The mixing time of switch Markov chains

Péter L. Erdős,Catherine Greenhill,Tamás Róbert Mezei,István Miklós, Dániel Soltész, Lajos Soukup

European Journal of Combinatorics(2022)

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摘要
Since 1997 a considerable effort has been spent to study the mixing time of switch Markov chains on the realizations of graphic degree sequences of simple graphs. Several results were proved on rapidly mixing Markov chains on unconstrained, bipartite, and directed sequences, using different mechanisms. The aim of this paper is to unify these approaches. We will illustrate the strength of the unified method by showing that on any P-stable family of unconstrained/bipartite/directed degree sequences the switch Markov chain is rapidly mixing. This is a common generalization of every known result that shows the rapid mixing nature of the switch Markov chain on a region of degree sequences. Among the applications of this general result is an almost uniform sampler for power-law and heavy-tailed degree sequences. Another application shows that the switch Markov chain on the degree sequence of an Erdős-Rényi random graph G ( n , p ) is asymptotically almost surely rapidly mixing if p is bounded away from 0 and 1 by at least 5 log n n − 1.
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