论文标题

尖锐的Poincaré和Log-Sobolev不平等的开关链上的常规两部分图

Sharp Poincaré and log-Sobolev inequalities for the switch chain on regular bipartite graphs

论文作者

Tikhomirov, Konstantin, Youssef, Pierre

论文摘要

考虑$ n $顶点上的$ d $ regratular二分之一的开关链,$ 3 \ leq d \ leq d \ leq n^{c} $,对于一个小的通用常数$ c> 0 $。我们证明,该连锁店以$ o(nd)$的订单$ o(nd)$的命令满足庞加莱的不平等。此外,当固定$ D $时,我们为链条的log-sobolev不等式建立了订单$ o_d(n \ log n)$的链条不等式。我们证明两个结果都是最佳的。 Poincaré不平等意味着,在该方案中,$ 3 \ leq d \ leq n^c $开关链的混合时间最多是$ o \ big(((nd)^2 \ log(nd)\ big)$,在先前已知的$ o \ big((nd)^(nd)^{13} {13} {13} \ log(nd)$上,kann和kann和kann ck and y nd $ big和$ o \ big(n^7d^{18} \ log(nd)\ big)$由Dyer等人获得。我们为常数$ d $建立的log-sobolev不等式意味着链条的混合时间上有绑定的$ o(n \ log^2 n)$,直到$ \ log n $ factor,它捕获了猜想的最佳界限。我们的证明策略依赖于构建,用于在$ d $的两部分简单图中的任何固定功能,这是配置模型给出的一组函数的适当扩展。然后,我们与所研究的随机换位模型建立了一个比较程序,以获得相应的功能不平等。虽然我们的方法属于不同状态空间上马尔可夫链的丰富比较技术,但该方法的关键特征 - 处理其固定措施之间具有很大变形的链条 - 是该理论的新颖补充。

Consider the switch chain on the set of $d$-regular bipartite graphs on $n$ vertices with $3\leq d\leq n^{c}$, for a small universal constant $c>0$. We prove that the chain satisfies a Poincaré inequality with a constant of order $O(nd)$; moreover, when $d$ is fixed, we establish a log-Sobolev inequality for the chain with a constant of order $O_d(n\log n)$. We show that both results are optimal. The Poincaré inequality implies that in the regime $3\leq d\leq n^c$ the mixing time of the switch chain is at most $O\big((nd)^2 \log(nd)\big)$, improving on the previously known bound $O\big((nd)^{13} \log(nd)\big)$ due to Kannan, Tetali and Vempala and $O\big(n^7d^{18} \log(nd)\big)$ obtained by Dyer et al. The log-Sobolev inequality that we establish for constant $d$ implies a bound $O(n\log^2 n)$ on the mixing time of the chain which, up to the $\log n$ factor, captures a conjectured optimal bound. Our proof strategy relies on building, for any fixed function on the set of $d$-regular bipartite simple graphs, an appropriate extension to a function on the set of multigraphs given by the configuration model. We then establish a comparison procedure with the well studied random transposition model in order to obtain the corresponding functional inequalities. While our method falls into a rich class of comparison techniques for Markov chains on different state spaces, the crucial feature of the method - dealing with chains with a large distortion between their stationary measures - is a novel addition to the theory.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源