论文标题
随机重置下的复杂网络上随机步行的熵率
Entropy rate of random walks on complex networks under stochastic resetting
论文作者
论文摘要
近年来，在随机重置下进行重置的随机过程引起了很多关注，并用作随机动力学的非平凡且有趣的静态和动态特征的例证。在本文中，我们旨在解决在离散时间马尔可夫过程中随机重置的熵率如何影响，并探索重置在随机过程的混合特性中的非平凡效应。特别是，我们考虑在复杂的网络上重置随机步行，并计算熵率是重置概率的函数。有趣的是，我们发现熵率可以显示出对重置概率的非单调依赖性。存在熵率达到最大值的最佳重置概率。我们还表明，最大熵率可能大于同一拓扑上的最大透射随机步行。我们的研究提供了随机重置对非平衡统计物理学的新非平地作用。
Stochastic processes under resetting at random times have attracted a lot of attention in recent years and served as illustrations of nontrivial and interesting static and dynamic features of stochastic dynamics. In this paper, we aim to address how the entropy rate is affected by stochastic resetting in discrete-time Markovian processes, and explore nontrivial effects of the resetting in the mixing properties of a stochastic process. In particular, we consider resetting random walks on complex networks and compute the entropy rate as a function of the resetting probability. Interestingly, we find that the entropy rate can show a nonmonotonic dependence on the resetting probability. There exists an optimal resetting probability for which the entropy rate reaches a maximum. We also show that the maximum entropy rate can be larger than that of the maximal-entropy random walks on the same topology. Our study provides a new nontrivial effect of stochastic resetting on nonequilibrium statistical physics.
