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Bulletin of the American Physical Society

Quantum state estimation and feedback control aided by weak measurement reversal

Hermann Uys, Pieter du Toit, S. C. Burd, Thomas Konrad

Published Jun 10, 2015• 0 citations
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Abstract We present protocols for feedback control and stabilization of a single qubit undergoing Rabi oscillations. Using a hybrid quantum-classical Bayesian estimation technique we simulate monitoring of the dynamical parameter (Rabi frequency) of the governing Hamiltonian in real-time. We numerically demonstrate feedback control of the system parameter using a classical proportional-integral feedback control scheme and show that by implementing a unitary reversal of the back-action of the weak measurement the loop response time is dramatically reduced. This reversal is chosen by assuming the system is already executing the targeted dynamics, an approach called self-fulfilling prophecy . In addition, self-fulfilling prophecy reduces measurement induced noise, leading to stabilized dynamics.
In this paper, we propose a Lyapunov-based state feedback control for state transfer based on the on-line quantum state estimation (OQSE). The OQSE is designed based on continuous weak measurements and compressed sensing. The controlled system is described by quantum master equation for open quantum systems, and the continuous measurement operators are derived according to the dynamic equation of system. The feedback control law is designed based on the Lyapunov stability theorem, and a strict proof of proposed control laws are given. At each sampling time, the state is estimated on-line, which is used to design the control law. The simulation experimental results show the effectiveness of the proposed feedback control strategy.
In this paper the state of Markovian open quantum system is estimated on-line based on the continuous weak measurement and compression sensing theory, and a quantum Lyapunov feedback control law is designed to transfer the state from the initial state to the desired target state based on the state estimated on-line. Numerical simulation experiments are implemented under MATLAB environment. The experimental results show the effectiveness of the on-line estimated state-based feedback control method proposed