
Zi-Chao Lin, Ke Yang, Yu-Peng Zhang, Jian Wang, Yu-Xiao Liu Journal reference: Phys. Rev. D 99, 084020 (2019) [pdf] DOI: 10.1103/PhysRevD.99.084020
-
Geodesics and periodic orbits in Kehagias-Sfetsos black holes in deformed Hor̆ava-Lifshitz gravity -
Abstract
- The motion of a massive test particle around a Kehagias-Sfetsos black hole in deformed Ho\u{r}ava-Lifshitz gravity is studied. Employing the effective potential, the marginally bound orbits and the innermost stable circular orbits are analyzed. For the marginally bound orbits, their radius and angular momentum decrease with the parameter $\omega$ of the gravity. For the innermost stable circular orbits, the energy and angular momentum also decrease with $\omega$. Based on these results, we investigate the periodic orbits in the Kehagias-Sfetsos black holes. It is found that the apsidal angle parameter increases with the particle energy, while decreases with the angular momentum. Moreover, compared to the Schwarzschild black hole, the periodic orbits in Kehagias-Sfetsos black holes always have lower energy. These results provide us a possible way to distinguish the Kehagias-Sfetsos black hole in deformed Ho\u{r}ava-Lifshitz gravity from the Schwarzschild black hole.
Shao-Wen Wei, Jie Yang, Yu-Xiao Liu Journal reference: Phys. Rev. D 99, 104016 (2019) [pdf] DOI: 10.1103/PhysRevD.99.104016
-
Gravitational Waves and Extra Dimensions: A Short Review -
Abstract
- We give a brief review on the recent development of gravitational waves in extra-dimensional theories of gravity. Studying extra-dimensional theories with gravitational waves provides a new way to constrain extra dimensions. After a flash look at the history of gravitational waves and a brief introduction to several major extra-dimensional theories, we focus on the sources and spectra of gravitational waves in extra-dimensional theories. It is shown that one can impose limits on the size of extra dimensions and the curvature of the universe by researching the propagations of gravitational waves and the corresponding electromagnetic waves. Since gravitational waves can propagate throughout the bulk, how the amplitude of gravitational waves decreases determines the number of extra dimensions for some models. In addition, we also briefly present some other characteristics of gravitational waves in extra-dimensional theories.
Hao Yu, Zi-Chao Lin, Yu-Xiao Liu Journal reference: Commun. Theor. Phys. 71 (2019) 991-1006 [pdf] DOI: 10.1088/0253-6102/71/8/991
-
Parts4Feature: Learning 3D Global Features from Generally Semantic Parts
in Multiple Views -
Abstract
- Deep learning has achieved remarkable results in 3D shape analysis by learning global shape features from the pixel-level over multiple views. Previous methods, however, compute low-level features for entire views without considering part-level information. In contrast, we propose a deep neural network, called Parts4Feature, to learn 3D global features from part-level information in multiple views. We introduce a novel definition of generally semantic parts, which Parts4Feature learns to detect in multiple views from different 3D shape segmentation benchmarks. A key idea of our architecture is that it transfers the ability to detect semantically meaningful parts in multiple views to learn 3D global features. Parts4Feature achieves this by combining a local part detection branch and a global feature learning branch with a shared region proposal module. The global feature learning branch aggregates the detected parts in terms of learned part patterns with a novel multi-attention mechanism, while the region proposal module enables locally and globally discriminative information to be promoted by each other. We demonstrate that Parts4Feature outperforms the state-of-the-art under three large-scale 3D shape benchmarks.
Zhizhong Han, Xinhai Liu, Yu-Shen Liu, Matthias Zwicker [pdf]
-
3DViewGraph: Learning Global Features for 3D Shapes from A Graph of
Unordered Views with Attention -
Abstract
- Learning global features by aggregating information over multiple views has been shown to be effective for 3D shape analysis. For view aggregation in deep learning models, pooling has been applied extensively. However, pooling leads to a loss of the content within views, and the spatial relationship among views, which limits the discriminability of learned features. We propose 3DViewGraph to resolve this issue, which learns 3D global features by more effectively aggregating unordered views with attention. Specifically, unordered views taken around a shape are regarded as view nodes on a view graph. 3DViewGraph first learns a novel latent semantic mapping to project low-level view features into meaningful latent semantic embeddings in a lower dimensional space, which is spanned by latent semantic patterns. Then, the content and spatial information of each pair of view nodes are encoded by a novel spatial pattern correlation, where the correlation is computed among latent semantic patterns. Finally, all spatial pattern correlations are integrated with attention weights learned by a novel attention mechanism. This further increases the discriminability of learned features by highlighting the unordered view nodes with distinctive characteristics and depressing the ones with appearance ambiguity. We show that 3DViewGraph outperforms state-of-the-art methods under three large-scale benchmarks.
Zhizhong Han, Xiyang Wang, Chi-Man Vong, Yu-Shen Liu, Matthias Zwicker, C. L. Philip Chen [pdf]
-
Modulating quantum Fisher information of qubit in dissipative cavity by coupling strength -
Abstract
- By using the non-Markovian master equation, we investigate the effect of the cavity and the environment on the quantum Fisher information (QFI) of an atom qubit system in a dissipation cavity. We obtain the formulae of QFI for two different initial states and analyze the effect of the atom-cavity coupling and the cavity-reservoir coupling on the QFI. The results show that the dynamic behavior of the QFI is obviously dependent on the initial atomic states, the atom-cavity coupling and the cavity-reservoir coupling. The stronger the atom-cavity coupling, the quicker the QFI oscillates and the slower the QFI reduces. Especially, the QFI will tend to a stable value not zero if the atom-cavity coupling is large enough. On the other hand, the smaller the cavity-reservoir coupling, the stronger the non-Markovian effect, the slower the QFI decay. In other words, choosing the best parameter can improve the accuracy of parameter estimation. In addition, the physical explanation of the dynamic behavior of the QFI is given by means of the QFI flow.
Danping Lin, Yu Liu, Hong-Mei Zou Journal reference: Chin. Phys. B . 2018, 27(11): 110303 [pdf] DOI: 10.1088/1674-1056/27/11/110303
-
Superposition of macroscopically squeezed states with enhanced squeezing
in cavity optomechanical system at single-photon level -
Abstract
- We propose an efficient approach to generate the superposed macroscopically squeezed states with enhanced squeezing in a two-mode optomechanical system. This can be achieved by introducing a sinusoidal modulation to either the cavity frequencies or the coupling strengths between two cavity modes. The squeezement of the oscillator can be significantly enhanced to 12.16 dB with single photon, once the relative ratio of coupling strength is optimized under proper conditions. Further enhanced squeezing can be obtained by carefully adjusting the system parameters. In terms of the Wigner quasi-probability distribution, we show the squeezed error ellipses and interference fringes of the Yurke-Stoler-type squeezed states, denoting the squeezing and superposition properties. Our state generation scheme show reliable performance and robust resistance to finite environmental fluctuations, which implies applications for both fundamental interest and practical value.
Sai-Nan Huai, Wei Nie, Yun-bo Zhang, Yu-xi Liu [pdf]
-
PRSim -
Abstract
- {\it SimRank} is a classic measure of the similarities of nodes in a graph. Given a node $u$ in graph $G =(V, E)$, a {\em single-source SimRank query} returns the SimRank similarities $s(u, v)$ between node $u$ and each node $v \in V$. This type of queries has numerous applications in web search and social networks analysis, such as link prediction, web mining, and spam detection. Existing methods for single-source SimRank queries, however, incur query cost at least linear to the number of nodes $n$, which renders them inapplicable for real-time and interactive analysis. { This paper proposes \prsim, an algorithm that exploits the structure of graphs to efficiently answer single-source SimRank queries. \prsim uses an index of size $O(m)$, where $m$ is the number of edges in the graph, and guarantees a query time that depends on the {\em reverse PageRank} distribution of the input graph. In particular, we prove that \prsim runs in sub-linear time if the degree distribution of the input graph follows the power-law distribution, a property possessed by many real-world graphs. Based on the theoretical analysis, we show that the empirical query time of all existing SimRank algorithms also depends on the reverse PageRank distribution of the graph.} Finally, we present the first experimental study that evaluates the absolute errors of various SimRank algorithms on large graphs, and we show that \prsim outperforms the state of the art in terms of query time, accuracy, index size, and scalability.
Zhewei Wei, Xiaodong He, Xiaokui Xiao, Sibo Wang, Yu Liu, Xiaoyong Du, Ji-Rong Wen [pdf] DOI: 10.1145/3299869.3319873 1905.02354v1 [pdf]
-
Extracting human emotions at different places based on facial expressions and spatial clustering analysis -
Abstract
- The emergence of big data enables us to evaluate the various human emotions at places from a statistic perspective by applying affective computing. In this study, a novel framework for extracting human emotions from large-scale georeferenced photos at different places is proposed. After the construction of places based on spatial clustering of user generated footprints collected in social media websites, online cognitive services are utilized to extract human emotions from facial expressions using the state-of-the-art computer vision techniques. And two happiness metrics are defined for measuring the human emotions at different places. To validate the feasibility of the framework, we take 80 tourist attractions around the world as an example and a happiness ranking list of places is generated based on human emotions calculated over 2 million faces detected out from over 6 million photos. Different kinds of geographical contexts are taken into consideration to find out the relationship between human emotions and environmental factors. Results show that much of the emotional variation at different places can be explained by a few factors such as openness. The research may offer insights on integrating human emotions to enrich the understanding of sense of place in geography and in place-based GIS.
Yuhao Kang, Qingyuan Jia, Song Gao, Xiaohuan Zeng, Yueyao Wang, Stephan Angsuesser, Yu Liu, Xinyue Ye, Teng Fei Journal reference: Transactions in GIS, Year 2019, Volume 23, Issue 3 [pdf] DOI: 10.1111/tgis.12552
-
Chiral kinetic theory in curved spacetime -
Abstract
- Many-body systems with chiral fermions exhibit anomalous transport phenomena originated from quantum anomalies. Based on quantum field theory, we derive the kinetic theory for chiral fermions interacting with an external electromagnetic field and a background curved geometry. The resultant framework respects the covariance under the U(1) gauge, local Lorentz, and diffeomorphic transformations. It is particularly useful to study the gravitational or non-inertial effects for chiral systems. As the first application, we study the chiral dynamics in a rotating coordinate and clarify the roles of the Coriolis force and spin-vorticity coupling in generating the chiral vortical effect (CVE). We also show that the CVE is an intrinsic phenomenon of a rotating chiral fluid, and thus independent of observer's frame.
Yu-Chen Liu, Lan-Lan Gao, Kazuya Mameda, Xu-Guang Huang Journal reference: Phys. Rev. D 99, 085014 (2019) [pdf] DOI: 10.1103/PhysRevD.99.085014
-
RGBD Based Dimensional Decomposition Residual Network for 3D Semantic
Scene Completion -
Abstract
- RGB images differentiate from depth images as they carry more details about the color and texture information, which can be utilized as a vital complementary to depth for boosting the performance of 3D semantic scene completion (SSC). SSC is composed of 3D shape completion (SC) and semantic scene labeling while most of the existing methods use depth as the sole input which causes the performance bottleneck. Moreover, the state-of-the-art methods employ 3D CNNs which have cumbersome networks and tremendous parameters. We introduce a light-weight Dimensional Decomposition Residual network (DDR) for 3D dense prediction tasks. The novel factorized convolution layer is effective for reducing the network parameters, and the proposed multi-scale fusion mechanism for depth and color image can improve the completion and segmentation accuracy simultaneously. Our method demonstrates excellent performance on two public datasets. Compared with the latest method SSCNet, we achieve 5.9% gains in SC-IoU and 5.7% gains in SSC-IOU, albeit with only 21% network parameters and 16.6% FLOPs employed compared with that of SSCNet.
Jie Li, Yu Liu, Dong Gong, Qinfeng Shi, Xia Yuan, Chunxia Zhao, Ian Reid [pdf]
-
Experimental Quantum-enhanced Cryptographic Remote Control -
Abstract
- The Internet of Things (IoT), as a cutting-edge integrated cross-technology, promises to informationize people's daily lives, while being threatened by continuous challenges of eavesdropping and tampering. The emerging quantum cryptography, harnessing the random nature of quantum mechanics, may also enable unconditionally secure control network, beyond the applications in secure communications. Here, we present a quantum-enhanced cryptographic remote control scheme that combines quantum randomness and one-time pad algorithm for delivering commands remotely. We experimentally demonstrate this on an unmanned aircraft vehicle (UAV) control system. We precharge quantum random number (QRN) into controller and controlee before launching UAV, instead of distributing QRN like standard quantum communication during flight. We statistically verify the randomness of both quantum keys and the converted ciphertexts to check the security capability. All commands in the air are found to be completely chaotic after encryption, and only matched keys on UAV can decipher those commands precisely. In addition, the controlee does not response to the commands that are not or incorrectly encrypted, showing the immunity against interference and decoy. Our work adds true randomness and quantum enhancement into the realm of secure control algorithm in a straightforward and practical fashion, providing a promoted solution for the security of artificial intelligence and IoT.
Xiao-Ling Pang, Lu-Feng Qiao, Ke Sun, Yu Liu, Ai-Lin Yang, Xian-Min Jin [pdf]
-
AIP Conference Proceedings -
Abstract
- We investigate the chemical potential and baryon number density of the hadron-quark phase transition in neutron star matter. The hadron matter is described with relativistic mean field theory, and the quark matter is described with the Dyson-Schwinger equation approach of QCD. In order to study the first-order phase transition, we develop the sound speed interpolation scheme to construct the equation of state in the middle density region where the hadron phase and quark phase coexist. The phase transition chemical potential is constrained with the maximum mass, the tidal deformability and the radius of neutrons stars. And the most probable value of the phase transition chemical potential is found.
Zhan Bai, Yu-xin Liu [pdf] DOI: 10.1063/1.5117820 1904.01978v3 [pdf]
-
Talking Face Generation by Adversarially Disentangled Audio-Visual
Representation -
Abstract
- Talking face generation aims to synthesize a sequence of face images that correspond to a clip of speech. This is a challenging task because face appearance variation and semantics of speech are coupled together in the subtle movements of the talking face regions. Existing works either construct specific face appearance model on specific subjects or model the transformation between lip motion and speech. In this work, we integrate both aspects and enable arbitrary-subject talking face generation by learning disentangled audio-visual representation. We find that the talking face sequence is actually a composition of both subject-related information and speech-related information. These two spaces are then explicitly disentangled through a novel associative-and-adversarial training process. This disentangled representation has an advantage where both audio and video can serve as inputs for generation. Extensive experiments show that the proposed approach generates realistic talking face sequences on arbitrary subjects with much clearer lip motion patterns than previous work. We also demonstrate the learned audio-visual representation is extremely useful for the tasks of automatic lip reading and audio-video retrieval.
Hang Zhou, Yu Liu, Ziwei Liu, Ping Luo, Xiaogang Wang [pdf]
-
Knowledge Distillation via Route Constrained Optimization -
Abstract
- Distillation-based learning boosts the performance of the miniaturized neural network based on the hypothesis that the representation of a teacher model can be used as structured and relatively weak supervision, and thus would be easily learned by a miniaturized model. However, we find that the representation of a converged heavy model is still a strong constraint for training a small student model, which leads to a high lower bound of congruence loss. In this work, inspired by curriculum learning we consider the knowledge distillation from the perspective of curriculum learning by routing. Instead of supervising the student model with a converged teacher model, we supervised it with some anchor points selected from the route in parameter space that the teacher model passed by, as we called route constrained optimization (RCO). We experimentally demonstrate this simple operation greatly reduces the lower bound of congruence loss for knowledge distillation, hint and mimicking learning. On close-set classification tasks like CIFAR100 and ImageNet, RCO improves knowledge distillation by 2.14% and 1.5% respectively. For the sake of evaluating the generalization, we also test RCO on the open-set face recognition task MegaFace.
Xiao Jin, Baoyun Peng, Yichao Wu, Yu Liu, Jiaheng Liu, Ding Liang, Junjie Yan, Xiaolin Hu [pdf]
-
Gravitational resonances in mimetic thick branes -
Abstract
- In this work, we investigate gravitational resonances in both single and double mimetic thick branes, which can provide a new way to detect the extra dimension. For the single brane model, we apply the relative probability proposed in [Phys. Rev. D. 80 (2009) 065019]. For the double brane model, we investigate the resonances quasi-localized on the double brane, on the sub-branes and between the sub-branes, respectively. To investigate the resonances quasi-localized on the double brane, we introduce two different definitions of the relative probability and find that the corresponding mass spectra of gravitational resonances are almost the same. For the gravitational resonances quasi-localized on sub-branes and between the sub-branes, the influence of the distance between the two sub-branes and the thickness of the sub-branes are analyzed and new features are found in both cases.
Yi Zhong, Yu-Peng Zhang, Wen-Di Guo, Yu-Xiao Liu Journal reference: JHEP 1904 (2019) 154 [pdf] DOI: 10.1007/JHEP04(2019)154
-
Adversarial Cross-Modal Retrieval via Learning and Transferring
Single-Modal Similarities -
Abstract
- Cross-modal retrieval aims to retrieve relevant data across different modalities (e.g., texts vs. images). The common strategy is to apply element-wise constraints between manually labeled pair-wise items to guide the generators to learn the semantic relationships between the modalities, so that the similar items can be projected close to each other in the common representation subspace. However, such constraints often fail to preserve the semantic structure between unpaired but semantically similar items (e.g. the unpaired items with the same class label are more similar than items with different labels). To address the above problem, we propose a novel cross-modal similarity transferring (CMST) method to learn and preserve the semantic relationships between unpaired items in an unsupervised way. The key idea is to learn the quantitative similarities in single-modal representation subspace, and then transfer them to the common representation subspace to establish the semantic relationships between unpaired items across modalities. Experiments show that our method outperforms the state-of-the-art approaches both in the class-based and pair-based retrieval tasks.
Xin Wen, Zhizhong Han, Xinyu Yin, Yu-Shen Liu [pdf]
-
Measuring road network topology vulnerability by Ricci curvature -
Abstract
- Describing the basic properties of road network systems, such as their robustness, vulnerability, and reliability, has been a very important research topic in the field of urban transportation. Current research mainly uses several statistical indicators of complex networks to analyze the road network systems. However, these methods are essentially node-based. These node-based methods are more concerned with the number of connections between nodes, and lack of consideration for interactions. So, this leads to the well-known node paradox problem, and their ability of characterizing the local and intrinsic properties of a network is weak. From the perspective of network intrinsic geometry, this paper proposes a method for measuring road network vulnerability using a discrete Ricci curvature, which can identify the key sections of a road network and indicate its fragile elements. The results show that our method performs better than complex network statistics on measuring the vulnerability of a road network. Additionally, it can characterize the evolution of the road network vulnerability among different periods of time in the same city through our method. Finally, we compare our method with the previous method of centrality and show the different between them. This article provides a new perspective on a geometry to analyze the vulnerability of a road network and describes the inherent nature of the vulnerability of a road system from a new perspective. It also contributes to enriching the analytical methods of complex road networks.
Lei Gao, Xingquan Liu, Yu Liu, Pu Wang, Min Deng, Qing Zhu, Haifeng Li Journal reference: Physica A: Statistical Mechanics and its Applications 2019 [pdf] DOI: 10.1016/j.physa.2019.121071
-
Eta decay and muonic puzzles -
Abstract
- New physics motivated by muonic puzzles (proton radius and muon $g-2$ discrepancies) is studied. Using a light scalar boson $\phi$, assuming Yukawa interactions, accounts for these muonic puzzles simultaneously. Our previous work limits the existence of such a scalar boson's mass $m_\phi$ from about 160 keV to 60 MeV. We improve this result by including the influence of all of the possible particles that couple to the $\phi$ in computing the decay rate. Doing this involves including the strong interaction physics, involving quarks, necessary to compute the $\eta\pi\phi$ vertex function. The Nambu-Jona-Lasinio model, which accounts for the spontaneous symmetry breaking that yields the constituent mass is employed to represent the relevant strong-interaction physics. We use the $\eta\pi\phi$ vertex function to reanalyze the electron beam dump experiments. The result is that the allowed range of $m_\phi$ lies between about 160 keV and 3.5 MeV. This narrow range represents an inviting target for ruling out or discovering this scalar boson. A possible UV completion of our phenomenological model is discussed.
Yu-Sheng Liu, Ian C. Cloët, Gerald A. Miller [pdf] DOI: 10.1016/j.nuclphysb.2019.114638 1805.01028v2 [pdf]
-
Weak cosmic censorship conjecture in Kerr black holes of modified gravity -
Abstract
- By neglecting the effects of self-force and radiation, we investigate the possibility of destroying the Kerr-MOG black hole through the point particle absorption process. Using the instability of event horizon and equation of particle motion, we get the upper and lower energy bounds allowed for a matter particle to produce the naked singularity. We find that the energy gap always exists between the upper and lower energy bounds for both extremal and near-extremal black holes, which means some tailored particles can actually lead to the violation of the weak cosmic censorship conjecture. However, when considering the effect of the adiabatic process, the result shows that the Kerr-MOG black hole gets more stable instead of a naked singularity, and thus the weak cosmic censorship conjecture can be restored at some level.
