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The European Physical Journal Plus

Exponentially stabilizing two-level stochastic quantum systems via improved noise-assisted feedback

Jie Wen

Published Feb 5, 2026• 0 citations
Publisher
DOI
10.1140/epjp/s13360-025-07258-0

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In this paper, the global exponential stabilization of two-level stochastic quantum systems is achieved by using measurement-based feedback strategies, including state feedback and noise-assisted feedback, and the state convergence rate is improved by dividing the state space. For both the combination of two continuous noise-assisted feedback and the combination of state feedback and noise-assisted feedback, the state space is divided based on the comparison of real-time state convergence rate under different measurement-based feedback strategies, respectively. The global exponential convergence and the effect of dividing state space in improving state convergence rate for two-level quantum systems are proved in theory and verified in numerical simulations.
We propose a novel control strategy by combining state feedback and noise-assisted feedback to exponentially stabilize the target eigenstate for two-level stochastic quantum systems in this paper. The state space is divided into two subspaces, and the state feedback and noise-assisted feedback work in the corresponding subspace, respectively, to achieve the faster state convergence than that of using the two feedback strategies individually. Two kinds of continuous noise-assisted feedback controls are used to form the combined feedback strategies, respectively, and the exponential stabilization of target eigenstate is proved. The effectiveness and superiority of the combined feedback strategies are also verified in numerical simulations.
We propose a novel control strategy by combining state feedback and noise-assisted feedback to exponentially stabilize the target eigenstate for two-level stochastic quantum systems in this paper. The state space is divided into two subspaces, and the state feedback and noise-assisted feedback work in the corresponding subspace, respectively, to achieve the faster state convergence than that of using the two feedback strategies individually. Two kinds of continuous noise-assisted feedback controls are used to form the combined feedback strategies, respectively, and the exponential stabilization of target eigenstate is proved. The effectiveness and superiority of the combined feedback strategies are also verified in numerical simulations.