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arXiv 2204.04072quant-phmath-phmath.MP
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通过Fisher信息刻画(非)马尔可夫性

Characterizing (non-)Markovianity through Fisher Information

Paolo Abiuso, Matteo Scandi, Dario De Santis, Jacopo Surace

AI总结:

本文提出利用Fisher信息度量研究非马尔可夫性,证明其单调收缩等价于马尔可夫性,并首次揭示Fisher距离膨胀对应于通过贝叶斯回溯的信息回流。

摘要:

非孤立物理系统通常会向环境丢失信息,当这种丢失不可逆时,该演化被称为马尔可夫的。非马尔可夫效应通过监测信息量化指标(如物理状态之间的距离)如何随时间演化来研究。在此我们表明,Fisher信息度量在此背景下作为研究对象自然涌现;我们从数学和操作角度全面刻画了其收缩性与马尔可夫性之间的关系。我们证明,对于经典和量子动力学,马尔可夫性等价于在状态集合所有点上Fisher度量的单调收缩。同时,基于Fisher距离膨胀的非马尔可夫性操作见证通常无法检测所有非马尔可夫演化,除非对动力学应用特定的物理后处理。最后,我们首次证明,任意时刻状态间Fisher距离的非马尔可夫膨胀对应于通过贝叶斯回溯,关于时间0动力学初始状态的信息回流。

英文摘要:

A non-isolated physical system typically loses information to its environment, and when such loss is irreversible the evolution is said to be Markovian. Non-Markovian effects are studied by monitoring how information quantifiers, such as the distance between physical states, evolve in time. Here we show that the Fisher information metric emerges as a natural object to study in this context; we fully characterize the relation between its contractivity properties and Markovianity, both from the mathematical and operational point of view. We prove, both for classical and quantum dynamics, that Markovianity is equivalent to the monotonous contraction of the Fisher metric at all points of the set of states. At the same time, operational witnesses of non-Markovianity based on the dilation of the Fisher distance cannot, in general, detect all non-Markovian evolutions, unless specific physical postprocessing is applied to the dynamics. Finally, we show for the first time that non-Markovian dilations of Fisher distance between states at any time correspond to backflow of information about the initial state of the dynamics at time 0, via Bayesian retrodiction.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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