标题： 基于粗粒度观测的马尔可夫系统参数推断与非平衡识别 显示英文标题

标题： Parameter inference and nonequilibrium identification for Markovian systems based on coarse-grained observations

摘要： 大多数实验只能检测分子系统的粗粒度聚类集合，而内部微观状态通常无法访问。 在此基础上，基于一个无限长的粗粒度轨迹，我们获得了一组充分统计量，这些统计量提取了所有粗粒度观测的统计信息。 基于这些充分统计量，我们建立了一个理论框架，用于具有任意数量微观状态和任意粗粒度划分的一般马尔可夫系统的参数推断和非平衡识别。 我们的框架可以确定充分统计量是否足以对所有未知参数进行经验估计，并且我们还可以提供一个定量准则，揭示非平衡性。 我们的非平衡准则推广了[J. Chem. Phys. 132:041102 (2010)]中针对具有两个粗粒度聚类的三态系统得到的准则，并且与基于自相关函数的经典准则相比，能够检测更大的非平衡区域。 显示英文摘要

摘要： Most experiments can only detect a set of coarse-grained clusters of a molecular system, while the internal microstates are often inaccessible. Here, based on an infinitely long coarse-grained trajectory, we obtain a set of sufficient statistics which extracts all statistic information of coarse-grained observations. Based on these sufficient statistics, we set up a theoretical framework of parameter inference and nonequilibrium identification for a general Markovian system with an arbitrary number of microstates and arbitrary coarse-grained partitioning. Our framework can identify whether the sufficient statistics are enough for empirical estimation of all unknown parameters and we can also provide a quantitative criterion that reveals nonequilibrium. Our nonequilibrium criterion generalizes the one obtained [J. Chem. Phys. 132:041102 (2010)] for a three-state system with two coarse-grained clusters, and is capable of detecting a larger nonequilibrium region compared to the classical criterion based on autocorrelation functions.