On some basic features of strictly stationary, reversible Markov chains
本文综述了严格平稳可逆马尔可夫链的数学理论，介绍了其特殊对称性带来的额外特征，并贡献了与Rosenblatt强混合条件相关的新结果，适合概率论与统计物理研究者阅读。
It has been well known for some time that for strictly stationary Markov chains that are ‘reversible’, the special symmetry (with the distribution of the Markov chain as a whole being invariant under a reversal of the ‘direction of time’) provides special extra features in the mathematical theory. This article here is in part an exposition of some of the basic aspects of that special theory. The mathematical techniques employed in this review are relatively gentle, involving only some basic measure‐theoretic probability theory. To that special theory, a couple of new results are contributed here that are connected with the Rosenblatt strong mixing condition; and those new results in turn assist in bringing further clarity to the exposition of the theory.