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首页> 外文期刊>Physical Review X >Statistics of Infima and Stopping Times of Entropy Production and Applications to Active Molecular Processes
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Statistics of Infima and Stopping Times of Entropy Production and Applications to Active Molecular Processes

机译：熵产量和停止时间的统计数据和活性分子过程的应用

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We study the statistics of infima, stopping times, and passage probabilities of entropy production in nonequilibrium steady states, and we show that they are universal. We consider two examples of stopping times: first-passage times of entropy production and waiting times of stochastic processes, which are the times when a system reaches a given state for the first time. Our main results are as follows: (i)?The distribution of the global infimum of entropy production is exponential with mean equal to minus Boltzmann’s constant; (ii)?we find exact expressions for the passage probabilities of entropy production; (iii)?we derive a fluctuation theorem for stopping-time distributions of entropy production. These results have interesting implications for stochastic processes that can be discussed in simple colloidal systems and in active molecular processes. In particular, we show that the timing and statistics of discrete chemical transitions of molecular processes, such as the steps of molecular motors, are governed by the statistics of entropy production. We also show that the extreme-value statistics of active molecular processes are governed by entropy production; for example, we derive a relation between the maximal excursion of a molecular motor against the direction of an external force and the infimum of the corresponding entropy-production fluctuations. Using this relation, we make predictions for the distribution of the maximum backtrack depth of RNA polymerases, which follow from our universal results for entropy-production infima.
机译：我们研究Infima，停止时间和熵产量不足稳定状态的概率概率，我们表明他们是普遍的。我们考虑了两个停止时间的例子：熵的第一通道时间，随机过程的等待时间，这是系统首次达到给定状态的时代。我们的主要结果如下：（i）？全球熵产量的分布是指数级，平均等于减去博尔兹曼的常数; （ii）？我们为熵生产的通行概率找到了确切的表达; （iii）？我们推出了停止时间分布的波动定理。这些结果对随机过程具有有趣的影响，这些过程可以在简单的胶体系统和活性分子过程中讨论。特别是，我们表明分子过程的离散化学转变的时序和统计，例如分子电机的步骤，受到熵产生的统计数据。我们还表明，活性分子过程的极值统计数据受熵生产的管辖;例如，我们在分子电机的最大偏移与外力方向和相应的熵 - 产生波动的最小值之间获得关系。使用这一关系，我们对RNA聚合酶的最大倒退深度的分布进行了预测，这是从我们的熵生产Infima的普遍结果遵循的。

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