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arXiv 2205.07214cond-mat.stat-mech
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离散时间马尔可夫过程的熵产生

Entropy Production for Discrete-Time Markov Processes

Masanao Igarashi

AI总结:

本文研究了单一和复合系统中离散时间马尔可夫过程熵产生的多种定义,明确了其等价条件、非负性及总熵产生与边际熵产生不等式在不同定义下的成立情况,并通过Gaussian process计算与数值模拟验证,给出了各定义的适用场景。

摘要:

我们研究了单一系统和复合系统中离散时间马尔可夫过程熵产生的多种定义。这些定义在单一系统中已有研究,但在复合系统中研究较少。通过明确区分,我们回顾了等价条件和多种定义的含义,并表明所有定义都满足熵产生的重要性质,如非负性。我们还表明,总熵产生与边际熵产生之间的不等式对某一定义成立,但对另一一定义不成立。此外,我们通过计算Gaussian process的熵产生验证了这一事实,并以数值方式展示了结果。最后,综合考虑所有结果,我们找到了每种定义的适当用途。

英文摘要:

We study the multiple definitions of the entropy production for discrete-time Markov processes in single systems and composite systems. These definitions have been studied in single systems, but less so in composite systems. With a clear distinction, we review the equivalence condition and the meaning of the multiple definitions and show that all definitions satisfy the important property for the entropy production, such as non-negativity. We also show that the inequalities between total entropy production and marginal entropy production holds for a definition but doesn't for another definition. Furthermore, we verify that fact by calculating entropy productions for Gaussian process and numerically show the result. Finally, we find appropriate use of each definition taking all results into account.

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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