Bin Liang, Shao-Wen Wei, Yu-Xiao Liu Journal reference: Mod. Phys. Lett. A 34, 1950037 (2019) [pdf] DOI: 10.1142/S0217732319500378
-
Thermodynamics of
-
Abstract
- We study the thermodynamics of QCD system under external magnetic field via the 2+1 flavor Polyakov-loop quark-meson model. To incorporate quantum and thermal fluctuations, the functional renormalization group approach is implemented in our work. Pressure, entropy density, magnetic susceptibility and other thermodynamic quantities are calculated and analyzed to investigate the effect of magnetic field on the QCD system. The calculated results are in reasonable agreement with lattice QCD simulations and perturbation theory. We then give an intuitive picture for the response of QCD system to the magnetic field.
Xiang Li, Wei-jie Fu, Yu-xin Liu Journal reference: Phys. Rev. D 99, 074029 (2019) [pdf] DOI: 10.1103/PhysRevD.99.074029
-
Correlation Congruence for Knowledge Distillation -
Abstract
- Most teacher-student frameworks based on knowledge distillation (KD) depend on a strong congruent constraint on instance level. However, they usually ignore the correlation between multiple instances, which is also valuable for knowledge transfer. In this work, we propose a new framework named correlation congruence for knowledge distillation (CCKD), which transfers not only the instance-level information, but also the correlation between instances. Furthermore, a generalized kernel method based on Taylor series expansion is proposed to better capture the correlation between instances. Empirical experiments and ablation studies on image classification tasks (including CIFAR-100, ImageNet-1K) and metric learning tasks (including ReID and Face Recognition) show that the proposed CCKD substantially outperforms the original KD and achieves state-of-the-art accuracy compared with other SOTA KD-based methods. The CCKD can be easily deployed in the majority of the teacher-student framework such as KD and hint-based learning methods.
Baoyun Peng, Xiao Jin, Jiaheng Liu, Shunfeng Zhou, Yichao Wu, Yu Liu, Dongsheng Li, Zhaoning Zhang [pdf]
-
Conditional Adversarial Generative Flow for Controllable Image Synthesis -
Abstract
- Flow-based generative models show great potential in image synthesis due to its reversible pipeline and exact log-likelihood target, yet it suffers from weak ability for conditional image synthesis, especially for multi-label or unaware conditions. This is because the potential distribution of image conditions is hard to measure precisely from its latent variable $z$. In this paper, based on modeling a joint probabilistic density of an image and its conditions, we propose a novel flow-based generative model named conditional adversarial generative flow (CAGlow). Instead of disentangling attributes from latent space, we blaze a new trail for learning an encoder to estimate the mapping from condition space to latent space in an adversarial manner. Given a specific condition $c$, CAGlow can encode it to a sampled $z$, and then enable robust conditional image synthesis in complex situations like combining person identity with multiple attributes. The proposed CAGlow can be implemented in both supervised and unsupervised manners, thus can synthesize images with conditional information like categories, attributes, and even some unknown properties. Extensive experiments show that CAGlow ensures the independence of different conditions and outperforms regular Glow to a significant extent.
Rui Liu, Yu Liu, Xinyu Gong, Xiaogang Wang, Hongsheng Li [pdf]
-
Determining Hadron-Quark Phase Transition Chemical Potential via
Astronomical Observations -
Abstract
- We propose a scheme to determine the chemical potential and baryon number density of the hadron-quark phase transition in cold dense strong interaction matter (compact star matter). The hadron matter is described with the relativistic mean field theory, and the quark matter is described with the Dyson-Schwinger equation approach of QCD. To study the first-order phase transition, we take the sound speed as the interpolation objective to construct the equation of state in the middle density region. With the maximum mass, the tidal deformability and the radius of neutron stars being taken as calibration quantities, the phase transition chemical potential is constrained to a quite small range. And the most probable value of the phase transition chemical potential is found.
Zhan Bai, Yu-xin Liu [pdf]
-
Pulsed Quantum-State Reconstruction of Dark Systems -
Abstract
- We propose a novel strategy to reconstruct the quantum state of dark systems, i.e., degrees of freedom that are not directly accessible for measurement or control. Our scheme relies on the quantum control of a two-level probe that exerts a state-dependent potential on the dark system. Using a sequence of control pulses applied to the probe makes it possible to tailor the information one can obtain and, for example, allows us to reconstruct the density operator of a dark spin as well as the Wigner characteristic function of a harmonic oscillator. Because of the symmetry of the applied pulse sequence, this scheme is robust against slow noise on the probe. The proof-of-principle experiments are readily feasible in solid-state spins and trapped ions.
Yu Liu, Jiazhao Tian, Ralf Betzholz, Jianming Cai Journal reference: Phys. Rev. Lett. 122, 110406 (2019) [pdf] DOI: 10.1103/PhysRevLett.122.110406
-
Multipath-enabled private audio with noise -
Abstract
- We address the problem of privately communicating audio messages to multiple listeners in a reverberant room using a set of loudspeakers. We propose two methods based on emitting noise. In the first method, the loudspeakers emit noise signals that are appropriately filtered so that after echoing along multiple paths in the room, they sum up and descramble to yield distinct meaningful audio messages only at specific focusing spots, while being incoherent everywhere else. In the second method, adapted from wireless communications, we project noise signals onto the nullspace of the MIMO channel matrix between the loudspeakers and listeners. Loudspeakers reproduce a sum of the projected noise signals and intended messages. Again because of echoes, the MIMO nullspace changes across different locations in the room. Thus, the listeners at focusing spots hear intended messages, while the acoustic channel of an eavesdropper at any other location is jammed. We show, using both numerical and real experiments, that with a small number of speakers and a few impulse response measurements, audio messages can indeed be communicated to a set of listeners while ensuring negligible intelligibility elsewhere.
Anadi Chaman, Yu-Jeh Liu, Jonah Casebeer, Ivan Dokmanić [pdf]
-
Possible correlations between gamma-ray burst and its host galaxy offset -
Abstract
- We collected the information of 304 gamma-ray bursts (GRBs) from the literature, and analyzed the correlations among the host galaxy offsets (the distance from the site of the GRB to the center of its host galaxy), $T_{\rm 90,i}$ (the duration $T_{\rm 90}$ in rest-frame), $T_{\rm R45,i}$ (the duration $T_{\rm R45}$ in rest-frame), $E_{\rm \gamma,iso}$ (the isotropic equivalent energy), $L_{\rm \gamma,iso}$ ($=E_{\rm \gamma,iso}/T_{\rm 90,i}$, the isotropic equivalent luminosity) and $L_{\rm pk}$ (peak luminosity). We found that $ T_{\rm 90,i}$, $ T_{\rm R45,i}$, $ E_{\rm \gamma,iso}$, $L_{\rm pk}$ have negative correlation with $ {\rm offset}$, which is consistent with origin of short GRBs (SGRBs) and long GRBs (LGRBs). On separate analysis, we found similar results for $\log E_{\rm \gamma,iso}$ - $\log {\rm (offset)}$ and $\log L_{\rm pk}$ - $\log {\rm (offset)}$ relations in case of SGRBs only, while no obvious relation for LGRBs. There is no correlations between offset and $L_{\rm \gamma,iso}$. We also put the special GRB 170817A {and GRB 060218A} on the plots. {The two GRBs both have low luminosity and small offset.} In the $ \log ({\rm offset})- \log T_{\rm 90,i}$ plot, we found GRB 170817A locates in between the two regions of SGRBs and LGRBs and it is the outlier in the $ {\rm offset}-E_{\rm \gamma, iso}$, $ {\rm offset}-L_{\rm \gamma, iso}$ and $ {\rm offset}-L_{\rm pk}$ plots. Together with GRB 060218A being an outlier in all plots, it indicates the speciality of GRBs 170817A and 060218A, and might imply more subgroups of the GRB samples.
Fei-Fei Wang, Yuan-Chuan Zou, Yu Liu, Bin Liao, Reetanjali Moharana Journal reference: 2018JHEAp..18...21W [pdf] DOI: 10.1016/j.jheap.2018.03.001
-
Dressed quark tensor vertex and nucleon tensor charge -
Abstract
- We construct the quark-antiquark scattering kernels of Bethe-Salpeter equation from the quark self-energy directly under two specific forms of quark-gluon vertices. The quark dressed tensor vertex is then calculated within this consistent framework and rainbow-ladder(RL) approximation. After employing a simplified nucleon model, the nucleon tensor charge can be defined with the tensor vertex. We then compute the tensor charge with the bare tensor vertex and the dressed vertices obtained in this framework and in RL approximation. The obtained results are consistent with the lattice QCD calculations. We also find that typically the gluon dressing effects suppress the nucleon tensor charge compared to the bare tensor vertex, by about $23\%$ for RL approximation, and turn to be about $13\%$ in this framework.
Langtian Liu, Lei Chang, Yu-xin Liu Journal reference: Phys. Rev. D 99, 074013 (2019) [pdf] DOI: 10.1103/PhysRevD.99.074013
-
Abelian quotients associated with fully rigid subcategories -
Abstract
- In this article, we study the Gorenstein property of abelian quotient categories induced by fully rigid subcategories on an exact category B. We also study when d-cluster tilting subcategories become fully rigid. We show that the quotient abelian category induced by such d-cluster tilting subcategories are hereditary.
Yu Liu [pdf]
-
A New Model to Predict Optimum Conditions for Growth of 2D Materials on a Substrate -
Abstract
- Very recently we developed an efficient method to calculate the free energy of 2D materials on substrates and achieved high calculation precision for graphene or $\gamma$-graphyne on copper substrates. In the present work, the method was further confirmed to be accurate by molecular dynamic simulations of silicene on Ag substrate using empirical potential and was applied to predict the optimum conditions based on \emph{ab initio} calculations for silicene growth on Ag (110) and Ag (111) surface, which are in good agreement with previous experimental observations.
Yu-Peng Liu, Bo-Yuan Ning, Le-Cheng Gong, Tsu-Chien Weng, Xi-Jing Ning Journal reference: Nanomaterials, 9(2019) 978 [pdf] DOI: 10.3390/nano9070978
-
A Comprehensive Statistical Study of Gamma-Ray Bursts -
Abstract
- In order to obtain an overview of the gamma-ray bursts (GRBs), we need a full sample. In this paper, we collected 6289 GRBs (from GRB 910421 to GRB 160509A) from the literature, including prompt emission, afterglow and host galaxy properties. We hope to use this large sample to reveal the intrinsic properties of GRB. We have listed all the data in machine readable tables, including the properties of the GRBs, correlation coefficients and linear regression results of two arbitrary parameters, and linear regression results of any three parameters. These machine readable tables could be used as a data reservoir for further studies on the classifications or correlations. One may find some intrinsic properties from these statistical results. With this comprehensive table, it is possible to find relations between different parameters, and to classify the GRBs into different kinds of sub-groups. With the completion, it may reveal the nature of GRBs and may be used as tools like pseudo-redshift indicators, standard candles, etc. All the machine readable data and statistical results are available on the website of the journal.
Feifei Wang, Yuan-Chuan Zou, Fuxiang Liu, Bin Liao, Yu Liu, Yating Chai, Lei Xia [pdf] DOI: 10.3847/1538-4357/ab0a86 1902.05489v1 [pdf]
-
Intrinsic curvature and topology of shadows in Kerr spacetime -
Abstract
- From the viewpoint of differential geometry and topology, we investigate the characterization of the shadows in a Kerr spacetime. Two new quantities, the length of the shadow boundary and the local curvature radius are introduced. Each shadow can be uniquely determined by these two quantities. For the black hole case, the result shows that we can constrain the black hole spin and the angular coordinate of the observer only by measuring the maximum and minimum of the curvature radius. While for the naked singularity case, we adopt the length parameter and the maximum of the curvature radius. This technique is completely independent of the coordinate system and the location of the shadow, and is expected to uniquely determine the parameters of the spacetime. Moreover, we propose a topological covariant quantity to measure and distinguish different topological structures of the shadows.
Shao-Wen Wei, Yu-Xiao Liu, Robert B. Mann Journal reference: Phys. Rev. D 99, 041303 (2019) [pdf] DOI: 10.1103/PhysRevD.99.041303
-
Probing the relationship between the null geodesics and thermodynamic phase transition for rotating Kerr-AdS black holes -
Abstract
- In this paper, we aim to examine the relationship between the unstable circular photon orbit and the thermodynamic phase transition for a rotating Kerr-AdS black hole. On one side, we give a brief review of the phase transition for the Kerr-AdS black hole. The coexistence curve and the metastable curve corresponding to the phase transition are clearly shown. On the other side, we calculate the radius and the angular momentum of the unstable circular orbits for a photon by analyzing the effective potential. Then combining these two sides, we find the following results. i) The radius and the angular momentum of the unstable circular photon orbits demonstrate the non-monotonic behaviors when the thermodynamic phase transition takes place. So from the behavior of the circular orbit, one can determine whether there exists a thermodynamic phase transition. ii) The difference of the radius or the angular momentum for the coexistence small and large black holes can be treated as an order parameter to describe the phase transition. And near the critical point, it has a critical exponent of $\frac{1}{2}$. iii) The temperature and pressure corresponding to the extremal points of the radius or the angular momentum of the unstable circular photon orbit completely agree with that of the metastable curves from the thermodynamic side. Thus, these results confirm the relationship between the geodesics and thermodynamic phase transition for the Kerr-AdS black hole. Therefore, on one hand, we are allowed to probe the thermodynamic phase transition from the gravity side. On the other hand, the signature of the strong gravitational effect can also be revealed from the black hole thermodynamics.
Shao-Wen Wei, Yu-Xiao Liu, Yong-Qiang Wang Journal reference: Phys. Rev. D 99, 044013 (2019) [pdf] DOI: 10.1103/PhysRevD.99.044013
-
A New Model to Predict Optimum Conditions for Growth of 2D Materials on a Substrate -
Abstract
- A method was developed to calculate the free energy of 2D materials on substrates and was demonstrated by the system of graphene and {\gamma}-graphyne on copper substrate. The method works at least 3 orders faster than state-of-the-art algorithms, and the accuracy was tested by molecular dynamics simulations, showing that the precision for calculations of the internal energy achieves up to 0.03% in a temperature range from 100 to 1300K. As expected, the calculated the free energy of a graphene sheet on Cu (111) or Ni (111) surface in a temperature range up to 3000K is always smaller than the one of a {\gamma}-graphyne sheet with the same number of C atoms, which is consistent with the fact that growth of graphene on the substrates is much easier than {\gamma}-graphyne.
Yu-Peng Liu, Bo-Yuan Ning, Le-Cheng Gong, Tsu-Chien Weng, Xi-Jing Ning Journal reference: Nanomaterials, 9(2019) 978 [pdf] DOI: 10.3390/nano9070978
-
Pentaquark states with the
$$QQQq\bar{q}$$
Q
Q
Q
q
q
¯
configuration in a simple model -
Abstract
- We discuss the mass splittings for the $S$-wave triply heavy pentaquark states with the $QQQq\bar{q}$ $(Q=b,c;q=u,d,s)$ configuration which is a mirror structure of $Q\bar{Q}qqq$. The latter configuration is related with the nature of $P_c(4380)$ observed by the LHCb Collaboration. The considered pentaquark masses are roughly estimated with a simple method. One finds that such states are probably not narrow even if they do exist. This leaves room for molecule interpretation for a state around the low-lying threshold of a doubly heavy baryon and a heavy-light meson, e.g. $\Xi_{cc}D$, if it were observed. As a by product, we conjecture that upper limits for the masses of the conventional triply heavy baryons can be determined by the masses of the conventional doubly heavy baryons.
Shi-Yuan Li, Yan-Rui Liu, Yu-Nan Liu, Zong-Guo Si, Jing Wu Journal reference: Eur. Phys. J. C 79, 87 (2019) [pdf] DOI: 10.1140/epjc/s10052-019-6589-7
-
First Unambiguous Imaging of Large-scale Quasi-periodic Extreme-ultraviolet Wave or Shock -
Abstract
- We report the first unambiguous quasi-periodic large-scale extreme-ultraviolet (EUV) wave or shock that was detected by the Atmospheric Imaging Assembly on board the Solar Dynamics Observatory. During the whip-like unwinding eruption of a small filament on 2012 April 24, multiple consecutive large-scale wavefronts emanating from AR11467 were observed simultaneously along the solar surface and a closed transequatorial loop system. In the meantime, an upward propagating dome-shaped wavefront was also observed, whose initial speed and deceleration are about 1392 km/s and 1.78 km/s^2, respectively. Along the solar surface, the quasi-peridoic wavefronts had a period of about 163 +/- 21 seconds and propagated at a nearly constant speed of 747 +/- 26 km/s; they interacted with active region AR11469 and launched a sympathetic upward propagating secondary EUV wave. The wavefronts along the loop system propagated at a speed of 897 km/s, and they were reflected back at the southern end of the loop system at a similar speed. In addition to the propagating waves, a standing kink wave was also present in the loop system simultaneously. Periodicity analysis reveals that the period of the wavefronts was consistent with that of the unwinding helical structures of the erupting filament. Based on these observational facts, we propose that the observed quasi-periodic EUV wavefronts were most likely excited by the periodic unwinding motion of the filament helical structures. In addition, two different seismological methods are applied to derive the magnetic field strength of the loop system, and for the first time the reliability of these inversion techniques are tested with the same magnetic structure.
Yuandeng Shen, P. F. Chen, Ying D. Liu, Kazunari Shibata, Zehao Tang, Yu Liu [pdf] DOI: 10.3847/1538-4357/ab01dd 1901.08199v1 [pdf]
-
Rate Distortion For Model Compression: From Theory To Practice -
Abstract
- The enormous size of modern deep neural networks makes it challenging to deploy those models in memory and communication limited scenarios. Thus, compressing a trained model without a significant loss in performance has become an increasingly important task. Tremendous advances has been made recently, where the main technical building blocks are parameter pruning, parameter sharing (quantization), and low-rank factorization. In this paper, we propose principled approaches to improve upon the common heuristics used in those building blocks, namely pruning and quantization. We first study the fundamental limit for model compression via the rate distortion theory. We bring the rate distortion function from data compression to model compression to quantify this fundamental limit. We prove a lower bound for the rate distortion function and prove its achievability for linear models. Although this achievable compression scheme is intractable in practice, this analysis motivates a novel model compression framework. This framework provides a new objective function in model compression, which can be applied together with other classes of model compressor such as pruning or quantization. Theoretically, we prove that the proposed scheme is optimal for compressing one-hidden-layer ReLU neural networks. Empirically, we show that the proposed scheme improves upon the baseline in the compression-accuracy tradeoff.
Weihao Gao, Yu-Han Liu, Chong Wang, Sewoong Oh [pdf]
-
Fine tuning the hydrophobicity of counter‐anions to tailor pore size in porous all‐poly(ionic liquid) membranes -
Abstract
- Charged porous polymer membranes (CPMs) emerging as a multifunctional platform for diverse applications in chemistry, materials science, and biomedicine have been attracting widespread attention. Fabrication of CPMs in a controllable manner is of particular significance for optimizing their function and maximizing practical values. Herein, we report the fabrication of CPMs exclusively from poly(ionic liquid)s (PILs), and their pore size and wettability were precisely tailored by rational choice of the counteranions. Specifically, stepwise subtle increase in hydrophobicity of the counteranions by extending the length of fluorinated alkyl substituents, i.e. from bis(trifluoromethane sulfonyl)imide (Tf2N) to bis(pentafluoroethane sulfonyl)imide (Pf2N) and bis(heptafluoropropane sulfonyl)imide (Hf2N), decreases the average pore size gradually from 1546 nm to 157 nm and 77 nm, respectively. Meanwhile, their corresponding water contact angles increased from 90 degree to 102 degree and 120o. The exquisite control over the porous architectures and surface wettability of CPMs by systematic variation of the anion's hydrophobicity provides a solid proof of the impact of the PIL anions on CPMs' structure.
Zhiping Jiang, Yu-ping Liu, Yue Shao, Peng Zhao, Jiayin Yuan, Hong Wang Journal reference: polymer international, 2019, 10.1002/pi.5764 [pdf] DOI: 10.1002/pi.5764
-
Direct evaluation of the force constant matrix in quantum Monte Carlo -
Abstract
- We develop a formalism to directly evaluate the matrix of force constants within a Quantum Monte Carlo calculation. We utilize the matrix of force constants to accurately relax the positions of atoms in molecules and determine their vibrational modes, using a combination of Variational and Diffusion Monte Carlo. The computed bond lengths differ by less than 0.007{\AA} from the experimental results for all four tested molecules. For hydrogen and hydrogen chloride, we obtain fundamental vibrational frequencies within 0.1% of experimental results and ~10 times more accurate than leading computational methods. For carbon dioxide and methane, the vibrational frequency obtained is on average within 1.1% of the experimental result, which is at least 3 times closer than results using Restricted Hartree-Fock and Density Functional Theory with a Perdew-Burke-Ernzerhof (PBE) functional and comparable or better than Density Functional Theory with a semi-empirical functional.
