PhD's Defense: Fabrizio Berritta
Title:
Real-time Quantum Control of Qubits
Abstract
A significant part of research in the field of quantum technologies is focused on mitigating noise, either by improving materials, developing noise decoupling schemes, or designing intrinsically noise-insensitive qubits. Here, we show an alternative approach in which the noise is continuously monitored and qubit control signals are adjusted accordingly [1]
In the first part of the talk, we focus on real-time closed-loop feedback protocols to estimate uncontrolled fluctuations of the qubit Hamiltonian parameters, followed by enhancing the quality of qubit rotations [1]. First, we coherently control two electron spins with a low-latency quantum controller. The protocol uses a singlet-triplet spin qubit implemented in a gallium arsenide double quantum dot. We establish real-time feedback on both control axes and enhance the resulting quality factor of coherent spin rotations. Even with some components of the Hamiltonian purely governed by noise, we demonstrate noise-driven coherent control. As an application, we implement Hadamard rotations in the presence of two fluctuating control axes.
Next, we present a protocol for a physics-informed real-time Hamiltonian estimation [2]. We estimate the fluctuating nuclear field gradient within the double dot on-the-fly by updating its probability distribution according to the Fokker-Planck equation. We further improve the physics-informed protocol by adaptively choosing the free evolution time of the electrons singlet pair, based on the previous measurement outcomes. The protocol results in a ten-fold improvement of the estimation speed compared to former schemes.
Finally, we present an adaptive frequency binary search scheme for efficiently tracking low-frequency fluctuations in a resonantly-driven qubit. In real time, we implement a Bayesian algorithm to estimate low-frequency magnetic flux noise in a flux-tunable transmon qubit, whose coherence and fidelity are improved. Furthermore, we show by gate set tomography that our frequency tracking protocol minimizes the amount of drift in the system.
Our approaches introduce closed-loop feedback schemes aimed at mitigating the effects of decoherence and extending the lifetime of quantum systems. In this view, our schemes provide valuable insights into the synergy between quantum control, quantum computation, and computer science.
[1] Berritta, F., Rasmussen, T., Krzywda, J. A. et al. Real-time two-axis control of a spin qubit. Nature Communications 15(1), 1676 (2024)
[2] Berritta, F., Krzywda, J. A., Benestad, J. et al. Physics-informed tracking of qubit fluctuations. Physical Review Applied 22(1), 014033 (2024)
Fig. 1. (a) Entangled electron spins (qubit) schedule, alternating between periods Top of quantum information processing (dashed box), and short periods Test for efficiently learning the fluctuating environment (gray box). (b) Overhauser field fluctuations, tracked in real-time by the relative rotation of the two electron spins, on a scanning electron micrograph of a gallium arsenide spin qubit array.
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