发表机构
The University of Tokyo（东京大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究在连续监测碰撞模型框架下，发现信息稳态的每次测量信息增益与非马尔可夫性程度负相关，并数值表征了相互作用参数的影响。
AI 中文摘要
信息稳态（ISSs）出现在从连续测量中获取信息的速率与早期测量信息向环境丢失的速率精确平衡之时。尽管ISSs已在马尔可夫环境中得到研究，但关于记忆效应如何影响其形成及稳态性质所知甚少。在本工作中，我们在连续监测碰撞模型的框架内研究非马尔可夫效应对ISSs的影响。我们将环境建模为一系列双量子比特辅助体，并发现对于这一特定模型，每次测量的稳态信息增益与非马尔可夫性程度呈负相关。数值结果进一步刻画了系统-辅助体和辅助体-辅助体相互作用参数如何影响非马尔可夫性程度和稳态信息增益。
英文摘要
Informational steady states (ISSs) arise when the rate at which information is gained from continuous measurements is exactly balanced by the rate at which information from earlier measurements is lost to the environment. While ISSs have been studied in Markovian settings, relatively little is known about how memory effects influence their formation and steady-state properties. In this work, we investigate non-Markovian effects on ISSs within the framework of continuously monitored collision models. We model the environment as a sequence of two-qubit ancillas and find that, for this specific model, the steady-state information gain per measurement is negatively correlated with the degree of non-Markovianity. Numerical results further characterize how the system-ancilla and ancilla-ancilla interaction parameters influence both the degree of non-Markovianity and the steady-state information gain.
