非平衡定态中细致平衡破缺的信号：微妙、显著与非凡
Signals of Detailed Balance Violation in Nonequilibrium Stationary States: Subtle, Manifest, and Extraordinary
AI总结：
本文研究非平衡定态中细致平衡破缺的信号，提出利用概率角动量和时间反演不对称性检测非平衡特征，并通过模拟验证方法的有效性。
摘要：
物理系统的演化常被建模为简单的马尔可夫过程。当系统进入定态时，其概率分布按定义是时间无关的。然而，这些定态并不一定属于平衡统计力学的框架，而可能是非平衡定态（NESS）。NESS的一个显著特征是时间反演不对称性（TRA）的存在以及持续的概率流环。这些环自然引出了概率角动量的概念，其在随机过程中的地位与噪声协方差同等重要。通过简单模型和物理数据的模拟演示，我们提出了从微妙到显著的各种检测这些TRA信号的方法。
英文摘要：
The evolution of physical systems are often modeled by simple Markovian processes. When settled into stationary states, the probability distributions of such systems are time independent, by definition. However, they do not necessarily fall within the framework of equilibrium statistical mechanics. Instead, they may be non-equilibrium steady states (NESS). One distinguished feature of NESS is the presence of time reversal asymmetry (TRA) and persistent probability current loops. These loops lead naturally to the notion of probability angular momenta, which play a role on the same footing as the noise covariance in stochastic processes. Illustrating with simulations of simple models and physical data, we present ways to detect these signals of TRA, from the subtle to the prominent.
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