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arXiv 1002.4520cond-mat.stat-mech
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马尔可夫过程的熵产生与粗粒化

Entropy production and coarse-graining in Markov processes

A. Puglisi, S. Pigolotti, L. Rondoni, A. Vulpiani

摘要:

研究了马尔可夫过程中熵产生的大时间涨落。特别是,我们认为一个粗粒度的过程中抽取{ \em快速状态}相对于一个给定的时间阈值的效果。我们的研究结果提供了强有力的证据表明,熵的产生并不直接受到这种抽取的影响,只要它不完全删除循环携带的净概率电流。在研究了简单图上随机游走的一些例子之后,我们将我们的分析应用于驱动蛋白循环的网络模型,驱动蛋白循环是一种重要的生物分子马达。一个尝试性的一般理论,这些事实的基础上,Schnakenberg的网络理论,提出。

英文摘要:

We study the large time fluctuations of entropy production in Markov processes. In particular, we consider the effect of a coarse-graining procedure which decimates {\em fast states} with respect to a given time threshold. Our results provide strong evidence that entropy production is not directly affected by this decimation, provided that it does not entirely remove loops carrying a net probability current. After the study of some examples of random walks on simple graphs, we apply our analysis to a network model for the kinesin cycle, which is an important biomolecular motor. A tentative general theory of these facts, based on Schnakenberg's network theory, is proposed.

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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