论文标题
非平衡马尔可夫系统的积分波动定理估计器的收敛性
Convergence of the Integral Fluctuation Theorem estimator for nonequilibrium Markov systems
论文作者
论文摘要
熵产生（IFT）的积分波动定理是少数已知对物理系统有效的少数平等性之一，该物理系统任意驱动远离平衡。从显微镜上讲，它可以理解为波动熵产生速率的固有对称性，这意味着热力学的第二定律。在这里，我们根据常规采样检查IFT统计估计量，并讨论其对罕见事件的限制，当稀有事件变得关键时。此外，通过一项大型偏差研究，我们讨论了一种在参数区域仔细设置实验的方法，在该参数区域中，IFT估计器安全收敛，并展示如何改善具有有限相关时间的马尔可夫链的收敛区域。我们用两个说明性的例子来证实我们的论点。
The Integral Fluctuation Theorem for entropy production (IFT) is among the few equalities that are known to be valid for physical systems arbitrarily driven far from equilibrium. Microscopically, it can be understood as an inherent symmetry for the fluctuating entropy production rate implying the second law of thermodynamics. Here, we examine an IFT statistical estimator based on regular sampling and discuss its limitations for nonequilibrium systems, when sampling rare events becomes pivotal. Furthermore, via a large deviation study, we discuss a method to carefully setup an experiment in the parameter region where the IFT estimator safely converges and also show how to improve the convergence region for Markov chains with finite correlation time. We corroborate our arguments with two illustrative examples.
