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arXiv 2302.01882cond-mat.stat-mechquant-ph
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具有限制扩散的动力系统的随机熵产生

Stochastic entropy production for dynamical systems with restricted diffusion

Jonathan Dexter, Ian J. Ford

摘要:

使用随机动力学对系统的演化进行建模通常意味着随着时间的推移,所采用的系统坐标具有更大的主观不确定性,并且随机熵产生已经被开发为这种变化的度量。在某些情况下,随机熵产生的演化可以用伊藤过程来描述,但是如果系统相空间中的扩散被限制在一个较低维度的子空间中,数学上的困难就会出现。例如,如果存在运动的常数,或者更一般地,当存在无噪声地演化的坐标的函数时,这可以出现。我们讨论了这种情况下,一个开放的三能级量子系统建模的马尔可夫量子态扩散的框架内,并显示如何计算的随机熵产生的问题,在这种情况下可以克服。我们继续说明如何在适当的环境耦合下建立一个非平衡定态的三能级系统,具有恒定的随机熵的平均生产率。

英文摘要:

Modelling the evolution of a system using stochastic dynamics typically implies a greater subjective uncertainty in the adopted system coordinates as time progresses, and stochastic entropy production has been developed as a measure of this change. In some situations the evolution of stochastic entropy production can be described using an Itô process, but mathematical difficulties can emerge if diffusion in the system phase space is restricted to a subspace of lower dimension. This can arise if there are constants of the motion, for example, or more generally when there are functions of the coordinates that evolve without noise. We discuss such a case for an open three-level quantum system modelled within a framework of Markovian quantum state diffusion and show how the problem of computing the stochastic entropy production in such a situation can be overcome. We go on to illustrate how a nonequilibrium stationary state of the three-level system, with a constant mean production rate of stochastic entropy, can be established under suitable environmental couplings.

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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