Yu Yang Fredrik Liu, Bartholomew Andrews, Gareth J. Conduit Journal reference: J. Chem. Phys., 150(3):034104, Jan 2019 [pdf] DOI: 10.1063/1.5070138
-
Learning Pairwise Relationship for Multi-object Detection in Crowded
Scenes -
Abstract
- As the post-processing step for object detection, non-maximum suppression (GreedyNMS) is widely used in most of the detectors for many years. It is efficient and accurate for sparse scenes, but suffers an inevitable trade-off between precision and recall in crowded scenes. To overcome this drawback, we propose a Pairwise-NMS to cure GreedyNMS. Specifically, a pairwise-relationship network that is based on deep learning is learned to predict if two overlapping proposal boxes contain two objects or zero/one object, which can handle multiple overlapping objects effectively. Through neatly coupling with GreedyNMS without losing efficiency, consistent improvements have been achieved in heavily occluded datasets including MOT15, TUD-Crossing and PETS. In addition, Pairwise-NMS can be integrated into any learning based detectors (Both of Faster-RCNN and DPM detectors are tested in this paper), thus building a bridge between GreedyNMS and end-to-end learning detectors.
Yu Liu, Lingqiao Liu, Hamid Rezatofighi, Thanh-Toan Do, Qinfeng Shi, Ian Reid [pdf]
-
Anisotropic magnetic entropy change in
-
Abstract
- Intrinsic, two-dimensional (2D) ferromagnetic semiconductors are an important class of materials for spintronics applications. Cr$_2$X$_2$Te$_6$ (X = Si and Ge) semiconductors show 2D Ising-like ferromagnetism, which is preserved in few-layer devices. The maximum magnetic entropy change associated with the critical properties around the ferromagnetic transition for Cr$_2$Si$_2$Te$_6$ $-\Delta S_M^{max} \sim$ 5.05 J kg$^{-1}$ K$^{-1}$ is much larger than $-\Delta S_M^{max} \sim$ 2.64 J kg$^{-1}$ K$^{-1}$ for Cr$_2$Ge$_2$Te$_6$ with an out-of-plane field change of 5 T. The rescaled $-\Delta S_M(T,H)$ curves collapse onto a universal curve independent of temperature and field for both materials. This indicates similar critical behavior and 2D Ising magnetism, confirming the magnetocrystalline anisotropy that could preserve the long-range ferromagnetism in few-layers of Cr$_2$X$_2$Te$_6$.
Yu Liu, C. Petrovic Journal reference: Physical Review MATERIALS 3, 014001 (2019) [pdf] DOI: 10.1103/PhysRevMaterials.3.014001
-
Host Galaxies of Type Ic and Broad-lined Type Ic Supernovae from the Palomar Transient Factory: Implications for Jet Production -
Abstract
- Unlike the ordinary supernovae (SNe) some of which are hydrogen and helium deficient (called Type Ic SNe), broad-lined Type Ic SNe (SNe Ic-bl) are very energetic events, and all SNe coincident with bona fide long duration gamma-ray bursts (LGRBs) are of Type Ic-bl. Understanding the progenitors and the mechanism driving SN Ic-bl explosions vs those of their SNe Ic cousins is key to understanding the SN-GRB relationship and jet production in massive stars. Here we present the largest set of host-galaxy spectra of 28 SNe Ic and 14 SN Ic-bl, all discovered before 2013 by the same untargeted survey, namely the Palomar Transient Factory (PTF). We carefully measure their gas-phase metallicities, stellar masses (M*s) and star-formation rates (SFRs) by taking into account recent progress in the metallicity field and propagating uncertainties correctly. We further re-analyze the hosts of 10 literature SN-GRBs using the same methods and compare them to our PTF SN hosts with the goal of constraining their progenitors from their local environments by conducting a thorough statistical comparison, including upper limits. We find that the metallicities, SFRs and M*s of our PTF SN Ic-bl hosts are statistically comparable to those of SN-GRBs, but significantly lower than those of the PTF SNe Ic. The mass-metallicity relations as defined by the SNe Ic-bl and SN-GRBs are not significantly different from the same relations as defined by the SDSS galaxies, in contrast to claims by earlier works. Our findings point towards low metallicity as a crucial ingredient for SN Ic-bl and SN-GRB production since we are able to break the degeneracy between high SFR and low metallicity. We suggest that the PTF SNe Ic-bl may have produced jets that were choked inside the star or were able break out of the star as unseen low-luminosity or off-axis GRBs.
Maryam Modjaz, Federica B. Bianco, Magdalena Siwek, Shan Huang, Daniel A. Perley, David Fierroz, Yu-Qian Liu, Iair Arcavi, Avishay Gal-Yam, Nadia Blagorodnova, Bradley S. Cenko, Alexei V. Filippenko, Mansi M. Kasliwal, S. R. Kulkarni, Steve Schulze, Kirsty Taggart, Weikang Zhen [pdf] DOI: 10.3847/1538-4357/ab4185 1901.00872v1 [pdf]
-
Excited Kerr black holes with scalar hair -
Abstract
- In the context of complex scalar field coupled to Einstein gravity theory, we present a novel family of solutions of Kerr black holes with excited-state scalar hair inspired by the work of Herdeiro and Radu in [Phys.\ Rev.\ Lett.\ {\bf 112}, 221101 (2014)], which can be regarded as numerical solutions of rotating compact objects with excited scalar hair, including boson stars and black holes. In contrast to Kerr black holes with ground state scalar hair, we find that the first-excited Kerr black holes with scalar hair have two types of nodes, including radial $n_r=1$ and angular $n_\theta=1$ nodes. Moreover, in the case of radial nodes the curves of the mass versus the frequency form nontrivial loops, and in the case of angular nodes the curves can be divided into two kinds: closed and open loops. We also study the dependence of the horizon area on angular momentum and Hawking temperature.
Yong-Qiang Wang, Yu-Xiao Liu, Shao-Wen Wei Journal reference: Phys. Rev. D 99, 064036 (2019) [pdf] DOI: 10.1103/PhysRevD.99.064036
-
Matching the meson quasidistribution amplitude in the RI/MOM scheme -
Abstract
- The $x$-dependence of light-cone distribution amplitude (LCDA) can be directly calculated from a quasi distribution amplitude (DA) in lattice QCD within the framework of large-momentum effective theory (LaMET). In this paper, we study the one-loop renormalization of the quasi-DA in the regularization-independent momentum subtraction (RI/MOM) scheme. The renormalization factor for the quasi parton distribution function can be used to renormalize the quasi-DA provided that they are implemented on lattice and in perturbation theory in the same manner. We derive the one-loop matching coefficient that matches quasi-DA in the RI/MOM scheme onto LCDA in the $\overline{\rm MS}$ scheme. Our result provides the crucial step to extract the LCDAs from lattice matrix elements of quasi-DAs.
Yu-Sheng Liu, Wei Wang, Ji Xu, Qi-An Zhang, Shuai Zhao, Yong Zhao Journal reference: Phys. Rev. D 99, 094036 (2019) [pdf] DOI: 10.1103/PhysRevD.99.094036
-
Magnetic and structural properties of the iron oxychalcogenides
-
Abstract
- We present the results of structural and magnetic phase comparisons of the iron oxychalcogenides La$_{2}$O$_{2}$Fe$_{2}$O$M$$_{2}$ ($M$ = S, Se). Elastic neutron scattering reveals that $M$ = S and Se have similar nuclear structures at room and low temperatures. We find that both materials obtain antiferromagnetic ordering at a Neel temperature $T_{N}$ 90.1 $\pm$ 0.16 K and 107.2 $\pm$ 0.06 K for $M$= Se and S, respectively. The magnetic arrangements of $M$ = S, Se are obtained through Rietveld refinement. We find the order parameter exponent $\beta$ to be 0.129 $\pm$ 0.006 for $M$ = Se and 0.133 $\pm$ 0.007 for $M$ = S. Each of these values is near the Ising symmetry value of 1/8. This suggests that although lattice and electronic structural modifications result from chalcogen exchange, the nature of the magnetic interactions is similar in these materials.
B. Freelon, Z. Yamani, Ian Swainson, R. Flauca, Yu Hao Liu, L. Craco, M. S. Laad, Meng Wang, Jiaqi Chen, R. J. Birgeneau, Minghu Fang Journal reference: Phys. Rev. B 99, 024109 (2019) [pdf] DOI: 10.1103/PhysRevB.99.024109
-
Double-peak specific heat and spin freezing in the spin-2 triangular lattice antiferromagnet
-
Abstract
- We report the properties of a triangular lattice iron-chalcogenide antiferromagnet FeAl$_{2}$Se$_{4}$. The spin susceptibility reveals a significant antiferromagnetic interaction with a Curie-Weiss temperature {\Theta}$_{CW}$ ~ -200K and a spin-2 local moment. Despite a large spin and a large |{\Theta}$_{CW}$|, the low-temperature behaviors are incompatible with conventional classical magnets. No long-range order is detected down to 0.4K. Similar to the well-known spin-1 magnet NiGa$_{2}$S$_{4}$, the specific heat of FeAl$_{2}$Se$_{4}$ exhibits an unusual double-peak structure and a T$^{2}$ power law at low temperatures, which are attributed to the underlying quadrupolar spin correlations and the Halperin-Saslow modes, respectively. The spin freezing occurs at ~ 14K, below which the relaxation dynamics is probed by the ac susceptibility. Our results are consistent with the early theory for the spin-1 system with Heisenberg and biquadratic spin interactions. We argue that the early proposal of the quadrupolar correlation and gauge glass dynamics may be well extended to FeAl$_{2}$Se$_{4}$. Our results provide useful insights about the magnetic properties of frustrated quantum magnets with high spins.
Kunkun Li, Shifeng Jin, Jiangang Guo, Yanping Xu, Yixi Su, Erxi Feng, Yu Liu, Shengqiang Zhou, Tianping Ying, Shiyan Li, Ziqiang Wang, Gang Chen, Xiaolong Chen Journal reference: Phys. Rev. B 99, 054421 (2019) [pdf] DOI: 10.1103/PhysRevB.99.054421
-
Finite temperature physics of 1D topological Kondo insulator: Stable Haldane phase, emergent energy scale and beyond -
Abstract
- We have studied the one-dimensional $p$-wave periodic Anderson model at finite temperature with the help of the numerically exact determinant quantum Monte Carlo simulation. It is found that the topological Haldane phase established for ground-state is still stable against small thermal fluctuation and its characteristic edge magnetization develops at low temperature. Moreover, the saturated low-$T$ spin structure factor and the $\frac{1}{T}$-law of susceptibility are useful to detect the free edge spin moment, which may be relevant for experimental explorations. We have also comparatively studied the conventional $s$-wave periodic Anderson model, which helps us identify an emergent energy scale $T_{cr}$. $T_{cr}$ signals a crossover into interesting low-$T$ regime and seems to be the expected Ruderman-Kittel-Kasuya-Yosida (RKKY) coupling. Finally, the collective Kondo screening effect has been examined and it is heavily reduced at boundary, which may give a fruitful playground for novel physics beyond the well-established Haldane state and topological band insulators.
Yin Zhong, Yu Liu, Qin Wang, Ke Liu, Hai-Feng Song, Hong-Gang Luo Journal reference: Front. Phys. 14(2), 23602 (2019) [pdf] DOI: 10.1007/s11467-018-0868-x
-
The Sariçiçek howardite fall in Turkey: Source crater of
-
Abstract
- 2018
-
Proton Isovector Helicity Distribution on the Lattice at Physical Pion Mass -
Abstract
- We present a state-of-the-art calculation of the isovector quark helicity Bjorken-$x$ distribution in the proton using lattice-QCD ensembles at the physical pion mass. We compute quasi-distributions at proton momenta $P_z \in \{2.2, 2.6, 3.0\}$~GeV on the lattice, and match them systematically to the physical parton distribution using large-momentum effective theory (LaMET). We reach an unprecedented precision through high statistics in simulations, large-momentum proton matrix elements, and control of excited-state contamination. The resulting distribution with combined statistical and systematic errors is in agreement with the latest phenomenological analysis of the spin-dependent experimental data; in particular, $\Delta \bar{u}(x)>\Delta \bar{d}(x)$.
Huey-Wen Lin, Jiunn-Wei Chen, Xiangdong Ji, Luchang Jin, Ruizi Li, Yu-Sheng Liu, Yi-Bo Yang, Jian-Hui Zhang, Yong Zhao Journal reference: Phys.Rev.Lett. 121 (2018) no.24, 242003 [pdf] DOI: 10.1103/PhysRevLett.121.242003
-
T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction -
Abstract
- Accurate and real-time traffic forecasting plays an important role in the Intelligent Traffic System and is of great significance for urban traffic planning, traffic management, and traffic control. However, traffic forecasting has always been considered an open scientific issue, owing to the constraints of urban road network topological structure and the law of dynamic change with time, namely, spatial dependence and temporal dependence. To capture the spatial and temporal dependence simultaneously, we propose a novel neural network-based traffic forecasting method, the temporal graph convolutional network (T-GCN) model, which is in combination with the graph convolutional network (GCN) and gated recurrent unit (GRU). Specifically, the GCN is used to learn complex topological structures to capture spatial dependence and the gated recurrent unit is used to learn dynamic changes of traffic data to capture temporal dependence. Then, the T-GCN model is employed to traffic forecasting based on the urban road network. Experiments demonstrate that our T-GCN model can obtain the spatio-temporal correlation from traffic data and the predictions outperform state-of-art baselines on real-world traffic datasets. Our tensorflow implementation of the T-GCN is available at https://github.com/lehaifeng/T-GCN.
Ling Zhao, Yujiao Song, Chao Zhang, Yu Liu, Pu Wang, Tao Lin, Min Deng, Haifeng Li Journal reference: IEEE Transactions on Intelligent Transportation Systems-2019 [pdf] DOI: 10.1109/TITS.2019.2935152
-
Joint Beam and Channel Tracking for Two-Dimensional Phased Antenna
Arrays -
Abstract
- Analog beamforming is a low-cost architecture for millimeter-wave (mmWave) mobile communications. However, it has two disadvantages for serving fast mobility users: (i) the mmWave beam in the wireless channel and the beam steered by analog beamforming have small angular spreads which are difficult to align with each other and (ii) the receiver can only observe the mmWave channel in one beam direction and rely on beam-probing algorithms to check other directions. In this paper, we develop a beam probing and tracking algorithm that can efficiently track fast-moving mmWave beams in three-dimensional (3D) space. This algorithm has several salient features: (1) fading channel supportive: it can simultaneously track the channel coefficient and two-dimensional (2D) beam direction in fading channel environments; (2) low probing overhead: it achieves the minimum probing requirement for joint beam and channel tracking; (3) fast tracking speed and high tracking accuracy: its tracking error converges to the minimum Cramer-Rao lower bound (CRLB) in static scenarios in theory and it outperforms several existing tracking algorithms with lower tracking error and faster tracking speed in simulations.
Yu Liu, Jiahui Li, Yin Sun, Shidong Zhou [pdf]
-
Quantized Scalar Fields in Curved Spacetime Background of Thick Brane -
Abstract
- In this paper, we adopt the method of quantum fields in curved spacetime to quantize a free scalar matter field in the braneworld background whose warped factor is of the form that could generate P\"{o}schl-Teller potential. Then we consider the interaction between the scalar field $\phi(x)$ and a classical scalar source $\rho(x)$ with the form $\mathcal{H}_I=\sqrt{-g}\tilde{g}\rho(x)\phi(x)$. The corresponding S-matrix is given and the number of particles generated by the source is obtained. Furthermore, we get the {particle numbers} in the cases that only ground state mode of the field could be detected and both the ground and first exited states could be detected, respectively. Finally, by the particle number density we define, we show how the extra dimension makes a difference specifically by the excited modes.
Jian Wang, Yu-Xiao Liu [pdf]
-
Pyramid Network with Online Hard Example Mining for Accurate Left Atrium
Segmentation -
Abstract
- Accurately segmenting left atrium in MR volume can benefit the ablation procedure of atrial fibrillation. Traditional automated solutions often fail in relieving experts from the labor-intensive manual labeling. In this paper, we propose a deep neural network based solution for automated left atrium segmentation in gadolinium-enhanced MR volumes with promising performance. We firstly argue that, for this volumetric segmentation task, networks in 2D fashion can present great superiorities in time efficiency and segmentation accuracy than networks with 3D fashion. Considering the highly varying shape of atrium and the branchy structure of associated pulmonary veins, we propose to adopt a pyramid module to collect semantic cues in feature maps from multiple scales for fine-grained segmentation. Also, to promote our network in classifying the hard examples, we propose an Online Hard Negative Example Mining strategy to identify voxels in slices with low classification certainties and penalize the wrong predictions on them. Finally, we devise a competitive training scheme to further boost the generalization ability of networks. Extensively verified on 20 testing volumes, our proposed framework achieves an average Dice of 92.83% in segmenting the left atria and pulmonary veins.
Cheng Bian, Xin Yang, Jianqiang Ma, Shen Zheng, Yu-An Liu, Reza Nezafat, Pheng-Ann Heng, Yefeng Zheng [pdf]
-
$n$-exangulated categories -
Abstract
- For each positive integer $n$ we introduce the notion of $n$-exangulated categories as higher dimensional analogues of extriangulated categories defined by Nakaoka-Palu. We characterize which $n$-exangulated categories are $n$-exact in the sense of Jasso and which are $(n+2)$-angulated in the sense of Geiss-Keller-Oppermann. For extriangulated categories with enough projectives and injectives we introduce the notion of $n$-cluster tilting subcategories and show that under certain conditions such $n$-cluster tilting subcategories are $n$-exangulated.
Martin Herschend, Yu Liu, Hiroyuki Nakaoka [pdf]
-
U(1) gauge vector field on a codimension-2 brane -
Abstract
- In this paper, we obtain a gauge invariant effective action for a bulk massless $U(1)$ gauge vector field on a brane with codimension two by using a general Kaluza-Klein (KK) decomposition for the field. It suggests that there exist two types of scalar KK modes to keep the gauge invariance of the action for the massive vector KK modes. Both the vector and scalar KK modes can be massive. The masses of the vector KK modes $m^{(n)}$ contain two parts, $m_{1}^{(n)}$ and $m_{2}^{(n)}$, due to the existence of the two extra dimensions. The masses of the two types of scalar KK modes $m_{\phi}^{(n)}$ and $m_{\varphi}^{(n)}$ are related to the vector ones, i.e., $m_{\phi}^{(n)}=m_{1}^{(n)}$ and $m_{\varphi}^{(n)}=m_{2}^{(n)}$. Moreover, we derive two Schr\"{o}dinger-like equations for the vector KK modes, for which the effective potentials are just the functions of the warp factor.
Chun-E Fu, Yuan Zhong, Yu-Xiao Liu [pdf] DOI: 10.1007/JHEP01(2019)021 1810.02081v3 [pdf]
-
Localization of gravitino field on f(R)-thick branes -
Abstract
- In this paper, we consider the localization of a five-dimensional gravitino field on $f(R)$-thick branes. We obtain the coupled chiral equations of the Kaluza-Klein (KK) modes of gravitinos with the gauge condition $\Psi_z=0$. The chiral equations of a gravitino's KK modes are found to be almost identical to those of the Dirac fermion. However, their chiralities are exactly opposite. The chiral KK modes of gravitinos could be localized in some types of $f(R)$-thick branes on introducing a coupling term. We investigate the localization of a gravitino on three types of $f(R)$-thick branes through a Yukawa-like coupling term with background scalar fields. It has been shown that all the KK modes of gravitinos cannot be localized in the pure geometric $f(R)$-thick branes by adding a five-dimensional gravitino mass term. However, for the $f(R)$-thick branes generated by one or two background scalar fields, only the left- or right-handed zero mode could be localized in the branes, and the massive KK resonant modes are the same for both left- and right-handed gravitinos despite their opposing chiralities. All these results are consistent with those of the five-dimensional Dirac fermion except their chiralities, which may be an important sign to distinguish the gravitino field and the Dirac fermion field.
