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非马尔可夫碰撞模型中的熵产生:信息回流与系统 - 环境相关性

Entropy Production in Non-Markovian Collision Models: Information Backflow vs. System-Environment Correlations.

作者信息

Şenyaşa Hüseyin T, Kesgin Şahinde, Karpat Göktuğ, Çakmak Barış

机构信息

Department of Physics, Faculty of Science and Letters, Istanbul Technical University, Maslak, Istanbul 34469, Turkey.

TEBIP High Performers Program, Board of Higher Education of Turkey, Istanbul University, Fatih, Istanbul 34452, Turkey.

出版信息

Entropy (Basel). 2022 Jun 14;24(6):824. doi: 10.3390/e24060824.

Abstract

We investigate the irreversible entropy production of a qubit in contact with an environment modelled by a microscopic collision model in both Markovian and non-Markovian regimes. Our main goal is to contribute to the discussions on the relationship between non-Markovian dynamics and negative entropy production rates. We employ two different types of collision models that do or do not keep the correlations established between the system and the incoming environmental particle, while both of them pertain to their non-Markovian nature through information backflow from the environment to the system. We observe that as the former model, where the correlations between the system and environment are preserved, gives rise to negative entropy production rates in the transient dynamics, the latter one always maintains positive rates, even though the convergence to the steady-state value is slower as compared to the corresponding Markovian dynamics. Our results suggest that the mechanism underpinning the negative entropy production rates is not solely non-Markovianity through information backflow, but rather the contribution to it through established system-environment correlations.

摘要

我们研究了在马尔可夫和非马尔可夫 regimes 中,与由微观碰撞模型建模的环境相接触的量子比特的不可逆熵产生。我们的主要目标是为关于非马尔可夫动力学与负熵产生率之间关系的讨论做出贡献。我们采用了两种不同类型的碰撞模型,一种会保持系统与进入的环境粒子之间建立的相关性,另一种则不会,而它们两者都通过从环境到系统的信息回流而具有非马尔可夫性质。我们观察到,对于前一种保持系统与环境之间相关性的模型,在瞬态动力学中会产生负熵产生率,而后一种模型尽管与相应的马尔可夫动力学相比,收敛到稳态值的速度较慢,但始终保持正速率。我们的结果表明,支撑负熵产生率的机制并非仅仅是通过信息回流的非马尔可夫性,而是通过已建立的系统 - 环境相关性对其做出的贡献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed3e/9222943/49a653586ec8/entropy-24-00824-g001.jpg

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