Mixing of Markov chains and their applications in the theory of counting and sampling

Since it is very easy to design irreducible, aperiodic, and reversible Markov chains that converge to a prescribed distribution over a finite space, we focus on them. Such Markov chains have the property that they have a globally stable stationary distribution. Furthermore, their eigenvalues are all real.