Xiang-Nan Zhou, Yun-Zhi Du, Hao Yu, Yu-Xiao Liu Journal reference: Sci.China Phys.Mech.Astron. 61 (2018) no.11, 110411 [pdf] DOI: 10.1007/s11433-018-9246-2
-
RGB-D Based Action Recognition with Light-weight 3D Convolutional
Networks -
Abstract
- Different from RGB videos, depth data in RGB-D videos provide key complementary information for tristimulus visual data which potentially could achieve accuracy improvement for action recognition. However, most of the existing action recognition models solely using RGB videos limit the performance capacity. Additionally, the state-of-the-art action recognition models, namely 3D convolutional neural networks (3D-CNNs) contain tremendous parameters suffering from computational inefficiency. In this paper, we propose a series of 3D light-weight architectures for action recognition based on RGB-D data. Compared with conventional 3D-CNN models, the proposed light-weight 3D-CNNs have considerably less parameters involving lower computation cost, while it results in favorable recognition performance. Experimental results on two public benchmark datasets show that our models can approximate or outperform the state-of-the-art approaches. Specifically, on the RGB+D-NTU (NTU) dataset, we achieve 93.2% and 97.6% for cross-subject and cross-view measurement, and on the Northwestern-UCLA Multiview Action 3D (N-UCLA) dataset, we achieve 95.5% accuracy of cross-view.
Haokui Zhang, Ying Li, Peng Wang, Yu Liu, Chunhua Shen [pdf]
-
How far from automatically interpreting deep learning -
Abstract
- In recent years, deep learning researchers have focused on how to find the interpretability behind deep learning models. However, today cognitive competence of human has not completely covered the deep learning model. In other words, there is a gap between the deep learning model and the cognitive mode. How to evaluate and shrink the cognitive gap is a very important issue. In this paper, the interpretability evaluation, the relationship between the generalization performance and the interpretability of the model and the method for improving the interpretability are concerned. A universal learning framework is put forward to solve the equilibrium problem between the two performances. The uniqueness of solution of the problem is proved and condition of unique solution is obtained. Probability upper bound of the sum of the two performances is analyzed.
Jinwei Zhao, Qizhou Wang, Yufei Wang, Xinhong Hei, Yu Liu [pdf]
-
Anomalous Hall effect in the trigonal
-
Abstract
- We report anomalous Hall effect (AHE) and transport properties of trigonal Cr$_5$Te$_8$ (tr-Cr$_5$Te$_8$) single crystals. The electrical resistivity as well as the Seebeck coefficient shows a clear kink at the paramagnetic-ferromagnetic transition of tr-Cr$_5$Te$_8$, which is also confirmed by the heat capacity measurement. The scaling behavior between anomalous Hall resistivity $\rho^A_{xy}$ and longitudinal resistivity $\rho_{xx}$ is linear below $T_c$. Further analysis suggests that the AHE in tr-Cr$_5$Te$_8$ is dominated by the skew-scattering mechanism rather than the intrinsic or extrinsic side-jump mechanism.
Yu Liu, C. Petrovic Journal reference: Physical Review B 98, 195122 (2018) [pdf] DOI: 10.1103/PhysRevB.98.195122
-
Point2Sequence: Learning the Shape Representation of 3D Point Clouds
with an Attention-based Sequence to Sequence Network -
Abstract
- Exploring contextual information in the local region is important for shape understanding and analysis. Existing studies often employ hand-crafted or explicit ways to encode contextual information of local regions. However, it is hard to capture fine-grained contextual information in hand-crafted or explicit manners, such as the correlation between different areas in a local region, which limits the discriminative ability of learned features. To resolve this issue, we propose a novel deep learning model for 3D point clouds, named Point2Sequence, to learn 3D shape features by capturing fine-grained contextual information in a novel implicit way. Point2Sequence employs a novel sequence learning model for point clouds to capture the correlations by aggregating multi-scale areas of each local region with attention. Specifically, Point2Sequence first learns the feature of each area scale in a local region. Then, it captures the correlation between area scales in the process of aggregating all area scales using a recurrent neural network (RNN) based encoder-decoder structure, where an attention mechanism is proposed to highlight the importance of different area scales. Experimental results show that Point2Sequence achieves state-of-the-art performance in shape classification and segmentation tasks.
Xinhai Liu, Zhizhong Han, Yu-Shen Liu, Matthias Zwicker [pdf]
-
Linear stability of f(R, ϕ, X) thick branes: tensor perturbations -
Abstract
- We explore thick branes in $f(R,\phi,X)$ gravity. We obtain the linear tensor perturbation equation of $f(R,\phi,X)$ branes and show that the branes are stable against the tensor perturbations under the condition of $\frac{\partial f(R,\phi,X)}{\partial R}>0$. In order to obtain thick brane solutions of the fourth-order field equations in this theory, we employ the reconstruction technique. We get exact solutions of the specific $f(R,\phi,X)$ thick brane generated by a non-canonical scalar field. It is shown that the zero mode of the graviton for the thick brane is localized under certain conditions. This implies that the four-dimensional Newtonian potential is recovered on the brane. The effects of the Kaluza-Klein modes of the graviton for the $f(R,\phi,X)$ thick brane are also discussed.
Zheng-Quan Cui, Yu-Xiao Liu, Bao-Min Gu, Li Zhao Journal reference: JHEP 11 (2018) 083 [pdf] DOI: 10.1007/JHEP11(2018)083
-
Gradient Harmonized Single-stage Detector -
Abstract
- Despite the great success of two-stage detectors, single-stage detector is still a more elegant and efficient way, yet suffers from the two well-known disharmonies during training, i.e. the huge difference in quantity between positive and negative examples as well as between easy and hard examples. In this work, we first point out that the essential effect of the two disharmonies can be summarized in term of the gradient. Further, we propose a novel gradient harmonizing mechanism (GHM) to be a hedging for the disharmonies. The philosophy behind GHM can be easily embedded into both classification loss function like cross-entropy (CE) and regression loss function like smooth-$L_1$ ($SL_1$) loss. To this end, two novel loss functions called GHM-C and GHM-R are designed to balancing the gradient flow for anchor classification and bounding box refinement, respectively. Ablation study on MS COCO demonstrates that without laborious hyper-parameter tuning, both GHM-C and GHM-R can bring substantial improvement for single-stage detector. Without any whistles and bells, our model achieves 41.6 mAP on COCO test-dev set which surpasses the state-of-the-art method, Focal Loss (FL) + $SL_1$, by 0.8.
Buyu Li, Yu Liu, Xiaogang Wang [pdf]
-
Learning to Measure Change: Fully Convolutional Siamese Metric Networks
for Scene Change Detection -
Abstract
- A critical challenge problem of scene change detection is that noisy changes generated by varying illumination, shadows and camera viewpoint make variances of a scene difficult to define and measure since the noisy changes and semantic ones are entangled. Following the intuitive idea of detecting changes by directly comparing dissimilarities between a pair of features, we propose a novel fully Convolutional siamese metric Network(CosimNet) to measure changes by customizing implicit metrics. To learn more discriminative metrics, we utilize contrastive loss to reduce the distance between the unchanged feature pairs and to enlarge the distance between the changed feature pairs. Specifically, to address the issue of large viewpoint differences, we propose Thresholded Contrastive Loss (TCL) with a more tolerant strategy to punish noisy changes. We demonstrate the effectiveness of the proposed approach with experiments on three challenging datasets: CDnet, PCD2015, and VL-CMU-CD. Our approach is robust to lots of challenging conditions, such as illumination changes, large viewpoint difference caused by camera motion and zooming. In addition, we incorporate the distance metric into the segmentation framework and validate the effectiveness through visualization of change maps and feature distribution. The source code is available at https://github.com/gmayday1997/ChangeDet.
Enqiang Guo, Xinsha Fu, Jiawei Zhu, Min Deng, Yu Liu, Qing Zhu, Haifeng Li [pdf]
-
Y^2Seq2Seq: Cross-Modal Representation Learning for 3D Shape and Text by
Joint Reconstruction and Prediction of View and Word Sequences -
Abstract
- A recent method employs 3D voxels to represent 3D shapes, but this limits the approach to low resolutions due to the computational cost caused by the cubic complexity of 3D voxels. Hence the method suffers from a lack of detailed geometry. To resolve this issue, we propose Y^2Seq2Seq, a view-based model, to learn cross-modal representations by joint reconstruction and prediction of view and word sequences. Specifically, the network architecture of Y^2Seq2Seq bridges the semantic meaning embedded in the two modalities by two coupled `Y' like sequence-to-sequence (Seq2Seq) structures. In addition, our novel hierarchical constraints further increase the discriminability of the cross-modal representations by employing more detailed discriminative information. Experimental results on cross-modal retrieval and 3D shape captioning show that Y^2Seq2Seq outperforms the state-of-the-art methods.
Zhizhong Han, Mingyang Shang, Xiyang Wang, Yu-Shen Liu, Matthias Zwicker [pdf]
-
View Inter-Prediction GAN: Unsupervised Representation Learning for 3D
Shapes by Learning Global Shape Memories to Support Local View Predictions -
Abstract
- In this paper we present a novel unsupervised representation learning approach for 3D shapes, which is an important research challenge as it avoids the manual effort required for collecting supervised data. Our method trains an RNN-based neural network architecture to solve multiple view inter-prediction tasks for each shape. Given several nearby views of a shape, we define view inter-prediction as the task of predicting the center view between the input views, and reconstructing the input views in a low-level feature space. The key idea of our approach is to implement the shape representation as a shape-specific global memory that is shared between all local view inter-predictions for each shape. Intuitively, this memory enables the system to aggregate information that is useful to better solve the view inter-prediction tasks for each shape, and to leverage the memory as a view-independent shape representation. Our approach obtains the best results using a combination of L_2 and adversarial losses for the view inter-prediction task. We show that VIP-GAN outperforms state-of-the-art methods in unsupervised 3D feature learning on three large scale 3D shape benchmarks.
Zhizhong Han, Mingyang Shang, Yu-Shen Liu, Matthias Zwicker [pdf]
-
Mobility-aware Caching Scheduling for Fog Computing in mmWave Band -
Abstract
- As an extension of cloud computing, fog computing at the edge of networks provides low latency, location awareness, and real-time interactions. At the same time, millimeter wave (mmWave) communications are able to provide directional multi-gigabit transmission rates with large available bandwidth. Based on the user mobile trajectories in a region, several activity hotspots that users pass by frequently can be obtained. By caching popular content at the edge nodes near the hotspots, users can download the cached content directly at a short distance, and the user experience can be significantly improved. Considering multiple hotspots in a region, how to efficiently schedule the transmission for the caching at edge nodes becomes a key problem. In this paper, we focus on the problem of mobility aware transmission scheduling for caching at edge nodes near hotspots, and utilize multi-hop relaying and concurrent transmissions to achieve better performance. After formulating the optimal scheduling problem as a stochastic nonlinear mixed integer program, we propose a mobility aware caching scheduling scheme, called MHRC (Multi-Hop Relaying based Caching), where multi-hop D2D paths are established for edge nodes, and concurrent transmissions are exploited in the scheduling of caching at edge nodes. Extensive performance evaluation demonstrates MHRC achieves more than 1x higher expected cached data amount compared with state-of-the-art schemes.
Yong Niu, Yu Liu, Yong Li, Zhangdui Zhong, Bo Ai, Pan Hui [pdf]
-
Probesim -
Abstract
- Single-source and top-$k$ SimRank queries are two important types of similarity search in graphs with numerous applications in web mining, social network analysis, spam detection, etc. A plethora of techniques have been proposed for these two types of queries, but very few can efficiently support similarity search over large dynamic graphs, due to either significant preprocessing time or large space overheads. This paper presents ProbeSim, an index-free algorithm for single-source and top-$k$ SimRank queries that provides a non-trivial theoretical guarantee in the absolute error of query results. ProbeSim estimates SimRank similarities without precomputing any indexing structures, and thus can naturally support real-time SimRank queries on dynamic graphs. Besides the theoretical guarantee, ProbeSim also offers satisfying practical efficiency and effectiveness due to several non-trivial optimizations. We conduct extensive experiments on a number of benchmark datasets, which demonstrate that our solutions significantly outperform the existing methods in terms of efficiency and effectiveness. Notably, our experiments include the first empirical study that evaluates the effectiveness of SimRank algorithms on graphs with billion edges, using the idea of pooling.
Yu Liu, Bolong Zheng, Xiaodong He, Zhewei Wei, Xiaokui Xiao, Kai Zheng, Jiaheng Lu [pdf] DOI: 10.14778/3151113.3151115 1709.06955v2 [pdf]
-
Describing the ADD model in a warped geometry -
Abstract
- We propose a new description of the (4+N)-dimensional Arkani-Hamed-Dimopoulos-Dvali (ADD) model in a (4+1)-dimensional warped geometry to solve the gauge hierarchy problem. It has the same KK spectrum as in the ADD model and recovers its phenomenons that do not involve the interaction among the graviton KK modes. There is no hierarchy between the fundamental length and the size of the extra dimension. An explicit realization is constructed in the nonlocal gravity theory to give a warped description of the six-dimensional ADD model. Remarkably, the equivalent number N of the extra dimensions in this description may be non-integral, which provides a new mechanism to escape the experimental constrains.
Bin Guo, Yu-Xiao Liu, Ke Yang, Xin-He Meng [pdf]
-
Fault Diagnosis and Bad Data Detection of Power Transmission Network - A
Time Domain Approach -
Abstract
- Fault analysis and bad data are often processed in separate manners. In this paper it is proved that fault as well as bad current measurement data can be modeled as control failure for the power transmission network and any fault on the transmission line can be treated as multiple bad data. Subsequently a linear observer theory is designed in order to identify the fault type and bad data simultaneously. The state space model based observer theory allows a particular failure mode manifest itself as residual which remains in a fixed direction. Moreover coordinate transformation is performed to allow the residual for each failure mode to generate specific geometry characteristic in separate output dimensions. The design approach based on the observer theory is presented in this paper. The design allows 1) bad data detection for current measurement, and 2) fault location, and fault resistance estimation (as a byproduct) where the fault location accuracy is not affected by fault resistance. However it loses freedom in designing the eigenvalues in the excessive subspace. While the theoretical framework is general, the analysis and design are dedicated to transmission lines.
Zhenyu Tan, Yu Liu, Hongbo Sun, Bai Cui [pdf]
-
Recovery of Saturated $γ$ Signal Waveforms by Artificial Neural
Networks -
Abstract
- Particle may sometimes have energy outside the range of radiation detection hardware so that the signal is saturated and useful information is lost. We have therefore investigated the possibility of using an Artificial Neural Network (ANN) to restore the saturated waveforms of $\gamma$ signals. Several ANNs were tested, namely the Back Propagation (BP), Simple Recurrent (Elman), Radical Basis Function (RBF) and Generalized Radial Basis Function (GRBF) neural networks (NNs) and compared with the fitting method based on the Marrone model. The GBRFNN was found to perform best.
Yu Liu, Jing-Jun Zhu, Neil Roberts, Ke-Ming Chen, Yu-Lu Yan, Shuang-Rong Mo, Peng Gu, Hao-Yang Xing [pdf]
-
Nucleon Transversity Distribution at the Physical Pion Mass from Lattice
QCD -
Abstract
- We report a state-of-the-art lattice calculation of the isovector quark transversity distribution of the proton at the physical pion mass. Within the framework of large-momentum effective theory (LaMET), we compute the transversity quasi-distributions using clover valence fermions on 2+1+1-flavor (up/down, strange, charm) HISQ-lattice configurations with boosted proton momenta as large as 3.0~GeV. The relevant lattice matrix elements are nonperturbatively renormalized in regularization-independent momentum-subtraction (RI/MOM) scheme and systematically matched to the physical transversity distribution. With high statistics, large proton momenta and meticulous control of excited-state contamination, we provide the best theoretical prediction for the large-$x$ isovector quark transversity distribution, with better precision than the most recent global analyses of experimental data. Our result also shows that the sea quark asymmetry in the proton transversity distribution is consistent with zero, which has been assumed in all current global analyses.
Yu-Sheng Liu, Jiunn-Wei Chen, Luchang Jin, Ruizi Li, Huey-Wen Lin, Yi-Bo Yang, Jian-Hui Zhang, Yong Zhao [pdf]
-
Braneworld in
-
Abstract
- In this paper, we investigate the braneworld scenario in $f(T)$ gravity with a $K$-field as the background field. We consider various different specific forms of $f(T)$ gravity and $K$-field, and find a general way to construct the braneworld model. Based on our solutions, the split of branes is investigated. Besides, the stability of the braneworld is studied by investigating the tensor perturbation of the vielbein.
Jian Wang, Wen-Di Guo, Zi-Chao Lin, Yu-Xiao Liu Journal reference: Phys. Rev. D 98, 084046 (2018) [pdf] DOI: 10.1103/PhysRevD.98.084046
-
Hierarchy problem and new warped extra dimension -
Abstract
- In this paper, we propose a new mechanism with warped extra dimension to solve the hierarchy problem, which is parallel to the Randall-Sundrum (RS) brane scenario. Different from the RS scenario, the fundamental scale is TeV scale and the four-dimensional Planck scale is generated from the exponential warped extra dimension at size of a few TeV$^{-1}$. The experimental consequences of this scenario are very different from that of the RS scenario. In the explicit realization in the nonlocal gravity theory, there is a tower of spin-2 excitations with mass gap $10^{-4}\text{eV}$ and they are coupled with the gravitational scale to the standard model particles. We further discuss the possible generalizations in other modified gravity theories. The experimental consequences are similar to $(4+N)$-dimensional large extra dimension but $N$ can be a non-integer, which satisfies the experimental constraints more easily than the integer large extra dimension model.
Bin Guo, Yu-Xiao Liu, Ke Yang, Shao-Wen Wei Journal reference: Phys. Rev. D 98, 085022 (2018) [pdf] DOI: 10.1103/PhysRevD.98.085022
-
Modeling granular material segregation using a combined finite element
method and advection-diffusion-segregation equation model -
Abstract
- A two-dimensional, transient, multi-scale modeling approach is presented for predicting the magnitude and rate of percolation segregation for binary mixtures of granular material in a rotating drum and conical hopper. The model utilizes finite element method simulations to determine the bulk-level granular velocity field, which is then combined with particle-level diffusion and segregation correlations using the advection-diffusion-segregation equation. The utility of this modelling approach is demonstrated by predicting segregation patterns in a rotating drum and during the discharge of conical hoppers with different geometries. The model exhibits good quantitative accuracy in predicting DEM and experimental segregation data reported in the literature for cohesionless granular materials. Moreover, since the numerical approach does not directly model individual particles, it is expected to scale well to systems of industrial scale.
Yu Liu, Marcial Gonzalez, Carl Wassgren [pdf]
-
Learning to Calibrate Quantum Control Pulses by Iterative Deconvolution -
Abstract
- In experimental control of quantum systems, the precision is often hindered by imperfect applied electronics that distort control pulses delivered to target quantum devices. To mitigate such error, the deconvolution method is commonly used for compensating the distortion via an identified convolutional model. However, its effectiveness is limited by model inaccuracies (e.g., imprecise parameters or unmodeled distortion dynamics). In this paper, we propose a learning-based scheme to eliminate the residual calibration error by repeatedly applying the deconvolution operations. The resulting iterative deconvolution method is shown to be able to correct both linear and nonlinear model errors to the highest precision allowed by available finite sampling rates. The calibration error induced by finite sampling rates is also analyzed, from which we propose that the inter-sampling error can be suppressed by actively introducing nonlinear components in the control electronics.
Xi Cao, Bing Chu, Haijin Ding, Luyan Sun, Yu-xi Liu, Rebing Wu [pdf]
-
Thermoelectric studies of
-
Abstract
- We report thermoelectric properties of Ir$_{1-x}$Rh$_x$Te$_2$ ($0 \leqslant x \leqslant 0.3$) alloy series where superconductivity at low temperatures emerges as the high-temperature structural transition ($T_s$) is suppressed. The isovalent ionic substitution of Rh into Ir has different effects on physical properties when compared to the anionic substitution of Se into Te, in which the structural transition is more stable with Se substitution. Rh substitution results in a slight reduction of lattice parameters and in an increase of number of carriers per unit cell. Weak-coupled BCS superconductivity in Ir$_{0.8}$Rh$_{0.2}$Te$_2$ that emerges at low temperature ($T_c^{zero}$ = 2.45 K) is most likely driven by electron-phonon coupling rather than dimer fluctuations mediated pairing.
