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arXiv 2108.07428cond-mat.stat-mechnlin.AOquant-ph
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统计物理中的引擎问题

The problem of engines in statistical physics

Robert Alicki, David Gelbwaser-Klimovsky, Alejandro Jenkins

摘要:

发动机是开放的系统,可以周期性地产生功,以外部不平衡为代价。它们在自然界和技术中无处不在,但在过去300年的数学物理课程中,它们的时间动力学往往成为理论盲点。这妨碍了统计力学应用于包括生命物质在内的主动系统的实用性。我们认为,开放量子系统理论的最新进展,再加上新的兴趣,了解如何积极的力量,结果从不同的宏观自由度之间的正反馈耗散的存在,指向一个更现实的描述自治引擎。我们提出了一个一般概念的发动机,有助于澄清其热量和功输出之间的区别。在此基础上,我们展示了如何外部加载力和热噪声可能被纳入相关的运动方程。这修改了通常的福克-普朗克和朗之万方程,提供了一个简单的振荡和旋转发动机的不可逆动力学的数学上完整的配方。

英文摘要:

Engines are open systems that can generate work cyclically, at the expense of an external disequilibrium. They are ubiquitous in nature and technology, but the course of mathematical physics over the last 300 years has tended to make their dynamics in time a theoretical blind spot. This has hampered the usefulness of statistical mechanics applied to active systems, including living matter. We argue that recent advances in the theory of open quantum systems, coupled with renewed interest in understanding how active forces result from positive feedback between different macroscopic degrees of freedom in the presence of dissipation, point to a more realistic description of autonomous engines. We propose a general conceptualization of an engine that helps clarify the distinction between its heat and work outputs. Based on this, we show how the external loading force and the thermal noise may be incorporated into the relevant equations of motion. This modifies the usual Fokker-Planck and Langevin equations, offering a thermodynamically complete formulation of the irreversible dynamics of simple oscillating and rotating engines.

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