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.

21 pages, 10 figures, including 11-page 6-figure Supplemental Material

References in corpus (29)

• Dynamical Decoupling of Open Quantum Systems
• Quantum Error Correction for Quantum Memories
• Semiconductor Spin Qubits
• Universal quantum control of two-electron spin quantum bits using dynamic nuclear polarization
• Relaxation, dephasing, and quantum control of electron spins in double quantum dots
• Detecting and polarizing nuclear spins with double resonance on a single electron spin
• Suppressing qubit dephasing using real-time Hamiltonian estimation
• Decoherence in Solid State Qubits
• Optimized quantum sensing with a single electron spin using real-time adaptive measurements
• Decoherence in qubits due to low-frequency noise
• Environmental noise spectroscopy with qubits subjected to dynamical decoupling
• Probing quantum devices with radio-frequency reflectometry
• Spectrum of the Nuclear Environment for GaAs Spin Qubits
• Characterization of a qubit Hamiltonian using adaptive measurements in a fixed basis
• Optically induced dynamic nuclear spin polarisation in diamond
• How to best sample a periodic probability distribution, or on the accuracy of Hamiltonian finding strategies
• Bayesian estimation for quantum sensing in the absence of single-shot detection
• Improving qubit coherence using closed-loop feedback
• Simultaneous Operations in a Two-Dimensional Array of Singlet-Triplet Qubits
• Coherence of a driven electron spin qubit actively decoupled from quasi-static noise
• Adaptive tracking of a time-varying field with a quantum sensor
• Machine learning for predictive estimation of qubit dynamics subject to dephasing
• Real-time two-axis control of a spin qubit
• Extending qubit coherence by adaptive quantum environment learning
• Resource-efficient adaptive Bayesian tracking of magnetic fields with a quantum sensor
• Approaching ideal visibility in singlet-triplet qubit operations using energy-selective tunneling-based Hamiltonian estimation
• Real-time adaptive estimation of decoherence timescales for a single qubit
• 1/f noise in quantum nanoscience
• Probing two-qubit capacitive interactions beyond bilinear regime using dual Hamiltonian parameter estimations

Cited by in corpus (6)

• Artificial Intelligence for Quantum Computing
• Nuclear Spin Engineering for Quantum Information Science
• Real-time adaptive tracking of fluctuating relaxation rates in superconducting qubits
• Efficient Qubit Calibration by Binary-Search Hamiltonian Tracking
• Charge state estimation in quantum dots using a Bayesian approach
• Learning the dynamics of Markovian open quantum systems from experimental data