Yu Liu, $^{1}$ Hechang Lei, $^{1}$ Kefeng Wang, $^{1}$ Milinda Abeykoon, $^{2}$ J. B. Warren, $^{3}$ Emil Bozin, $^{1}$, C. Petrovic$^{1}$ Journal reference: Physical Review B 98, 094519 (2018) [pdf] DOI: 10.1103/PhysRevB.98.094519
-
Magnetic and topological transitions in three-dimensional topological Kondo insulator -
Abstract
- By using an extended slave-boson method, we draw a global phase diagram summarizing both magnetic phases and paramagnetic (PM) topological insulating phases (TI$_s$) in three-dimensional topological Kondo insulator (TKI). By including electron hopping (EH) up to third neighbor, we identify four strong topological insulating (STI) phases and two weak topological insulating (WTI) phases, then the PM phase diagrams characterizing topological transitions between these TI$_s$ are depicted as functions of EH, $f$-electron energy level and hybridization constant. We also find an insulator-metal transition from a STI phase which has surface Fermi rings and spin textures in qualitative agreement to TKI candidate SmB$_6$. In weak hybridization regime, antiferromagnetic (AF) order naturally arises in the phase diagrams, and depending on how the magnetic boundary crosses the PM topological transition lines, AF phases are classified into AF topological insulator (AFTI) and non-topological AF insulator (nAFI), according to their $\mathcal{Z}_2$ indices. In two small regions of parameter space, two distinct topological transition processes between AF phases occur, leading to two types of AFTI, showing distinguishable surface dispersions around their Dirac points.
Huan Li, Zhi-Yong Wang, Xiao-Jun Zheng, Yu Liu, Yin Zhong [pdf] DOI: 10.1088/0256-307X/35/12/127501 1809.09867v1 [pdf]
-
$\mathcal{Z}_2$ classification for a novel antiferromagnetic topological insulating phase in three-dimensional topological Kondo insulator -
Abstract
- Antiferromagnetic topological insulator (AFTI) is a topological matter that breaks time-reversal symmetry. Since its proposal, explorations of AFTI in strong-correlated systems are still lacking. In this paper, we show for the first time that a novel AFTI phase can be realized in three-dimensional topological Kondo insulator (TKI). In a wide parameter region, the ground states of TKI undergo a second-order transition to antiferromagnetic insulating phases which conserve a combined symmetry of time reversal and a lattice translation, allowing us to derive a $\mathcal{Z}_2$-classification formula for these states. By calculating the $\mathcal{Z}_2$ index, the antiferromagnetic insulating states are classified into (AFTI) or non-topological antiferromagnetic insulator (nAFI) in different parameter regions. On the antiferromagnetic surfaces in AFTI, we find topologically protected gapless Dirac cones inside the bulk gap, leading to metallic Fermi rings exhibiting helical spin texture with weak spin-momentum locking. Depending on model parameters, the magnetic transitions take place either between AFTI and strong topological insulator, or between nAFI and weak topological insulator. By varying some model parameters, we find a topological transition between AFTI and nAFI, driving by closing of bulk gap. Our work may account for the pressure-induced magnetism in TKI compound SmB$_6$, and helps to explore richer AFTI phases in heavy-fermion systems as well as in other strong-correlated systems.
Huan Li, Yin Zhong, Yu Liu, Hong-Gang Luo, Hai-Feng Song Journal reference: Journal of Physics: Condensed Matter (2018) [pdf] DOI: 10.1088/1361-648X/aae17b
-
Abelian categories arising from cluster tilting subcategories II: quotient functors -
Abstract
- In this paper, we consider a kind of ideal quotient of an extriangulated category such that the ideal is the kernel of a functor from this extriangulated category to an abelian category. We study a condition when the functor is dense and full, in another word, the ideal quotient becomes abelian. Moreover, a new equivalent characterization of cluster-tilting subcategories is given by applying homological methods according to this functor. As an application, we show that in a connected 2-Calabi-Yau triangulated category B, a functorially finite, extension closed subcategory T of B is cluster tilting if and only if B/T is an abelian category.
Yu Liu, Panyue Zhou [pdf] DOI: 10.1017/prm.2019.42 1809.06597v1 [pdf]
-
Cocktails, but no party: multipath-enabled private audio -
Abstract
- We describe a private audio messaging system that uses echoes to unscramble messages at a few predetermined locations in a room. The system works by splitting the audio into short chunks and emitting them from different loudspeakers. The chunks are filtered so that as they echo around the room, they sum to noise everywhere except at a few chosen focusing spots where they exactly reproduce the intended messages. Unlike in the case of standard personal audio zones, the proposed method renders sound outside the focusing spots unintelligible. Our method essentially depends on echoes: the room acts as a mixing system such that at given points we get the desired output. Finally, we only require a modest number of loudspeakers and only a few impulse response measurements at points where the messages should be delivered. We demonstrate the effectiveness of the proposed method via objective quantitative metrics as well as informal listening experiments in a real room.
Yu-Jeh Liu, Jonah Casebeer, Ivan Dokmanić [pdf]
-
Glueball spectrum from
-
Abstract
- The lowest-lying glueballs are investigated in lattice QCD using $N_f=2$ clover Wilson fermion on anisotropic lattices. We simulate at two different and relatively heavy quark masses, corresponding to physical pion mass of $m_\pi\sim 938$ MeV and $650$ MeV. The quark mass dependence of the glueball masses have not been investigated in the present study. Only the gluonic operators built from Wilson loops are utilized in calculating the corresponding correlation functions. In the tensor channel, we obtain the ground state mass to be 2.363(39) GeV and 2.384(67) GeV at $m_\pi\sim 938$ MeV and $650$ MeV, respectively. In the pseudoscalar channel, when using the gluonic operator whose continuum limit has the form of $\epsilon_{ijk}TrB_iD_jB_k$, we obtain the ground state mass to be 2.573(55) GeV and 2.585(65) GeV at the two pion masses. These results are compatible with the corresponding results in the quenched approximation. In contrast, if we use the topological charge density as field operators for the pseudoscalar, the masses of the lowest state are much lighter (around 1GeV) and compatible with the expected masses of the flavor singlet $q\bar{q}$ meson. This indicates that the operator $\epsilon_{ijk}TrB_iD_jB_k$ and the topological charge density couple rather differently to the glueball states and $q\bar{q}$ mesons. The observation of the light flavor singlet pseudoscalar meson can be viewed as the manifestation of effects of dynamical quarks. In the scalar channel, the ground state masses extracted from the correlation functions of gluonic operators are determined to be around 1.4-1.5 GeV, which is close to the ground state masses from the correlation functions of the quark bilinear operators. In all cases, the mixing between glueballs and conventional mesons remains to be further clarified in the future.
Wei Sun, Long-Cheng Gui, Ying Chen, Ming Gong, Chuan Liu, Yu-Bin Liu, Zhaofeng Liu, Jian-Ping Ma, Jian-Bo Zhang Journal reference: Chin.Phys. C42 (2018) no.9, 093103 [pdf] DOI: 10.1088/1674-1137/42/9/093103
-
Abelian Categories Arising from Cluster Tilting Subcategories -
Abstract
- For a triangulated category T, if C is a cluster-tilting subcategory of T, then the quotient category T\C is an abelian category. Under certain conditions, the converse also holds. This is an very important result of cluster-tilting theory, due to Koenig-Zhu and Beligiannis. Now let B be a suitable extriangulated category, which is a simultaneous generalization of triangulated categories and exact categories. We introduce the notion of pre-cluster tilting subcategory C of B, which is a generalization of cluster tilting subcategory. We show that C is cluster tilting if and only if B/C is abelian.
Yu Liu, Panyue Zhou [pdf] DOI: 10.1007/s10485-019-09590-w 1809.02315v1 [pdf]
-
Critical behavior and magnetocaloric effect in
-
Abstract
- The critical properties and magnetocaloric effect of semiconducting ferrimagnet Mn$_3$Si$_2$Te$_6$ single crystals have been investigated by bulk magnetization and heat capacity around $T_c$. Critical exponents $\beta = 0.41\pm0.01$ with a critical temperature $T_c = 74.18\pm0.08$ K and $\gamma = 1.21\pm0.02$ with $T_c = 74.35\pm0.05$ K are deduced by the Kouvel-Fisher plot, whereas $\delta = 4.29\pm0.05(3.40\pm0.02)$ is obtained by a critical isotherm analysis at $T = 74(75)$ K. The magnetic exchange distance is found to decay as $J(r)\approx r^{-4.79}$, which lies between the mean-field and 3D Heisenberg models. Moreover, the magnetic entropy change $-\Delta S_M$ features a maximum at $T_c$, i.e., $-\Delta S_M^{max} \sim$ 2.53(1.67) J kg$^{-1}$ K$^{-1}$ with in-plane(out-of-plane) field change of 5 T, confirming large magnetic anisotropy. The heat capacity measurement further gives $-\Delta S_M^{max}$ $\sim$ 2.94 J kg$^{-1}$ K$^{-1}$ and the corresponding adiabatic temperature change $\Delta T_{ad}$ $\sim$ 1.14 K with out-of-plane field change of 9 T.
Yu Liu, C. Petrovic Journal reference: Physical Review B 98, 064423 (2018) [pdf] DOI: 10.1103/PhysRevB.98.064423
-
Observation of Floquet Raman Transition in a Driven Solid-State Spin System -
Abstract
- We experimentally observe Floquet Raman transitions in the weakly driven solid state spin system of nitrogen-vacancy center in diamond. The periodically driven spin system simulates a two-band Wannier-Stark ladder model, and allows us to observe coherent spin state transfer arising from Raman transition mediated by Floquet synthetic levels. It also leads to the prediction of analog photon-assisted Floquet Raman transition and dynamical localisation in a driven two-level quantum system. The demonstrated rich Floquet dynamics offers new capabilities to achieve effective Floquet coherent control of a quantum system with potential applications in various types of quantum technologies based on driven quantum dynamics. In particular, the Floquet-Raman system may be used as a quantum simulator for the physics of periodically driven systems.
Zijun Shu, Yu Liu, Qingyun Cao, Pengcheng Yang, Shaoliang Zhang, Martin B. Plenio, Fedor Jelezko, Jianming Cai Journal reference: Phys. Rev. Lett. 121, 210501 (2018) [pdf] DOI: 10.1103/PhysRevLett.121.210501
-
Modelling Irregular Spatial Patterns using Graph Convolutional Neural
Networks -
Abstract
- The understanding of geographical reality is a process of data representation and pattern discovery. Former studies mainly adopted continuous-field models to represent spatial variables and to investigate the underlying spatial continuity/heterogeneity in the regular spatial domain. In this article, we introduce a more generalized model based on graph convolutional neural networks (GCNs) that can capture the complex parameters of spatial patterns underlying graph-structured spatial data, which generally contain both Euclidean spatial information and non-Euclidean feature information. A trainable semi-supervised prediction framework is proposed to model the spatial distribution patterns of intra-urban points of interest(POI) check-ins. This work demonstrates the feasibility of GCNs in complex geographic decision problems and provides a promising tool to analyze irregular spatial data.
Di Zhu, Yu Liu [pdf]
-
Knowledge Graph Embedding with Entity Neighbors and Deep Memory Network -
Abstract
- Knowledge Graph Embedding (KGE) aims to represent entities and relations of knowledge graph in a low-dimensional continuous vector space. Recent works focus on incorporating structural knowledge with additional information, such as entity descriptions, relation paths and so on. However, common used additional information usually contains plenty of noise, which makes it hard to learn valuable representation. In this paper, we propose a new kind of additional information, called entity neighbors, which contain both semantic and topological features about given entity. We then develop a deep memory network model to encode information from neighbors. Employing a gating mechanism, representations of structure and neighbors are integrated into a joint representation. The experimental results show that our model outperforms existing KGE methods utilizing entity descriptions and achieves state-of-the-art metrics on 4 datasets.
Kai Wang, Yu Liu, Xiujuan Xu, Dan Lin [pdf]
-
Localization of five-dimensional Elko spinors with non-minimal coupling on thick branes -
Abstract
- It has been found that the zero mode of a five-dimensional Elko spinor could be localized on branes by introducing a Yukawa-type coupling between the Elko spinor and the background scalar field or the Ricci scalar. However, the Yukawa-type coupling is not appropriate for all brane models. In this paper, we explore other localization mechanism for the Elko spinor by introducing the non-minimal coupling $f(\phi)\mathfrak{L}_{Elko}$ between the five-dimensional Elko spinor and the background scalar field. We give the general expressions of the Elko zero mode and the function $f(\phi)$. Through two thick brane models and three concrete examples, we show that the Elko zero mode can be localized on the branes by this new mechanism. This provides us more possibilities of localizing the Elko zero mode.
Xiang-Nan Zhou, Yun-Zhi Du, Hua-Zhen Zhao, Yu-Xiao Liu Journal reference: Eur.Phys.J. C 78 (2018) 493 [pdf] DOI: 10.1140/epjc/s10052-018-5971-1
-
Improved Techniques for Learning to Dehaze and Beyond: A Collective
Study -
Abstract
- Here we explore two related but important tasks based on the recently released REalistic Single Image DEhazing (RESIDE) benchmark dataset: (i) single image dehazing as a low-level image restoration problem; and (ii) high-level visual understanding (e.g., object detection) of hazy images. For the first task, we investigated a variety of loss functions and show that perception-driven loss significantly improves dehazing performance. In the second task, we provide multiple solutions including using advanced modules in the dehazing-detection cascade and domain-adaptive object detectors. In both tasks, our proposed solutions significantly improve performance. GitHub repository URL is: https://github.com/guanlongzhao/dehaze
Yu Liu, Guanlong Zhao, Boyuan Gong, Yang Li, Ritu Raj, Niraj Goel, Satya Kesav, Sandeep Gottimukkala, Zhangyang Wang, Wenqi Ren, Dacheng Tao [pdf]
-
Merger estimates for rotating Kerr black holes in modified gravity -
Abstract
- In this paper, we explore the signatures of non-rotating and rotating black hole mergers in the matter-free modified gravity. First, we solve the unstable circular null orbits and the innermost stable circular timelike orbits via the geodesic motion. The characteristic quantities of these orbits are systematically analyzed by varying the black hole spin and the scalar field parameter of the gravity. Then based on it, we study the ringdown modes from the light ring/quasinormal modes correspondence. The final spins of the merged black holes are also estimated with the Buonanno-Kidder-Lehner recipe. Several black hole merging cases are investigated in detail. All these results show that the black hole mergers are closely dependent of the scalar field parameter of the gravity.
Shao-Wen Wei, Yu-Xiao Liu Journal reference: Phys. Rev. D 98, 024042 (2018) [pdf] DOI: 10.1103/PhysRevD.98.024042
-
Generalized Su-Schrieffer-Heeger model in one dimensional optomechanical
arrays -
Abstract
- We propose an implementation of a generalized Su-Schrieffer-Heeger (SSH) model based on optomechanical arrays. The topological properties of the generalized SSH model depend on the effective optomechanical interactions enhanced by strong driving optical fields. Three phases including one trivial and two distinct topological phases are found in the generalized SSH model. The phase transition can be observed by turning the strengths and phases of the effective optomechanical interactions via adjusting the external driving fields. Moreover, four types of edge states can be created in generalized SSH model of an open chain under single-particle excitation, and the dynamical behaviors of the excitation in the open chain are related to the topological properties under the periodic boundary condition. We show that the edge states can be pumped adiabatically along the optomechanical arrays by periodically modulating the amplitude and frequency of the driving fields. The generalized SSH model based on the optomechanical arrays provides us a tunable platform to engineer topological phases for photons and phonons, which may have potential applications in controlling the transport of photons and phonons.
Xun-Wei Xu, Yan-Jun Zhao, Hui Wang, Ai-Xi Chen, Yu-xi Liu [pdf]
-
Coronal EUV, QFP, and kink waves simultaneously launched during the course of jet–loop interaction -
Abstract
- We present the observations of an extreme ultraviolet (EUV) wave, a quasi-periodic fast-propagating (QFP) magnetosonic wave, and a kink wave that were simultaneously associated with the impingement of a coronal jet upon a group of coronal loops. After the interaction, the coronal loop showed obvious kink oscillation that had a period of about 428 seconds. In the meantime, a large-scale EUV wave and a QFP wave are observed on the west of the interaction position. It is interesting that the QFP wave showed refraction effect during its passing through two strong magnetic regions. The angular extent, speed, and lifetime of the EUV (QFP) wave were about 140 (40) degree, 423 (322) km/s, and 6 (26) minutes, respectively. It is measured that the period of the QFP wave was about 390 +/- 100 second. Based on the observational analysis results, we propose that the kink wave was probably excited by the interaction of the jet; the EUV was probably launched by the sudden expansion of the loop system due to the impingement of the coronal jet; and the QFP wave was possibly formed through the dispersive evolution of the disturbance caused by the jet-loop interaction.
Yuandeng Shen, Zehao Tang, Hongbo Li, Yu Liu [pdf] DOI: 10.1093/mnrasl/sly127 1807.09533v1 [pdf]
-
Combinatorial Multi-Armed Bandit with General Reward Functions -
Abstract
- In this paper, we study the stochastic combinatorial multi-armed bandit (CMAB) framework that allows a general nonlinear reward function, whose expected value may not depend only on the means of the input random variables but possibly on the entire distributions of these variables. Our framework enables a much larger class of reward functions such as the $\max()$ function and nonlinear utility functions. Existing techniques relying on accurate estimations of the means of random variables, such as the upper confidence bound (UCB) technique, do not work directly on these functions. We propose a new algorithm called stochastically dominant confidence bound (SDCB), which estimates the distributions of underlying random variables and their stochastically dominant confidence bounds. We prove that SDCB can achieve $O(\log{T})$ distribution-dependent regret and $\tilde{O}(\sqrt{T})$ distribution-independent regret, where $T$ is the time horizon. We apply our results to the $K$-MAX problem and expected utility maximization problems. In particular, for $K$-MAX, we provide the first polynomial-time approximation scheme (PTAS) for its offline problem, and give the first $\tilde{O}(\sqrt T)$ bound on the $(1-\epsilon)$-approximation regret of its online problem, for any $\epsilon>0$.
Wei Chen, Wei Hu, Fu Li, Jian Li, Yu Liu, Pinyan Lu [pdf]
-
Evidence of spin-phonon coupling in
-
Abstract
- We present the Raman scattering results on layered 2D semiconducting ferromagnetic compound CrSiTe$_3$. Four Raman active modes, predicted by symmetry, have been observed and assigned. The experimental results are supported by DFT calculations. The self-energies of the $A_g^3$ and the $E_g^3$ symmetry modes exhibit unconventional temperature evolution around 180 K. In addition, the doubly degenerate $E_g^3$ mode shows clear change of asymmetry in the same temperature region. The observed behavior is consistent with the presence of the previously reported short-range magnetic order and the strong spin-phonon coupling.
A. Milosavljević, A. Šolajić, J. Pešić, Yu Liu, C. Petrovic, N. Lazarević, Z. V. Popović Journal reference: Phys. Rev. B 98, 104306, (2018) [pdf] DOI: 10.1103/PhysRevB.98.104306
-
Cross-correlation between photons and phonons in quadratically coupled optomechanical systems -
Abstract
- We study photon, phonon statistics and the cross-correlation between photons and phonons in a quadratically coupled optomechanical system. Photon blockade, phonon blockade and strongly anticorrelated photons and phonons can be observed in the same parameter regime with the effective nonlinear coupling between the optical and mechanical modes, enhanced by a strong optical driving field. Interestingly, an optimal value of the effective nonlinear coupling strength for the photon blockade is not within the strong nonlinear coupling regime. This abnormal phenomenon results from the destructive interference between different paths for two-photon excitation in the optical mode with a moderate effective nonlinear coupling strength. Further more, we show that phonon (photon) pairs and correlated photons and phonons can be generated in the strong nonlinear coupling regime with a proper detuning between the weak mechanical driving field and mechanical mode. Our results open up a way to generate anticorrelated and correlated photons and phonons, which may have important applications in quantum information processing.
Xun-Wei Xu, Hai-Quan Shi, Ai-Xi Chen, Yu-xi Liu Journal reference: Phys. Rev. A 98, 013821 (2018) [pdf] DOI: 10.1103/PhysRevA.98.013821
-
-
Abstract
- Presented here is decryst, a software suite for structure determination from powder diffraction, which uses the direct space method, and is able to apply anti-bump constraints automatically and efficiently during the procedure of global optimisation using the crystallographic collision detection algorithm in arXiv:1708.03180. decryst employs incremental computation in its global optimisation cycles, which results in dramatic performance enhancement; it is also designed with parallel and distributed computing in mind, allowing for even better performance by simultaneous use of multiple processors. decryst is free and open source software, and can be obtained at https://gitlab.com/CasperVector/decryst/; it strives to be simple yet flexible, in the hope that the underlying techniques could be adopted in more crystallographic applications.
Yu Liu Journal reference: J. Appl. Cryst. 2018, 51(4), 1237-1243 [pdf] DOI: 10.1107/S160057671800804X
-
Mapping and Measuring Large-scale Photonic Correlation with
Single-photon Imaging -
Abstract
- Quantum correlation and its measurement are essential in exploring fundamental quantum physics problems and developing quantum enhanced technologies. Quantum correlation may be generated and manipulated in different spaces, which demands different measurement approaches corresponding to position, time, frequency and polarization of quantum particles. In addition, after early proof-of-principle demonstrations, it is of great demand to measure quantum correlation in a Hilbert space large enough for real quantum applications. When the number of modes goes up to several hundreds, it becomes economically unfeasible for single-mode addressing and also extremely challenging for processing correlation events with hardware. Here we present a general and large-scale measurement approach of Correlation on Spatially-mapped Photon-Level Image (COSPLI). The quantum correlations in other spaces are mapped into the position space and are captured by single-photon-sensitive imaging system. Synthetic methods are developed to suppress noises so that single-photon registrations can be faithfully identified in images. We eventually succeed in retrieving all the correlations with big-data technique from tens of millions of images. We demonstrate our COSPLI by measuring the joint spectrum of parametric down-conversion photons. Our approach provides an elegant way to observe the evolution results of large-scale quantum systems, representing an innovative and powerful tool added into the platform for boosting quantum information processing.
