Ertel Benjamin, van der Meer Jann, Seifert Udo
II. Institut für Theoretische Physik, Universität Stuttgart, 70550 Stuttgart, Germany.
Phys Rev E. 2022 Apr;105(4-1):044113. doi: 10.1103/PhysRevE.105.044113.
Semi-Markov processes generalize Markov processes by adding temporal memory effects as expressed by a semi-Markov kernel. We recall the path weight for a semi-Markov trajectory and the fact that thermodynamic consistency in equilibrium imposes a crucial condition called direction-time independence for which we present an alternative derivation. We prove a thermodynamic uncertainty relation that formally resembles the one for a discrete-time Markov process. The result relates the entropy production of the semi-Markov process to mean and variance of steady-state currents. We prove a further thermodynamic uncertainty relation valid for semi-Markov descriptions of coarse-grained Markov processes that emerge by grouping states together. A violation of this inequality can be used as an inference tool to conclude that a given semi-Markov process cannot result from coarse graining an underlying Markov one. We illustrate these results with representative examples.
半马尔可夫过程通过添加由半马尔可夫核表示的时间记忆效应来推广马尔可夫过程。我们回顾了半马尔可夫轨迹的路径权重以及平衡态下的热力学一致性施加了一个关键条件,即方向时间独立性,对此我们给出了一种替代推导。我们证明了一个形式上类似于离散时间马尔可夫过程的热力学不确定性关系。该结果将半马尔可夫过程的熵产生与稳态电流的均值和方差联系起来。我们还证明了另一个对通过将状态分组而出现的粗粒化马尔可夫过程的半马尔可夫描述有效的热力学不确定性关系。违反这个不等式可以用作一种推理工具,以得出给定的半马尔可夫过程不可能由对底层马尔可夫过程进行粗粒化得到的结论。我们用代表性例子说明了这些结果。