Physics-informed tracking of qubit fluctuations
arxiv(2024)
摘要
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.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要