Ke Sun, Jun Gao, Ming-Ming Cao, Zhi-Qiang Jiao, Yu Liu, Zhan-Ming Li, Eilon Poem, Andreas Eckstein, Ruo-Jing Ren, Xiao-Ling Pang, Hao Tang, Ian A. Walmsley, Xian-Min Jin [pdf]
-
EUV Waves Driven by the Sudden Expansion of Transequatorial Loops Caused by Coronal Jets -
Abstract
- We present two events to study the driving mechanism of extreme-ultraviolet (EUV) waves that are not associated with coronal mass ejections (CMEs), by using high resolution observations taken by the Atmospheric Imaging Assembly (AIA) on board Solar Dynamics Observatory. Observational results indicate that the observed EUV waves were accompanied by ares and coronal jets, but without CMEs that were regarded as the driver of most EUV waves in previous studies. In the first case, it is observed that a coronal jet ejected along a transequatorial loop system at a plane-of-the-sky (POS) speed of $335 \pm 22$ km/s, in the meantime, an arc-shaped EUV wave appeared on the eastern side of the loop system. In addition, the EUV wave further interacted with another interconnecting loop system and launched a fast propagating (QFP) magnetosonic wave along the loop system, which had a period of 200 s and a speed of $388 \pm 65$ km/s, respectively. In the second case, we also observed a coronal jet ejected at a POS speed of $282 \pm 44$ km/s along a transequatorial loop system and the generation of bright EUV wave on the eastern side of the loop system. Based on the observational results, we propose that the observed EUV waves on the eastern side of the transequatorial loop systems are fast-mode magnetosonic waves, and they were driven by the sudden lateral expansion of the transequatorial loop systems due to the direct impingement of the associated coronal jets, while the QFP wave in the first case formed due to the dispersive evolution of the disturbance caused by the interaction between the EUV wave and the interconnecting coronal loops. It is noted that EUV waves driven by sudden loop expansions have shorter lifetimes than those driven by CMEs.
Yuandeng Shen, Zehao Tang, Yuhu Miao, Jiangtao Su, Yu Liu Journal reference: ApJL, 2018, 860, L8 [pdf] DOI: 10.3847/2041-8213/aac8dd
-
Zoom Out-and-In Network with Map Attention Decision for Region Proposal
and Object Detection -
Abstract
- In this paper, we propose a zoom-out-and-in network for generating object proposals. A key observation is that it is difficult to classify anchors of different sizes with the same set of features. Anchors of different sizes should be placed accordingly based on different depth within a network: smaller boxes on high-resolution layers with a smaller stride while larger boxes on low-resolution counterparts with a larger stride. Inspired by the conv/deconv structure, we fully leverage the low-level local details and high-level regional semantics from two feature map streams, which are complimentary to each other, to identify the objectness in an image. A map attention decision (MAD) unit is further proposed to aggressively search for neuron activations among two streams and attend the most contributive ones on the feature learning of the final loss. The unit serves as a decisionmaker to adaptively activate maps along certain channels with the solely purpose of optimizing the overall training loss. One advantage of MAD is that the learned weights enforced on each feature channel is predicted on-the-fly based on the input context, which is more suitable than the fixed enforcement of a convolutional kernel. Experimental results on three datasets, including PASCAL VOC 2007, ImageNet DET, MS COCO, demonstrate the effectiveness of our proposed algorithm over other state-of-the-arts, in terms of average recall (AR) for region proposal and average precision (AP) for object detection.
Hongyang Li, Yu Liu, Wanli Ouyang, Xiaogang Wang [pdf]
-
Beyond Trade-off: Accelerate FCN-based Face Detector with Higher
Accuracy -
Abstract
- Fully convolutional neural network (FCN) has been dominating the game of face detection task for a few years with its congenital capability of sliding-window-searching with shared kernels, which boiled down all the redundant calculation, and most recent state-of-the-art methods such as Faster-RCNN, SSD, YOLO and FPN use FCN as their backbone. So here comes one question: Can we find a universal strategy to further accelerate FCN with higher accuracy, so could accelerate all the recent FCN-based methods? To analyze this, we decompose the face searching space into two orthogonal directions, `scale' and `spatial'. Only a few coordinates in the space expanded by the two base vectors indicate foreground. So if FCN could ignore most of the other points, the searching space and false alarm should be significantly boiled down. Based on this philosophy, a novel method named scale estimation and spatial attention proposal ($S^2AP$) is proposed to pay attention to some specific scales and valid locations in the image pyramid. Furthermore, we adopt a masked-convolution operation based on the attention result to accelerate FCN calculation. Experiments show that FCN-based method RPN can be accelerated by about $4\times$ with the help of $S^2AP$ and masked-FCN and at the same time it can also achieve the state-of-the-art on FDDB, AFW and MALF face detection benchmarks as well.
Guanglu Song, Yu Liu, Ming Jiang, Yujie Wang, Junjie Yan, Biao Leng [pdf]
-
Thick brane in mimetic $f(T)$ gravity -
Abstract
- We apply the mimetic $f(T)$ theory into the thick brane model. We take the Lagrange multiplier formulation of the action and get the corresponding field equations of motion. Considering the mimetic field as a single-kink or a double-kink, we find solutions for different kinds of $f(T)$. Besides, we investigate the stability of the mimetic $f(T)$ brane by considering the tensor perturbations of the vielbein. Localization problem is also studied and it is shown that the four-dimensional gravity can be recovered for all the solutions. The effects of the torsion show that for the polynomial form of $f(T)$, the zero mode has a split compared with that of $f(T)=T$, but situations for the exponential form of $f(T)$ is similar to that of $f(T)=T$.
Wen-Di Guo, Yi Zhong, Ke Yang, Tao-Tao Sui, Yu-Xiao Liu [pdf]
-
Formation and eruption of a double-decker filament triggered by micro-bursts and recurrent jets in the filament channel -
Abstract
- We present the observations of a double-decker filament to study its formation, triggering, and eruption physics. It is observed that the double-decker filament was formed by splitting of an original single filament. During the splitting process, intermittent bright point bursts are observed in the filament channel, which resulted in the generation of the upper filament branch. The eruption of the newly formed double-decker filament was possibly triggered by two recurrent two-sided loop jets in the filament channel and the continuous mass unloading from the upper filament body. The interaction between the first jet and the filament directly resulted in the unstable of the lower branch and the fast rising phase of the upper branch. The second jet occurred at the same site about three hours after the first one, which further disturbed and accelerated the rising of the lower filament branch. It is interesting that the rising lower branch overtook the upper one, and then the two branches probably merged into one filament. Finally, the whole filament erupted violently and caused a large-scale coronal mass ejection, leaving behind a pair of flare ribbons and two dimming regions on the both sides of the filament channel. We think that the intermittent bursts may directly result in the rearrangement of the filament magnetic field and therefore the formation of the double-decker filament, then the recurrent jets further caused the fully eruption of the entire filament system. The study provides convincing evidence for supporting the scenario that a double-decker filament can be formed by splitting a single filament into two branches.
Zhanjun Tian, Yuandeng Shen, Yu Liu [pdf] DOI: 10.1016/j.newast.2018.05.005 1805.12314v1 [pdf]
-
Homologous Large-amplitude Nonlinear Fast-mode Magnetosonic Waves Driven by Recurrent Coronal Jets -
Abstract
- The detailed observational analysis of a homologous Extreme-ultraviolet (EUV) wave event is presented to study the driving mechanism and the physical property of the EUV waves, combining high resolution data taken by the Solar Dynamics Observatory and the Solar TErrestrial RElations Observatory. It is observed that four homologous EUV waves originated from the same active region AR11476 within about one hour, and the time separations between consecutive waves were of 8 - 20 minutes. The waves showed narrow arc-shaped wavefronts and propagated in the same direction along a large-scale transequatorial loop system at a speed of 648 - 712 km/s and a deceleration of 0.985 - 1.219 km/s2. The EUV waves were accompanied by weak flares, coronal jets, and radio type III bursts, in which the EUV waves were delayed with respect to the start times of the radio type III bursts and coronal jets about 2 - 13 and 4 - 9 minutes, respectively. Different to previous studies of homologous EUV waves, no coronal mass ejections were found in the present event. Based on the observational results and the close temporal the spatial relationship between the EUV waves and the coronal jets, for the first time, we propose that the observed homologous EUV waves were large-amplitude nonlinear fast-mode magnetosonic waves or shocks driven by the associated recurrent coronal jets, resemble the generation mechanism of a piston shock in a tube. In addition, it is found that the recurrent jets were tightly associated with the alternating flux cancellation and emergence in the eruption source region and radio type III bursts.
Yuandeng Shen, Yu Liu, Ying D. Liu, Jiangtao Su, Zehao Tang, Yuhu Miao [pdf] DOI: 10.3847/1538-4357/aac9be 1805.12303v1 [pdf]
-
Domain wall brane in a reduced Born–Infeld-f(T) theory -
Abstract
- The Born-Infeld $f(T)$ theory is reduced from the Born-Infeld determinantal gravity in Weitzenb\"ock spacetime. We investigate a braneworld scenario in this theory and obtain an analytic domain wall solution by utilizing the first-order formalism. The model is stable against the linear tensor perturbation. It is shown that the massless graviton is localized on the brane, but the continuous massive gravitons are non-localized and will generate a tiny correction with the behavior of ${1}/{(k r)^{3}}$ to the Newtonian potential. The four-dimensional teleparallel gravity is recovered as an effective infrared theory on the brane. As a physical application, we consider the (quasi-)localization property of spin-1/2 Dirac fermion in this model.
Ke Yang, Wen-Di Guo, Zi-Chao Lin, Yu-Xiao Liu Journal reference: Phys. Lett. B 782 (2018) 170-175 [pdf] DOI: 10.1016/j.physletb.2018.05.017
-
LOCALIZATIONS OF THE HEARTS OF COTORSION PAIRS -
Abstract
- In this article, we study localizations of hearts of cotorsion pairs (U,V) where U is rigid on an extriangulated category B. The hearts of such cotorsion pairs are equivalent to the functor categories over the stable category of U. Inspired by Marsh and Palu, we consider the mutation of U that induces a cotorsion pair (U',V'). Generally speaking, the hearts of (U,V) and (U',V') are not equivalent to each other, but we will give a generalized pseudo-Morita equivalence between certain localizations of their hearts.
Yu Liu [pdf] DOI: 10.1017/S0017089519000284 1705.00278v5 [pdf]
-
Anisotropic magnetocaloric effect in single crystals of
-
Abstract
- We report a systematic investigation of dc magnetization and ac susceptibility, as well as anisotropic magnetocaloric effect in bulk CrI$_3$ single crystals. A second-stage magnetic transition was observed just below the Curie temperature $T_c$, indicating a two-step magnetic ordering. The low temperature thermal demagnetization could be well fitted by the spin-wave model rather than the single-particle model, confirming its localized magnetism. The maximum magnetic entropy change $-\Delta S_M^{max} \sim 5.65$ J kg$^{-1}$ K$^{-1}$ and the corresponding adiabatic temperature change $\Delta T_{ad} \sim 2.34$ K are achieved from heat capacity analysis with the magnetic field up to 9 T. Anisotropy of $\Delta S_M(T,H)$ was further investigated by isothermal magnetization, showing that the difference of $-\Delta S_M^{max}$ between the $ab$ plane and the $c$ axis reaches a maximum value $\sim$ 1.56 J kg$^{-1}$ K$^{-1}$ with the field change of 5 T. With the scaling analysis of $\Delta S_M$, the rescaled $\Delta S_M(T,H)$ curves collapse onto a universal curve, indicating a second-order type of the magnetic transition. Furthermore, the $-\Delta S_M^{max}$ follows the power law of $H^n$ with $n = 0.64(1)$, and the relative cooling power RCP depends on $H^m$ with $m = 1.12(1)$.
Yu Liu, C. Petrovic Journal reference: Physical Review B 97, 174418 (2018) [pdf] DOI: 10.1103/PhysRevB.97.174418
-
Photon orbits and thermodynamic phase transition of
-
Abstract
- We study the relationship between the null geodesics and thermodynamic phase transition for the charged AdS black hole. In the reduced parameter space, we find that there exist non-monotonic behaviors of the photon sphere radius and the minimum impact parameter for the pressure below its critical value. The study also shows that the changes of the photon sphere radius and the minimum impact parameter can serve as order parameters for the small-large black hole phase transition. In particular, these changes have an universal exponent of $\frac{1}{2}$ near the critical point for any dimension $d$ of spacetime. These results imply that there may exist universal critical behavior of gravity near the thermodynamic critical point of the black hole system.
Shao-Wen Wei, Yu-Xiao Liu Journal reference: Phys. Rev. D 97, 104027 (2018) [pdf] DOI: 10.1103/PhysRevD.97.104027
-
Lattice Calculation of Parton Distribution Function from LaMET at
Physical Pion Mass with Large Nucleon Momentum -
Abstract
- We present a lattice-QCD calculation of the unpolarized isovector parton distribution function (PDF) using ensembles at the physical pion mass with large proton boost momenta $P_z \in \{2.2,2.6,3.0\}$~GeV within the framework of large-momentum effective theory (LaMET). In contrast to our previous physical-pion PDF result, we increase the statistics significantly, double the boost momentum, increase the investment in excited-state contamination systematics, and switch to $\gamma_t$ operator to avoid mixing with scalar matrix elements. We use four source-sink separations in our analysis to control the systematics associated with excited-state contamination. The one-loop LaMET matching corresponding to the new operator is calculated and applied to our lattice data. We detail the systematics that affect PDF calculations, providing guidelines to improve the precision of future lattice PDF calculations. We find our final parton distribution to be in reasonable agreement with the PDF provided by the latest phenomenological analysis.
Jiunn-Wei Chen, Luchang Jin, Huey-Wen Lin, Yu-Sheng Liu, Yi-Bo Yang, Jian-Hui Zhang, Yong Zhao [pdf]
-
Transferable Semi-supervised Semantic Segmentation -
Abstract
- The performance of deep learning based semantic segmentation models heavily depends on sufficient data with careful annotations. However, even the largest public datasets only provide samples with pixel-level annotations for rather limited semantic categories. Such data scarcity critically limits scalability and applicability of semantic segmentation models in real applications. In this paper, we propose a novel transferable semi-supervised semantic segmentation model that can transfer the learned segmentation knowledge from a few strong categories with pixel-level annotations to unseen weak categories with only image-level annotations, significantly broadening the applicable territory of deep segmentation models. In particular, the proposed model consists of two complementary and learnable components: a Label transfer Network (L-Net) and a Prediction transfer Network (P-Net). The L-Net learns to transfer the segmentation knowledge from strong categories to the images in the weak categories and produces coarse pixel-level semantic maps, by effectively exploiting the similar appearance shared across categories. Meanwhile, the P-Net tailors the transferred knowledge through a carefully designed adversarial learning strategy and produces refined segmentation results with better details. Integrating the L-Net and P-Net achieves 96.5% and 89.4% performance of the fully-supervised baseline using 50% and 0% categories with pixel-level annotations respectively on PASCAL VOC 2012. With such a novel transfer mechanism, our proposed model is easily generalizable to a variety of new categories, only requiring image-level annotations, and offers appealing scalability in real applications.
Huaxin Xiao, Yunchao Wei, Yu Liu, Maojun Zhang, Jiashi Feng [pdf]
-
PAD-Net: A Perception-Aided Single Image Dehazing Network -
Abstract
- In this work, we investigate the possibility of replacing the $\ell_2$ loss with perceptually derived loss functions (SSIM, MS-SSIM, etc.) in training an end-to-end dehazing neural network. Objective experimental results suggest that by merely changing the loss function we can obtain significantly higher PSNR and SSIM scores on the SOTS set in the RESIDE dataset, compared with a state-of-the-art end-to-end dehazing neural network (AOD-Net) that uses the $\ell_2$ loss. The best PSNR we obtained was 23.50 (4.2% relative improvement), and the best SSIM we obtained was 0.8747 (2.3% relative improvement.)
Yu Liu, Guanlong Zhao [pdf]
-
Polaronic transport and thermoelectricity in
-
Abstract
- We report a study of Co-doped berthierite Fe$_{1-x}$Co$_x$Sb$_2$S$_4$ ($x$ = 0, 0.1, and 0.2). The alloy series of Fe$_{1-x}$Co$_x$Sb$_2$S$_4$ crystallize in an orthorhombic structure with the Pnma space group, similar to FeSb$_2$, and show semiconducting behavior. The large discrepancy between activation energy for conductivity, $E_\rho$ (146 $\sim$ 270 meV), and thermopower, $E_S$ (47 $\sim$ 108 meV), indicates the polaronic transport mechanism. Bulk magnetization and heat capacity measurements of pure FeSb$_2$S$_4$ ($x$ = 0) exhibit a broad antiferromagnetic (AFM) transition ($T_N$ = 46 K) followed by an additional weak transition ($T^*$ = 50 K). Transition temperatures ($T_N$ and $T^*$) slightly decrease with increasing Co content $x$. This is also reflected in the thermal conductivity measurement, indicating strong spin-lattice coupling. Fe$_{1-x}$Co$_x$Sb$_2$S$_4$ shows relatively high value of thermopower (up to $\sim$ 624 $\mu$V K$^{-1}$ at 300 K) and thermal conductivity much lower when compared to FeSb$_{2}$, a feature desired for potential applications based on FeSb$_{2}$ materials.
Yu Liu, Chang-Jong Kang, Eli Stavitski, Qianheng Du, Klaus Attenkofer, G. Kotliar, C. Petrovic Journal reference: Physical Review B 97, 155202 (2018) [pdf] DOI: 10.1103/PhysRevB.97.155202
-
Anomalous Hall effect in the van der Waals bonded ferromagnet
-
Abstract
- We report anomalous Hall effect (AHE) in single crystals of quasi-two-dimensional Fe$_{3-x}$GeTe$_2$ ($x \approx 0.36$) ferromagnet grown by the flux method which induces defects on Fe site and bad metallic resistivity. Fe K-edge x-ray absorption spectroscopy was measured to provide information on local atomic environment in such crystals. The dc and ac magnetic susceptibility measurements indicate a second-stage transition below 119 K in addition to the paramagnetic to ferromagnetic transition at 153 K. A linear scaling behavior between the modified anomalous Hall resistivity $\rho_{xy}/\mu_0H_{eff}$ and longitudinal resistivity $\rho_{xx}^2M/\mu_0H_{eff}$ implies that the AHE in Fe$_{3-x}$GeTe$_2$ should be dominated by the intrinsic Karplus-Luttinger mechanism rather than the extrinsic skew-scattering and side-jump mechanisms. The observed deviation in the linear-M Hall conductivity $\sigma_{xy}^A$ below 30 K is in line with its transport characteristic at low temperatures, implying the scattering of conduction electrons due to magnetic disorder and the evolution of the Fermi surface induced by possible spin-reorientation transition.
Yu Liu, Eli Stavitski, Klaus Attenkofer, C. Petrovic Journal reference: Physical Review B 97, 165415 (2018) [pdf] DOI: 10.1103/PhysRevB.97.165415
-
Exploring Disentangled Feature Representation Beyond Face Identification -
Abstract
- This paper proposes learning disentangled but complementary face features with minimal supervision by face identification. Specifically, we construct an identity Distilling and Dispelling Autoencoder (D2AE) framework that adversarially learns the identity-distilled features for identity verification and the identity-dispelled features to fool the verification system. Thanks to the design of two-stream cues, the learned disentangled features represent not only the identity or attribute but the complete input image. Comprehensive evaluations further demonstrate that the proposed features not only maintain state-of-the-art identity verification performance on LFW, but also acquire competitive discriminative power for face attribute recognition on CelebA and LFWA. Moreover, the proposed system is ready to semantically control the face generation/editing based on various identities and attributes in an unsupervised manner.
