Publications by Ferdinand Kuemmeth
- 2025
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Efficient Qubit Calibration by Binary-Search Hamiltonian Tracking -
Abstract
- We present a real-time method for calibrating the frequency of a resonantly driven qubit. The real-time processing capabilities of a controller dynamically compute adaptive probing sequences for qubit-frequency estimation. Each probing time and drive frequency are calculated to divide the prior probability distribution into two branches, following a locally optimal strategy that mimics a conventional binary search. We show the algorithm's efficacy by stabilizing a flux-tunable transmon qubit, leading to improved coherence and gate fidelity. By feeding forward the updated qubit frequency, the FPGA-powered control electronics also mitigates non-Markovian noise in the system, which is detrimental to quantum error correction. Our protocol highlights the importance of feedback in improving the calibration and stability of qubits subject to drift and can be readily applied to other qubit platforms.
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Efficient Qubit Calibration by Binary-Search Hamiltonian Tracking -
Abstract
- 2024
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Automated in situ optimization and disorder mitigation in a quantum
device -
Abstract
- We investigate automated in situ optimization of the potential landscape in a quantum point contact device, using a $3 \times 3$ gate array patterned atop the constriction. Optimization is performed using the covariance matrix adaptation evolutionary strategy, for which we introduce a metric for how "step-like" the conductance is as the channel becomes constricted. We first perform the optimization of the gate voltages in a tight-binding simulation and show how such in situ tuning can be used to mitigate a random disorder potential. The optimization is then performed in a physical device in experiment, where we also observe a marked improvement in the quantization of the conductance resulting from the optimization procedure.
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A quantum dot in germanium proximitized by a superconductor -
Abstract
- Planar germanium quantum wells have recently been shown to host hard-gapped superconductivity. Additionally, quantum dot spin qubits in germanium are well-suited for quantum information processing, with isotopic purification to a nuclear spin-free material expected to yield long coherence times. Therefore, as one of the few group IV materials with the potential to host superconductor-semiconductor hybrid devices, proximitized quantum dots in germanium is a compelling platform to achieve and combine topological superconductivity with existing and novel qubit modalities. Here we demonstrate a quantum dot (QD) in a Ge/SiGe heterostructure proximitized by a platinum germanosilicide (PtGeSi) superconducting lead (SC), forming a SC-QD-SC junction. We show tunability of the QD-SC coupling strength, as well as gate control of the ratio of charging energy and the induced gap. We further exploit this tunability by exhibiting control of the ground state of the system between even and odd parity. Furthermore, we characterize the critical magnetic field strengths, finding a critical out-of-plane field of 0.90(4). Finally we explore sub-gap spin splitting in the device, observing rich physics in the resulting spectra, that we model using a zero-bandwidth model in the Yu-Shiba-Rusinov limit. The demonstration of controllable proximitization at the nanoscale of a germanium quantum dot opens up the physics of novel spin and superconducting qubits, and Josephson junction arrays in a group IV material.
Lazar Lakic, William I. L. Lawrie, David van Driel, Lucas E. A. Stehouwer, Yao Su, Menno Veldhorst, Giordano Scappucci, Ferdinand Kuemmeth, Anasua Chatterjee [pdf]
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Autonomous Bootstrapping of Quantum Dot Devices -
Abstract
- Semiconductor quantum dots (QD) are a promising platform for multiple different qubit implementations, all of which are voltage-controlled by programmable gate electrodes. However, as the QD arrays grow in size and complexity, tuning procedures that can fully autonomously handle the increasing number of control parameters are becoming essential for enabling scalability. We propose a bootstrapping algorithm for initializing a depletion mode QD device in preparation for subsequent phases of tuning. During bootstrapping, the QD device functionality is validated, all gates are characterized, and the QD charge sensor is made operational. We demonstrate the bootstrapping protocol in conjunction with a coarse tuning module, showing that the combined algorithm can efficiently and reliably take a cooled-down QD device to a desired global state configuration in under 8 minutes with a success rate of 96 %. Importantly, by following heuristic approaches to QD device initialization and combining the efficient ray-based measurement with the rapid radio-frequency reflectometry measurements, the proposed algorithm establishes a reference in terms of performance, reliability, and efficiency against which alternative algorithms can be benchmarked.
Anton Zubchenko, Danielle Middlebrooks, Torbjørn Rasmussen, Lara Lausen, Ferdinand Kuemmeth, Anasua Chatterjee, Justyna P. Zwolak [pdf]
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Physics-informed tracking of qubit fluctuations -
Abstract
- Environmental fluctuations degrade the performance of solid-state qubits but can in principle be mitigated by real-time Hamiltonian estimation down to time scales set by the estimation efficiency. We implement a physics-informed and an adaptive Bayesian estimation strategy and apply them in real time to a semiconductor spin qubit. The physics-informed strategy propagates a probability distribution inside the quantum controller according to the Fokker-Planck equation, appropriate for describing the effects of nuclear spin diffusion in gallium-arsenide. Evaluating and narrowing the anticipated distribution by a predetermined qubit probe sequence enables improved dynamical tracking of the uncontrolled magnetic field gradient within the singlet-triplet qubit. The adaptive strategy replaces the probe sequence by a small number of qubit probe cycles, with each probe time conditioned on the previous measurement outcomes, thereby further increasing the estimation efficiency. The combined real-time estimation strategy efficiently tracks low-frequency nuclear spin fluctuations in solid-state qubits, and can be applied to other qubit platforms by tailoring the appropriate update equation to capture their distinct noise sources.
Fabrizio Berritta, Jan A. Krzywda, Jacob Benestad, Joost van der Heijden, Federico Fedele, Saeed Fallahi, Geoffrey C. Gardner, Michael J. Manfra, Evert van Nieuwenburg, Jeroen Danon, Anasua Chatterjee, Ferdinand Kuemmeth Journal reference: Phys. Rev. Applied 22, 014033 (2024) [pdf] DOI: 10.1103/PhysRevApplied.22.014033
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Low-temperature benchmarking of qubit control wires by primary electron
thermometry -
Abstract
- Low-frequency qubit control wires require non-trivial thermal anchoring and low-pass filtering. The resulting electron temperature serves as a quality benchmark for these signal lines. In this technical note, we make use of a primary electron thermometry technique, using a Coulomb blockade thermometer, to establish the electron temperature in the millikelvin regime. The experimental four-probe measurement setup, the data analysis, and the measurement limitations are discussed in detail. We verify the results by also using another electron thermometry technique, based on a superconductor-insulator-normal metal junction. Our comparison of signal lines with QDevil's QFilter to unfiltered signal lines demonstrates that the filter significantly reduces both the rms noise and electron temperature, which is measured to be 22 $\pm$ 1 mK.
Elias Roos Hansen, Ferdinand Kuemmeth, Joost van der Heijden [pdf]
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Automated in situ optimization and disorder mitigation in a quantum
device -
Abstract