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随机热力学:耗散性、累积性、能量存储与熵产生

Stochastic thermodynamics: dissipativity, accumulativity, energy storage and entropy production.

作者信息

Lanchares Manuel, Haddad Wassim M

机构信息

School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0150, USA.

出版信息

Philos Trans A Math Phys Eng Sci. 2023 Oct 2;381(2256):20220284. doi: 10.1098/rsta.2022.0284. Epub 2023 Aug 14.

Abstract

In this paper, we develop an energy-based dynamical system model driven by a Markov input process to present a unified framework for stochastic thermodynamics predicated on a stochastic dynamical systems formalism. Specifically, using a stochastic dissipativity, losslessness and accumulativity theory, we develop a nonlinear stochastic port-Hamiltonian system model characterized by energy conservation and entropy non-conservation laws that are consistent with statistical thermodynamic principles. In particular, we show that the difference between the average stored system energy and the average supplied system energy for our stochastic thermodynamic model is a martingale with respect to the system filtration, whereas the difference between average system entropy production and the average system entropy consumption is a submartingale with respect to the system filtration. This article is part of the theme issue 'Thermodynamics 2.0: Bridging the natural and social sciences (Part 2)'.

摘要

在本文中,我们开发了一个由马尔可夫输入过程驱动的基于能量的动力学系统模型,以提出一个基于随机动力系统形式主义的随机热力学统一框架。具体而言,利用随机耗散性、无损性和累积性理论,我们开发了一个非线性随机端口哈密顿系统模型,其特征在于与统计热力学原理一致的能量守恒定律和熵不守恒定律。特别地,我们表明,对于我们的随机热力学模型,平均存储系统能量与平均供应系统能量之间的差异相对于系统滤子是一个鞅,而平均系统熵产生与平均系统熵消耗之间的差异相对于系统滤子是一个下鞅。本文是主题特刊“热力学2.0:连接自然科学与社会科学(第2部分)”的一部分。

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