Yu Liu, Fangyin Wei, Jing Shao, Lu Sheng, Junjie Yan, Xiaogang Wang [pdf]
-
Synthesizing exceptional points with three resonators -
Abstract
- In non-Hermitian coulped-resonator networks, the eigenvectors of degenerate eigenmodes may become parallel due to the singularity at so-called Exceptional Points (EP). To exploit the parametric sensitivity at EPs, an important problem is, given an arbitrary set of coupled resonators, how to generate a desired EP by properly coupling them together. This paper provides the solution for the case of three resonators. We show that all physically admissible EPs can be realized with either weakly coupled linear networks or strongly coupled circular networks, and the latter type of EPs has not been reported in the literature. Each admissible EP eigenvalue can be realized by two and only two resonator networks, and the formulas for calculating the required coupling constants are provided. The characteristics of these EPs are illustrated by the change of transmission spectra near them, which verify the enhanced sensitivity induced by the singularity of EPs.
Re-Bing Wu, Yu Zheng, Qi-Ming Chen, Yu-xi Liu Journal reference: Phys. Rev. A 98, 033817 (2018) [pdf] DOI: 10.1103/PhysRevA.98.033817
-
Kinks in higher derivative scalar field theory -
Abstract
- We study static kink configurations in a type of two-dimensional higher derivative scalar field theory whose Lagrangian contains second-order derivative terms of the field. The linear fluctuation around arbitrary static kink solutions is analyzed. We find that, the linear spectrum can be described by a supersymmetric quantum mechanics problem, and the criteria for stable static solutions can be given analytically. We also construct a superpotential formalism for finding analytical static kink solutions. Using this formalism we first reproduce some existed solutions and then offer a new solution. The properties of our solution is studied and compared without those preexisted. We also show the possibility in constructing twinlike model in the higher derivative theory, and give the consistency conditions for twinlike models corresponding to the canonical scalar field theory.
Yuan Zhong, Rong-Zhen Guo, Chun-E Fu, Yu-Xiao Liu Journal reference: Phys. Lett. B 782 (2018) 346-352 [pdf] DOI: 10.1016/j.physletb.2018.05.048
-
Field effect enhancement in buffered quantum nanowire networks -
Abstract
- III-V semiconductor nanowires have shown great potential in various quantum transport experiments. However, realizing a scalable high-quality nanowire-based platform that could lead to quantum information applications has been challenging. Here, we study the potential of selective area growth by molecular beam epitaxy of InAs nanowire networks grown on GaAs-based buffer layers. The buffered geometry allows for substantial elastic strain relaxation and a strong enhancement of field effect mobility. We show that the networks possess strong spin-orbit interaction and long phase coherence lengths with a temperature dependence indicating ballistic transport. With these findings, and the compatibility of the growth method with hybrid epitaxy, we conclude that the material platform fulfills the requirements for a wide range of quantum experiments and applications.
Filip Krizek, Joachim E. Sestoft, Pavel Aseev, Sara Marti-Sanchez, Saulius Vaitiekenas, Lucas Casparis, Sabbir A. Khan, Yu Liu, Tomas Stankevic, Alexander M. Whiticar, Alexandra Fursina, Frenk Boekhout, Rene Koops, Emanuele Uccelli, Leo P. Kouwenhoven, Charles M. Marcus, Jordi Arbiol, Peter Krogstrup Journal reference: Phys. Rev. Materials 2, 093401 (2018) [pdf] DOI: 10.1103/PhysRevMaterials.2.093401
-
Modeling granular material blending in a rotating drum using a finite
element method and advection-diffusion equation multi-scale model -
Abstract
- A multi-scale model is presented for predicting the magnitude and rate of powder blending in a rotating drum blender. The model combines particle diffusion coefficient correlations from the literature with advective flow field information from blender finite element method simulations. The multi-scale model predictions for overall mixing and local concentration variance closely match results from discrete element method (DEM) simulations for a rotating drum, but take only hours to compute as opposed to taking days of computation time for the DEM simulations. Parametric studies were performed using the multi-scale model to investigate the influence of various parameters on mixing behavior. The multi-scale model is expected to be more amenable to predicting mixing in complex geometries and scale more efficiently to industrial-scale blenders than DEM simulations or analytical solutions.
Yu Liu, Marcial Gonzalez, Carl Wassgren [pdf]
-
Stable Palatini
-
Abstract
- We consider the static domain wall braneworld scenario constructed from the Palatini formalism $f(\mathcal{R})$ theory. We check the self-consistency under scalar perturbations. By using the scalar-tensor formalism we avoid dealing with the higher-order equations. We develop the techniques to deal with the coupled system. We show that under some conditions, the scalar perturbation simply oscillates with time, which guarantees the stability. We also discuss the localization condition of the scalar mode by analyzing the effective potential and the fifth dimensional profile of the scalar mode. We apply these results to an explicit example, and show that only some of the solutions allow for stable scalar perturbations. These stable solutions also give nonlocalizable massless mode. This is important for reproducing a viable four-dimensional gravity.
Bao-Min Gu, Yu-Xiao Liu, Yuan Zhong Journal reference: Phys. Rev. D 98, 024027 (2018) [pdf] DOI: 10.1103/PhysRevD.98.024027
-
Tuning the coupling between superconducting resonators with collective qubits -
Abstract
- By simultaneously coupling multiple two-level artificial atoms to two superconducting resonators, we design a quantum switch that tunes the resonator-resonator coupling strength from zero to a large value proportional to the number of qubits. This process is implemented by engineering the qubits into different subradiant states, where the microwave photons decay from different qubits destructively interfere with each other such that the resonator-resonator coupling strength keeps stable in an open environment. Based on a three-step control scheme, we switch the coupling strength among different values within nanoseconds without changing the transition frequency of the qubits. We also apply the quantum switch to a network of superconducting resonators, and demonstrate its potential applications in quantum simulation and quantum information storage and processing.
Qi-Ming Chen, Re-Bing Wu, Luyan Sun, Yu-xi Liu Journal reference: Phys. Rev. A 98, 042328 (2018) [pdf] DOI: 10.1103/PhysRevA.98.042328
-
Mechanically modulated emission spectra and blockade of polaritons in a hybrid semiconductor-optomechanical system -
Abstract
- We study a hybrid semiconductor-optomechanical system, which consists of a cavity with an oscillating mirror made by semiconducting materials or with a semiconducting membrane inside. The cavity photons and the excitons in the oscillating mirror or semiconducting membrane form into polaritons. And correspondingly, the optomechanical interaction between the cavity photons and the mirror or membrane is changed into the polariton-mechanical interaction. We theoretically study the eigenenergies and eigenfunctions of this tripartite hybrid system with the generalized rotating-wave approximation. We show that the emission spectrum of polariton mode is modulated by the mechanical resonator. We also study the mechanical effect on the statistical properties of the polariton when the cavity is driven by a weak classical field. This work provides a detailed description of the rich nonlinearity owing to the competition between parametric coupling and three-wave mixing interaction concerning the polariton modes and the phonon mode. It also offers a way to operate the photons, phonons and excitons, e.g., detect the properties of mechanical resonator through the fine spectra of the polaritons or control the transmission of light in the integrated semiconducting-optomechanical platform.
Sai-Nan Huai, Yu-Long Liu, Yunbo Zhang, Yu-xi Liu Journal reference: Phys. Rev. A 98, 033825 (2018) [pdf] DOI: 10.1103/PhysRevA.98.033825
-
Three-dimensional magnetic critical behavior in
-
Abstract
- CrI$_3$ is a promising candidate for the van der Waals bonded ferromagnetic devices since its ferromagnetism can be maintained upon exfoliating of bulk crystals down to single layer. In this work we studied critical properties of bulk CrI$_3$ single crystals around the paramagnetic to ferromagnetic phase transition. Critical exponents $\beta$ = 0.260(4) with a critical temperature $T_c$ = 60.05(13) K and $\gamma$ = 1.136(6) with $T_c$ = 60.43(4) K are obtained by the Kouvel-Fisher method, whereas $\delta$ = 5.32(2) is obtained by a critical isotherm analysis at $T_c$ = 60 K. The critical exponents determined in bulk CrI$_3$ single crystals suggest a three-dimensional long-range magnetic coupling with the exchange distance decaying as $J(r)\approx r^{-4.69}$.
Yu Liu, C. Petrovic Journal reference: Physical Review B 97, 014420 (2018) [pdf] DOI: 10.1103/PhysRevB.97.014420
-
Observation of unusual optical band structure of CH3NH3PbI3 perovskite
single crystal -
Abstract
- Extensive efforts have been undertaken on the photoelectric physics of hybrid organolead halide perovskites to unveil the reason for the attractive photovoltaic performance. Yet, the resulting evidences are far from being fully conclusive. Herein, we provide another direct support for this issue. In addition to the observation on the conventional band edge at 1.58 eV that presents a blueshift toward temperature increase, interestingly, we also observe an unusual optical band edge at 1.48 eV in CH3NH3PbI3 perovskite single crystals. Contrary to the conventional band edge, this one shows an obvious redshift toward the enhancement in temperature, in agreement with the Varshni relation. More interestingly, the unusual band edge exhibits a series of obvious absorption and photocurrent signals, but the according photoluminescence signals are not observable. This indicates that this band edge is particularly beneficial for the photovoltaic effect due to the inhibited radiative recombination. The kinetics on photo-involved charge transition and transfer are investigated using the pump-probe photoconductivity technique, and a changeable band structure model was proposed.
Wei Huang, Shizhong Yue, Yu Liu, Laipan Zhu, Peng Jin, Qing Wu, Yang Zhang, Yanan Chen, Kong Liu, Ping Liang, Shengchun Qu, Zhijie Wang, Yonghai Chen [pdf]
-
Dispersively formed quasi-periodic fast magnetosonic wavefronts due to the eruption of a nearby mini-filament -
Abstract
- The observational analysis is performed to study the excitation mechanism and the propagation properties of a quasi-periodic fast-propagating (QFP) magnetosonic wave. The QFP wave was associated with the eruption of a nearby mini-filament and a small B4 GOES flare, which may indicate that the generation of a QFP wave do not need too much flare energy. The propagation of the QFP wave was along a bundle of funnel-shaped open loops with a speed of about 1100+/-78, and an acceleration of -2.2+/-1.1. Periodicity analysis indicates that the periods of the QFP wave are 43+/-6, 79+/-18 second. For the first time, we find that the periods of the QFP wave and the accompanying flare are inconsistent, which is different from the findings as reported in previous studies. We propose that the present QFP wave was possibly caused by the mechanism of dispersive evolution of an initially broadband disturbance resulted from the nearby mini-filament eruption.
Yuandeng Shen, Tengfei Song, Yu Liu [pdf] DOI: 10.1093/mnrasl/sly044 1803.01125v1 [pdf]
-
Absence of Dirac states in
-
Abstract
- We report magnetotransport properties of BaZnBi$_{2}$ single crystals. Whereas electronic structure features Dirac states, such states are removed from the Fermi level by spin-orbit coupling (SOC) and consequently electronic transport is dominated by the small hole and electron pockets. Our results are consistent with three dimensional (3D) but also with quasi two dimensional (2D) portions of the Fermi surface. The spin-orbit coupling-induced gap in Dirac states is much larger when compared to isostructural SrMnBi$_{2}$. This suggests that not only long range magnetic order but also mass of the alkaline earth atoms A in ABX$_{2}$ (A = alkaine earth, B = transition metal and X=Bi/Sb) are important for the presence of low-energy states obeying the relativistic Dirac equation at the Fermi surface
Weijun Ren, Aifeng Wang, D. Graf, Yu Liu, Zhidong Zhang, Wei-Guo Yin, C. Petrovic Journal reference: Phys. Rev. B 97, 035147 (2018) [pdf] DOI: 10.1103/PhysRevB.97.035147
-
Electromagnetically Induced Transparency in Circuit Quantum Electrodynamics with Nested Polariton States -
Abstract
- Electromagnetically induced transparency (EIT) is a signature of quantum interference in an atomic three-level system. By driving the dressed cavity-qubit states of a two-dimensional circuit QED system, we generate a set of polariton states in the nesting regime. The lowest three energy levels are utilized to form the $\Lambda$-type system. EIT is observed and verified by Akaike's information criterion based testing. Negative group velocities up to $-0.52\pm0.09$ km/s are obtained based on the dispersion relation in the EIT transmission spectrum.
Junling Long, H. S. Ku, Xian Wu, Xiu Gu, Russell E. Lake, Mustafa Bal, Yu-xi Liu, David P. Pappas Journal reference: Phys. Rev. Lett. 120, 083602 (2018) [pdf] DOI: 10.1103/PhysRevLett.120.083602
-
Stability of braneworlds with non-minimally coupled multi-scalar fields -
Abstract
- Linear stability of braneworld models constructed with multi-scalar fields is very different from that of single-scalar field models. It is well known that both the tensor and scalar perturbation equations of the later can always be written as a supersymmetric Schr\"{o}dinger equation, so it can be shown that the perturbations are stable at linear level. However, in general it is not true for multi-scalar field models and especially there is no effective method to deal with the stability problem of the scalar perturbations for braneworld models constructed with non-minimally coupled multi-scalar fields. In this paper we present a method to investigate the stability of such braneworld models. It is easy to find that the tensor perturbations are stable. For the stability problem of the scalar perturbations, we present a systematic covariant approach. The covariant quadratic order action and the corresponding first-order perturbed equations are derived. By introducing the orthonormal bases in field space and making the Kaluza-Klein decomposition, we show that the Kaluza-Klein modes of the scalar perturbations satisfy a set of coupled Schr\"{o}dinger-like equations, with which the stability of the scalar perturbations and localization of the scalar zero modes can be analyzed according to nodal theorem. The result depends on the explicit models. For superpotential derived barane models, the scalar perturbations are stable, but there exist normalizable scalar zero modes, which will result in unaccepted fifth force on the brane. We also use this method to analyze the $f(R)$ braneworld model with an explicit solution and find that the scalar perturbations are stable and the scalar zero modes can not be localized on the brane, which ensure that there is no extra long-range force and the Newtonian potential on the brane can be recovered.
Feng-Wei Chen, Bao-Min Gu, Yu-Xiao Liu Journal reference: Eur.Phys.J. C78 (2018) 131 [pdf] DOI: 10.1140/epjc/s10052-018-5613-7
-
Colour Confinement: a Dynamical Phenomenon of QCD -
Abstract
- We study in this Letter the origin of the confinement in QCD by analyzing the colour charge of physics states. We derive the colour charge operator in QCD and compare it with the electromagnetic charge operator in QED. It shows that the two charges have very similar structure, but the dynamical properties of the gauge fields are different. The difference between the behaviours of the gauge boson propagator at zero momentum for QCD and that for QED guarantees that there occurs colour confinement in QCD but there is no confinement in QED. We give then a universal relation between the confinement and the dynamical property of QCD and reveals the origin of the colour confinement, which can be demonstrated as the dynamical effect of QCD or more explicitly the dynamical mass generation of the gluon.
Fei Gao, Chong-yao Chen, Yu-xin Liu [pdf]
-
Recurrent Scale Approximation for Object Detection in CNN -
Abstract
- Since convolutional neural network (CNN) lacks an inherent mechanism to handle large scale variations, we always need to compute feature maps multiple times for multi-scale object detection, which has the bottleneck of computational cost in practice. To address this, we devise a recurrent scale approximation (RSA) to compute feature map once only, and only through this map can we approximate the rest maps on other levels. At the core of RSA is the recursive rolling out mechanism: given an initial map at a particular scale, it generates the prediction at a smaller scale that is half the size of input. To further increase efficiency and accuracy, we (a): design a scale-forecast network to globally predict potential scales in the image since there is no need to compute maps on all levels of the pyramid. (b): propose a landmark retracing network (LRN) to trace back locations of the regressed landmarks and generate a confidence score for each landmark; LRN can effectively alleviate false positives caused by the accumulated error in RSA. The whole system can be trained end-to-end in a unified CNN framework. Experiments demonstrate that our proposed algorithm is superior against state-of-the-art methods on face detection benchmarks and achieves comparable results for generic proposal generation. The source code of RSA is available at github.com/sciencefans/RSA-for-object-detection.
Yu Liu, Hongyang Li, Junjie Yan, Fangyin Wei, Xiaogang Wang, Xiaoou Tang [pdf]
-
ZOOpt: Toolbox for Derivative-Free Optimization -
Abstract
- Recent advances of derivative-free optimization allow efficient approximating the global optimal solutions of sophisticated functions, such as functions with many local optima, non-differentiable and non-continuous functions. This article describes the ZOOpt (https://github.com/eyounx/ZOOpt) toolbox that provides efficient derivative-free solvers and are designed easy to use. ZOOpt provides a Python package for single-thread optimization, and a light-weighted distributed version with the help of the Julia language for Python described functions. ZOOpt toolbox particularly focuses on optimization problems in machine learning, addressing high-dimensional, noisy, and large-scale problems. The toolbox is being maintained toward ready-to-use tool in real-world machine learning tasks.
Yu-Ren Liu, Yi-Qi Hu, Hong Qian, Yang Yu, Chao Qian [pdf]
-
Mathematical modeling reveals spontaneous emergence of self-replication in chemical reaction systems -
Abstract
- Explaining the origin of life requires us to explain how self-replication arises. To be specific, how can a self-replicating entity develop spontaneously from a chemical reaction system in which no reaction is self-replicating? Previously proposed mathematical models either supply an explicit framework for a minimal living system or only consider catalyzed reactions, and thus fail to provide a comprehensive theory. We set up a general model for chemical reaction systems that properly accounts for energetics, kinetics and the conservation law. We find that (1) some systems are collectively-catalytic where reactants are transformed into end products with the assistance of intermediates (as in the citric acid cycle), while some others are self-replicating where different parts replicate each other and the system self-replicates as a whole (as in the formose reaction); (2) many alternative chemical universes often contain one or more such systems; (3) it is possible to construct a self-replicating system where the entropy of some parts spontaneously decreases, in a manner similar to that discussed by Schr\"odinger; (4) complex self-replicating molecules can emerge spontaneously and relatively easily from simple chemical reaction systems through a sequence of transitions. Together these results start to explain the origins of prebiotic evolution.
Yu Liu, David Sumpter Journal reference: Journal of Biological Chemistry, 293 (49): 18854-18863, 2018 [pdf] DOI: 10.1074/jbc.RA118.003795
-
The artificial ecosystem: number soup (part II) -
Abstract
- This paper is a follow-up work about the artificial ecosystem model: number soup (Liu and Sumpter, J. Royal Soc. Interface, 2017). It elaborates more details about this model and points out future directions.
Yu Liu [pdf]
-
Vacuum-induced Autler-Townes splitting in a superconducting artificial atom -
Abstract
- We experimentally study a vacuum-induced Autler-Townes doublet in a superconducting three-level artificial atom strongly coupled to a coplanar waveguide resonator and simultaneously to a transmission line. The Autler-Townes splitting is observed in the reflection spectrum from the three-level atom in a transition between the ground state and the second excited state when the transition between the two excited states is resonant with a resonator. By applying a driving field to the resonator, we observe a change in the regime of the Autler-Townes splitting from quantum (vacuum-induced) to classical (with many resonator photons). Furthermore, we show that the reflection of propagating microwaves in a transmission line could be controlled by different frequency single photons in a resonator.
Z. H. Peng, J. H. Ding, Y. Zhou, L. L. Ying, Z. Wang, L. Zhou, L. M. Kuang, Yu-xi Liu, O. Astafiev, J. S. Tsai Journal reference: Phys. Rev. A 97, 063809 (2018) [pdf] DOI: 10.1103/PhysRevA.97.063809
-
Scalar particle production in a simple Horndeski theory -
Abstract
- The scalar particle production through a scalar field non-minimally coupled with geometry is investigated in the context of a spatially homogeneous and isotropic universe. In this paper, in order to study the evolution of particle production over time in the case of analytical solutions, we focus on a simple Horndeski theory. We first suppose that the universe is dominated by a scalar field and derive the energy conservation condition. Then from the thermodynamic point of view, the macroscopic non-conservation of the scalar field energy-momentum tensor can be explained as an irreversible production of the scalar particles. Based on the explanation, we obtain a scalar particle production rate and the corresponding entropy. Finally, since the universe, in general, could be regarded as a closed system satisfying the laws of thermodynamics, we naturally impose some thermodynamic constraints on it. The thermodynamic properties of the universe can provide additional constraints on the simple Horndeski theory.
Hao Yu, Wen-Di Guo, Ke Yang, Yu-Xiao Liu Journal reference: Phys. Rev. D 97, 083524 (2018) [pdf] DOI: 10.1103/PhysRevD.97.083524
-
Applicability of Kerker preconditioning scheme to the self-consistent density functional theory calculations of inhomogeneous systems -
Abstract
- Kerker preconditioner, based on the dielectric function of homogeneous electron gas, is designed to accelerate the self-consistent field (SCF) iteration in the density functional theory (DFT) calculations. However, question still remains regarding its applicability to the inhomogeneous systems. In this paper, we develop a modified Kerker preconditioning scheme which captures the long-range screening behavior of inhomogeneous systems thus improve the SCF convergence. The effectiveness and efficiency is shown by the tests on long-z slabs of metals, insulators and metal-insulator contacts. For situations without a priori knowledge of the system, we design the a posteriori indicator to monitor if the preconditioner has suppressed charge sloshing during the iterations. Based on the a posteriori indicator, we demonstrate two schemes of the self-adaptive configuration for the SCF iteration.
