Covering a graph with independent walks

Fuente: arXiv
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Autori principali: Hermon, Jonathan, Sousi, Perla
Natura: Preprint
Pubblicazione: 2021
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author Hermon, Jonathan
Sousi, Perla
author_facet Hermon, Jonathan
Sousi, Perla
contents Let $P$ be an irreducible and reversible transition matrix on a finite state space $V$ with invariant distribution $π$. We let $k$ chains start by choosing independent locations distributed according to $π$ and then they evolve independently according to $P$. Let $τ_{\mathrm{cov}}(k)$ be the first time that every vertex of $V$ has been visited at least once by at least one chain and let $t_{\rm{cov}}(k)=\mathbb{E}[τ_{\mathrm{cov}}(k)]$ with $t_{\rm{cov}}=t_{\rm{cov}}(1)$. We prove that $t_{\rm{cov}}(k)\lesssim t_{\rm{cov}}/k$. When $k\leq t_{\mathrm{cov}}/t_{\rm{rel}}$, where $t_{\rm{rel}}$ is the inverse of the spectral gap, we show that this bound is sharp. For $k\leq t_{\mathrm{cov}}/t_{\rm{mix}}$ with $t_{\rm{mix}}$ the total variation mixing time of $(P+I)/2$ we prove that $k \cdot \max_{x_1,\ldots,x_k}\mathbb{E}_{x_1,\ldots,x_k}[τ_{\rm{cov}}(k)] \asymp t_{\rm{cov}}$.
format Preprint
id arxiv_https___arxiv_org_abs_2104_00665
institution arXiv
publishDate 2021
record_format arxiv
spellingShingle Covering a graph with independent walks
Hermon, Jonathan
Sousi, Perla
Probability
60J10, 60J27
Let $P$ be an irreducible and reversible transition matrix on a finite state space $V$ with invariant distribution $π$. We let $k$ chains start by choosing independent locations distributed according to $π$ and then they evolve independently according to $P$. Let $τ_{\mathrm{cov}}(k)$ be the first time that every vertex of $V$ has been visited at least once by at least one chain and let $t_{\rm{cov}}(k)=\mathbb{E}[τ_{\mathrm{cov}}(k)]$ with $t_{\rm{cov}}=t_{\rm{cov}}(1)$. We prove that $t_{\rm{cov}}(k)\lesssim t_{\rm{cov}}/k$. When $k\leq t_{\mathrm{cov}}/t_{\rm{rel}}$, where $t_{\rm{rel}}$ is the inverse of the spectral gap, we show that this bound is sharp. For $k\leq t_{\mathrm{cov}}/t_{\rm{mix}}$ with $t_{\rm{mix}}$ the total variation mixing time of $(P+I)/2$ we prove that $k \cdot \max_{x_1,\ldots,x_k}\mathbb{E}_{x_1,\ldots,x_k}[τ_{\rm{cov}}(k)] \asymp t_{\rm{cov}}$.
title Covering a graph with independent walks
topic Probability
60J10, 60J27
url https://arxiv.org/abs/2104.00665