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多协同演化系统的随机热力学——超越多方过程

Stochastic Thermodynamics of Multiple Co-Evolving Systems-Beyond Multipartite Processes.

作者信息

Tasnim Farita, Wolpert David H

机构信息

Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

Santa Fe Institute, Santa Fe, NM 87501, USA.

出版信息

Entropy (Basel). 2023 Jul 17;25(7):1078. doi: 10.3390/e25071078.

Abstract

Many dynamical systems consist of multiple, co-evolving subsystems (i.e., they have multiple degrees of freedom). Often, the dynamics of one or more of these subsystems will not directly depend on the state of some other subsystems, resulting in a network of dependencies governing the dynamics. How does this dependency network affect the full system's thermodynamics? Prior studies on the stochastic thermodynamics of multipartite processes have addressed this question by assuming that, in addition to the constraints of the dependency network, only one subsystem is allowed to change state at a time. However, in many real systems, such as chemical reaction networks or electronic circuits, multiple subsystems can-or must-change state together. Here, we investigate the thermodynamics of such composite processes, in which multiple subsystems are allowed to change state simultaneously. We first present new, strictly positive lower bounds on entropy production in composite processes. We then present thermodynamic uncertainty relations for information flows in composite processes. We end with strengthened speed limits for composite processes.

摘要

许多动力系统由多个共同演化的子系统组成(即它们具有多个自由度)。通常,这些子系统中的一个或多个的动力学不会直接依赖于其他一些子系统的状态,从而产生一个控制动力学的依赖网络。这个依赖网络如何影响整个系统的热力学?先前关于多部分过程的随机热力学的研究通过假设除了依赖网络的约束外,一次只允许一个子系统改变状态来解决这个问题。然而,在许多实际系统中,如化学反应网络或电子电路,多个子系统可以——或者必须——一起改变状态。在这里,我们研究这种复合过程的热力学,其中允许多个子系统同时改变状态。我们首先给出复合过程中熵产生的新的严格正下界。然后我们给出复合过程中信息流的热力学不确定性关系。最后我们给出复合过程的强化速度限制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/803c/10378096/2da3aae69001/entropy-25-01078-g001.jpg

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