Yuzhi Zhou, Han Wang, Yu Liu, Xingyu Gao, Haifeng Song Journal reference: Phys. Rev. E 97, 033305 (2018) [pdf] DOI: 10.1103/PhysRevE.97.033305
-
Revisiting the equation of state of hybrid stars in the Dyson-Schwinger equation approach to QCD -
Abstract
- We investigate the equation of state(EoS) and the effect of the hadron-quark phase transition of strong interaction matter in compact stars. The hadron matter is described with the relativistic mean field theory,and the quark matter is described with the Dyson-Schwinger equation approach of QCD. The complete EoS of the hybrid star matter is constructed with not only the Gibbs construction but also the 3-window interpolation. The mass-radius relation of hybrid stars is also investigated. We find that, although the EoSs of both the hadron matter with hyperon and $\Delta$-baryon and the quark matter are generally softer than that of the nucleon matter, the 3-window interpolation construction may provide an EoS stiff enough for a hybrid star with mass exceeding 2$M_{\odot}^{}$ and, in turn, solve the so called "hyperon puzzle".
Zhan Bai, Huan Chen, Yu-xin Liu Journal reference: Phys. Rev. D 97, 023018 (2018) [pdf] DOI: 10.1103/PhysRevD.97.023018
-
Thick branes with inner structure in mimetic gravity -
Abstract
- In this paper, thick branes generated by mimetic scalar field are investigated. Three typical thick brane models are constructed and the linear tensor and scalar perturbations are analyzed. These branes have different inner structures, some of which are absent in general relativity. For each brane model, the solution is stable under both tensor and scalar perturbations. The tensor zero modes are localized on the branes, while the scalar perturbations do not propagate and they are not localized on the brane. As the branes split into multi sub-branes for specific parameters, the potentials of the tensor perturbations also split into multi-wells, and this may lead to new phenomenon in the resonance of the tensor perturbation and the localization of matter fields.
Yi Zhong, Yuan Zhong, Yu-Peng Zhang, Yu-Xiao Liu Journal reference: Eur.Phys.J. C78 (2018) 45 [pdf] DOI: 10.1140/epjc/s10052-018-5527-4
-
Innermost stable circular orbit of spinning particle in charged spinning black hole background -
Abstract
- In this paper we investigate the innermost stable circular orbit (ISCO) for a classical spinning test particle in the background of Kerr-Newman black hole. It is shown that the orbit of the spinning particle is related to the spin of the test particle. The motion of the spinning test particle will be superluminal if its spin is too large. We give an additional condition by considering the superluminal constraint for the ISCO in the black hole backgrounds. We obtain numerically the relations between the ISCO and the properties of the black holes and the test particle. It is found that the radius of the ISCO for a spinning test particle is smaller than that of a non-spinning test particle in the black hole backgrounds.
Yu-Peng Zhang, Shao-Wen Wei, Wen-Di Guo, Tao-Tao Sui, Yu-Xiao Liu Journal reference: Phys. Rev. D 97, 084056 (2018) [pdf] DOI: 10.1103/PhysRevD.97.084056
-
Localization of gravitino field on branes -
Abstract
- In this paper, we investigate the localization of a bulk gravitino field on the scalar-tensor branes and compare the result with that in the Randall-Sundrum-1 (RS1) model. The coupled chiral equations for the Kaluza-Klein (KK) modes of the gravitino field are obtained by fixing the gauge $\Psi_5=0$ and using the chiral KK decompositions. It is shown that, in the RS1 model for the left- and right-handed zero modes of the gravitino field, only one of them can be localized near one brane. For the massive modes, both chiral modes survive and the lower KK modes are localized near the IR brane from the four-dimensional physical coordinate point of view. However, for the scalar-tensor brane model, the localization of the gravitino chiral zero modes depends on the coupling parameter $\lambda$, and they will be not localized around anyone brane within a certain range of the parameter $\lambda$, which is quite different from the RS1 model. Furthermore, we also give the corresponding mass spectra of the massive KK gravitinos in the scalar-tensor model.
Yun-Zhi Du, Li Zhao, Xiang-Nan Zhou, Yi Zhong, Yu-Xiao Liu Journal reference: Annals Phys. 388 (2018) 69-88 [pdf] DOI: 10.1016/j.aop.2017.10.021
-
The Effect of Massive Neutrinos on the Position of Cold Dark Matter Halo: Revealed via the Delaunay Triangulation Void -
Abstract
- Using cosmological $N$-body simulation which coevolves cold dark matter (CDM) and neutrino particles, we discover the local effect of massive neutrinos on the spatial distribution of CDM halos, reflected on properties of the Delaunay Triangulation (DT) voids. Smaller voids are generally in regions with higher neutrino abundance and so their surrounding halos are impacted by a stronger neutrino free streaming. This makes the voids larger (surrounding halos being washed outward the void center). On the contrary, larger voids are generally in regions with lower neutrino abundance and so their surrounding halos are less impacted by neutrino free streaming, making the voids smaller (surrounding halos being squeezed toward the void center). This characteristic change of the spatial distribution of the halos suppresses the 2-point correlation function of halos on scales $\sim$ 1 Mpc$/h$ and significantly skews the number function of the DT voids, which serve as measurable neutrino effects in current or future galaxy surveys.
Jian Qin, Yu Liang, Cheng Zhao, Hao-Ran Yu, Yu Liu, Tong-Jie Zhang Journal reference: The Astrophysical Journal, Volume 862, Number 1 (2018) [pdf] DOI: 10.3847/1538-4357/aacbd2
-
Linearization of a warped
-
Abstract
- Without using conformal transformation, a simple type of five-dimensional $f(R)-$brane model is linearized directly in its higher-order frame. In this paper, the linearization is conducted in the equation of motion approach. We first derive all the linear perturbation equations without specifying a gauge condition. Then by taking the curvature gauge we derive the master equations of the linear perturbations. We show that these equations are equivalent to those obtained in the quadratical action approach [Phys. Rev. D 95 (2017) 104060], except the vector sector, in which a constraint equation can be obtained in the equation of motion approach but absent in the quadratical action approach. Our work sets an example on how to linearize higher-order theories without using conformal transformation, and might be useful for studying more complicated theories.
Yuan Zhong, Ke Yang, Yu-Xiao Liu Journal reference: Phys. Rev. D 97, 044032 (2018) [pdf] DOI: 10.1103/PhysRevD.97.044032
-
Temperature effect on shear and bulk viscosities of QCD matter -
Abstract
- We investigate the temperature dependence of the shear and bulk viscosities and their ratios to the entropy density via a continuum QCD approach. We calculate the pion mass and decay constant in the framework of Dyson-Schwinger equations of QCD and the pion thermal width by combining with Roy equations. We obtain then the variation behaviors of the viscosities, especially a novel feature of the bulk viscosity, with respect to temperature.
Fei Gao, Yu-xin Liu Journal reference: Phys. Rev. D 97, 056011 (2018) [pdf] DOI: 10.1103/PhysRevD.97.056011
-
Cosmological twinlike models with multi scalar fields -
Abstract
- We consider cosmological models driven by several canonical or noncanonical scalar fields. We show how the superpotential method enables one to construct twinlike models for a particular canonical model from some noncanonical ones. We conclude that it is possible to construct twinlike models for multi-field cosmological models, even when the spatial curvature is nonzero. This work extends the discussions of [D. Bazeia and J. D. Dantas, Phys. Rev. D, 85 (2012) 067303] to cases with multi scalar fields and with non-vanished spatial curvature, by using a different superpotential method.
Yuan Zhong, Chun-E Fu, Yu-Xiao Liu Journal reference: Sci. China Phys. Mech. Astron. (2018) 61: 90411 [pdf] DOI: 10.1007/s11433-018-9194-7
-
Proton Isovector Helicity Distribution on the Lattice at Physical Pion Mass -
Abstract
- 2017
-
Optimal occlusion uniformly partitions red blood cells fluxes within a
microvascular network -
Abstract
- In animals, gas exchange between blood and tissues occurs in narrow vessels, whose diameter is comparable to that of a red blood cell. Red blood cells must deform to squeeze through these narrow vessels, transiently blocking or occluding the vessels they pass through. Although the dynamics of vessel occlusion have been studied extensively, it remains an open question why microvessels need to be so narrow. We study occlusive dynamics within a model microvascular network: the embryonic zebrafish trunk. We show that pressure feedbacks created when red blood cells enter the finest vessels of the trunk act together to uniformly partition red blood cells through the microvasculature. Using mathematical models as well as direct observation, we show that these occlusive feedbacks are tuned throughout the trunk network to prevent the vessels closest to the heart from short-circuiting the network. Thus occlusion is linked with another open question of microvascular function: how are red blood cells delivered at the same rate to each micro-vessel? Our analysis shows that tuning of occlusive feedbacks increase the total dissipation within the network by a factor of 11, showing that uniformity of flows rather than minimization of transport costs may be prioritized by the microvascular network.
Shyr-Shea Chang, Shenyinying Tu, Kyung In Baek, Andrew Pietersen, Yu-Hsiu Liu, Van Savage, Sheng-Ping L. Hwang, Tzung K. Hsiai, Marcus Roper [pdf]
-
Critical behavior of the van der Waals bonded ferromagnet
-
Abstract
- The critical properties of the single-crystalline van der Waals bonded ferromagnet Fe$_{3-x}$GeTe$_2$ were investigated by bulk dc magnetization around the paramagnetic (PM) to ferromagnetic (FM) phase transition. The Fe$_{3-x}$GeTe$_2$ single crystals grown by self-flux method with Fe deficiency $x \approx 0.36$ exhibit bulk FM ordering below $T_c = 152$ K. The M\"{o}ssbauer spectroscopy was used to provide information on defects and local atomic environment in such crystals. Critical exponents $\beta = 0.372(4)$ with a critical temperature $T_c = 151.25(5)$ K and $\gamma = 1.265(15)$ with $T_c = 151.17(12)$ K are obtained by the Kouvel-Fisher method whereas $\delta = 4.50(1)$ is obtained by a critical isotherm analysis at $T_c = 151$ K. These critical exponents obey the Widom scaling relation $\delta = 1+\gamma/\beta$, indicating self-consistency of the obtained values. With these critical exponents the isotherm $M(H)$ curves below and above the critical temperatures collapse into two independent universal branches, obeying the single scaling equation $m = f_\pm(h)$, where $m$ and $h$ are renormalized magnetization and field, respectively. The exponents determined in this study are close to those calculated from the results of the renormalization group approach for a heuristic model of three-dimensional Heisenberg ($d = 3, n = 3$) spins coupled with the attractive long-range interactions between spins that decay as $J(r)\approx r^{-(3+\sigma)}$ with $\sigma=1.89$.
Yu Liu, V. N. Ivanovski, C. Petrovic Journal reference: Physical Review B 96, 144429 (2017) [pdf] DOI: 10.1103/PhysRevB.96.144429
-
Critical behavior of the quasi-two-dimensional weak itinerant ferromagnet trigonal chromium telluride
-
Abstract
- The critical properties of flux-grown single-crystalline quasi-two-dimensional weak itinerant ferromagnet Cr$_{0.62}$Te were investigated by bulk dc magnetization around the paramagnetic (PM) to ferromagnetic (FM) phase transition. Critical exponents $\beta = 0.315(7)$ with a critical temperature $T_c = 230.6(3)$ K and $\gamma = 1.81(2)$ with $T_c = 229.1(1)$ K are obtained by the Kouvel-Fisher method whereas $\delta = 6.35(4)$ is obtained by a critical isotherm analysis at $T_c = 230$ K. With these obtained exponents, the magnetization-field-temperature curves collapse into two independent curves following a single scaling equation $M|\frac{T-T_c}{T_c}|^{-\beta} = f_\pm(H|\frac{T-T_c}{T_c}|^{-\beta\delta})$ around $T_c$, suggesting the reliability of the obtained exponents. Additionally, the determined exponents of Cr$_{0.62}$Te exhibit an Ising-like behavior with a change from short-range order to long-range order in the nature of magnetic interaction and with an extension from 2D to 3D on cooling through $T_c$.
Yu Liu, C. Petrovic Journal reference: Physical Review B 96, 134410 (2017) [pdf] DOI: 10.1103/PhysRevB.96.134410
-
Complexity growth rates for AdS black holes in massive gravity and f(R) gravity -
Abstract
- The "complexity = action" duality states that the quantum complexity is equal to the action of the stationary AdS black holes within the Wheeler-DeWitt patch at late time approximation. We compute the action growth rates of the neutral and charged black holes in massive gravity and the neutral, charged and Kerr-Newman black holes in $f(R)$ gravity to test this conjecture. Besides, we investigate the effects of the massive graviton terms, higher derivative terms and the topology of the black hole horizon on the complexity growth rate.
Wen-Di Guo, Shao-Wen Wei, Yan-Yan Li, Yu-Xiao Liu Journal reference: Eur.Phys.J. C77 (2017) 904 [pdf] DOI: 10.1140/epjc/s10052-017-5466-5
-
A Quasi-periodic Fast-propagating Magnetosonic Wave Associated with the Eruption of a Magnetic Flux Rope -
Abstract
- Using high temporal and high spatial resolution observations taken by the Atmospheric Imaging Assembly onboard the Solar Dynamics Observatory, we present the detailed observational analysis of a high quality quasi-periodic fast- propagating (QFP) magnetosonic wave that was associated with the eruption of a magnetic flux rope and a GOES C5.0 flare. For the first time, we find that the QFP wave lasted during the entire flare lifetime rather than only the rising phase of the accompanying flare as reported in previous studies. In addition, the propagation of the different parts of the wave train showed different kinematics and morphologies. For the southern (northern) part, the speed, duration, intensity variation are about 875 +/- 29 (1485 +/- 233) km/s, 45 (60) minutes, and 4% (2%), and the pronounced periods of them are 106 +/- 12 and 160 +/- 18 (75 +/- 10 and 120 +/- 16) seconds, respectively. It is interesting that the northern part of the wave train showed obvious refraction effect when they pass through a region of strong magnetic field. Periodicity analysis result indicates that all the periods of the QFP wave can be found in the period spectrum of the accompanying flare, suggesting their common physical origin. We propose that the quasi-periodic nonlinear magnetohydrodynamics process in the magnetic reconnection that produces the accompanying flare should be important for exciting of QFP wave, and the different magnetic distribution along different paths can account for the different speeds and morphology evolution of the wave fronts.
Yuandeng Shen, Yu Liu, Tengfei Song, Zhanjun Tian [pdf] DOI: 10.3847/1538-4357/aaa3ff 1712.09045v1 [pdf]
-
Region-based Quality Estimation Network for Large-scale Person
Re-identification -
Abstract
- One of the major restrictions on the performance of video-based person re-id is partial noise caused by occlusion, blur and illumination. Since different spatial regions of a single frame have various quality, and the quality of the same region also varies across frames in a tracklet, a good way to address the problem is to effectively aggregate complementary information from all frames in a sequence, using better regions from other frames to compensate the influence of an image region with poor quality. To achieve this, we propose a novel Region-based Quality Estimation Network (RQEN), in which an ingenious training mechanism enables the effective learning to extract the complementary region-based information between different frames. Compared with other feature extraction methods, we achieved comparable results of 92.4%, 76.1% and 77.83% on the PRID 2011, iLIDS-VID and MARS, respectively. In addition, to alleviate the lack of clean large-scale person re-id datasets for the community, this paper also contributes a new high-quality dataset, named "Labeled Pedestrian in the Wild (LPW)" which contains 7,694 tracklets with over 590,000 images. Despite its relatively large scale, the annotations also possess high cleanliness. Moreover, it's more challenging in the following aspects: the age of characters varies from childhood to elderhood; the postures of people are diverse, including running and cycling in addition to the normal walking state.
Guanglu Song, Biao Leng, Yu Liu, Congrui Hetang, Shaofan Cai [pdf]
-
Crack detection in beam structures with a novel Laplace based Wavelet
Finite Element method -
Abstract
- Beam structure is one of the most widely used structures in mechanical engineering and civil engineering. Ultrasonic guided wave based crack identification is one of the most important and accepted approaches applied to detect unseen small flaws in structures. Numerical simulations of ultrasonic guided wave propagation have caught more and more attention due to the fast development of hardware and software in the last few years. From all the numerical simulation methods, wavelet based finite element method has been proved to be one of the most efficient methods due to its better spatial resolution, which means it needs fewer elements to get the same accuracy and it can improve the calculation cost significantly. However, it needs a very small time interval. Laplace transform can easily convert the time domain into a frequency domain and then revert it back to a time domain. Laplace transform has thus the advantage of finding better results with a very large time interval. which can save a lot of time cost. This paper will present an innovative method combining Laplace transform and the B-spline wavelet on interval (BSWI) finite element method. This novel method allows to get results with the same accuracy and with a significantly lower time cost, which would not only decrease the total number of elements in the structure but also increase the time integration interval. The numerical Laplace transform and BSWI finite element will be introduced. Moreover, this innovative method is applied to simulate the ultrasonic wave propagation in a beam structure in different materials. Numerical examples for crack identification in beam structures have been studied for verification.
Shuaifang Zhang, Dongsheng Li, Wei Shen, Xiwen Zhang, Yu Liu [pdf]
-
Device-to-Device Communications Enabled Energy Efficient Multicast Scheduling in mmWave Small Cells -
Abstract
- To keep pace with the rapid growth of mobile traffic demands, dense deployment of small cells in millimeter wave (mmWave) bands has become a promising candidate for next generation wireless communication systems. With a greatly increased data rate from huge bandwidth of mmWave communications, energy consumption should be mitigated for higher energy efficiency. Due to content popularity, many content-based mobile applications can be supported by the multicast service. mmWave communications exploit directional antennas to overcome high path loss, and concurrent transmissions can be enabled for better multicast service. On the other hand, device-to-device (D2D) communications in physical proximity should be exploited to improve multicast performance. In this paper, we propose an energy efficient multicast scheduling scheme, referred to as EMS, which utilizes both D2D communications and concurrent transmissions to achieve high energy efficiency. In EMS, a D2D path planning algorithm establishes multi-hop D2D transmission paths, and a concurrent scheduling algorithm allocates the links on the D2D paths into different pairings. Then the transmission power of links is adjusted by the power control algorithm. Furthermore, we theoretically analyze the roles of D2D communications and concurrent transmissions in reducing energy consumption. Extensive simulations under various system parameters demonstrate the superior performance of EMS in terms of energy consumption compared with the state-of-the-art schemes. Furthermore, we also investigate the choice of the interference threshold to optimize network performance.
Yong Niu, Yu Liu, Yong Li, Xinlei Chen, Zhangdui Zhong, Zhu Han Journal reference: IEEE Transactions on Communications, 2017 [pdf] DOI: 10.1109/TCOMM.2017.2773529
-
The hierarchical Green’s function approach to the two-dimensional Hubbard model -
Abstract
- By introducing multipe-site correlation functions, we propose a hierarchical Green function approach, and apply it to study the characteristic properties of a 2D square lattice Hubbard model by solving the equation of motions of a one-particle Green function and related multipe-site correlation functions. Under a cut-off approximation and taking the Fourier representation of multipe-site correlation functions, we obtain an analytical expression of one-particle Green function with static correlation functions. Then we calculate the spectral density function of electrons, and obtain that besides two main peaks corresponding to the lower and upper Hubbard bands in the spectral density function, there emerge some novel states between these two main peaks, and the total spectral weight of these emerged states is proportional to the hole doping concentration . Meanwhile, there also emerge some collective modes related to possible charge/spin density wave and/or electronic pairing density wave ordering states. This calculation is completely consistent with the spectroscopy observations of the cuprate superconductors in normal states. On the other hand, the appearence of the static correlation functions in the one-particle Green function can be used to describe the intertwined orders observed in the normal state of the cuprate superconductors.
Yu-Liang Liu [pdf] DOI: 10.1142/S0217979218502582 1712.02002v1 [pdf]
-
Wave analysis in one dimensional structures with a wavelet finite
element model and precise integration method -
Abstract
- Numerical simulation of ultrasonic wave propagation provides an efficient tool for crack identification in structures, while it requires a high resolution and expensive time calculation cost in both time integration and spatial discretization. Wavelet finite element model provides a highorder finite element model and gives a higher accuracy on spatial discretization, B-Spline wavelet interval (BSWI) has been proved to be one of the most commonly used wavelet finite element model with the advantage of getting the same accuracy but with fewer element so that the calculation cost is much lower than traditional finite element method and other high-order element methods. Precise Integration Method provides a higher resolution in time integration and has been proved to be a stable time integration method with a much lower cut-off error for same and even smaller time step. In this paper, a wavelet finite element model combined with precis
-
Optimal occlusion uniformly partitions red blood cells fluxes within a
microvascular network -
Abstract