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Main Authors: Prodromidis, Kyprianos-Iason, Sly, Allan
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2510.07254
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author Prodromidis, Kyprianos-Iason
Sly, Allan
author_facet Prodromidis, Kyprianos-Iason
Sly, Allan
contents We consider the stochastic Ising model on sparse Erdos-Renyi graphs $G(n,d/n)$ with $d>1$ at the critical temperature $β_c=\tanh^{-1}(d^{-1})$ and prove that with high probability, the mixing time is at most polynomial in $n$. Our approach combines the recent stochastic localization framework of Chen and Eldan, which yields spectral gap bounds in the well-behaved bulk of the graph, together with classical results on the relaxation time of Glauber dynamics on trees to handle regions where we cannot apply the Chen-Eldan method directly because of atypically large local neighborhoods.
format Preprint
id arxiv_https___arxiv_org_abs_2510_07254
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Polynomial mixing of the critical Ising model on sparse Erdos-Renyi graphs
Prodromidis, Kyprianos-Iason
Sly, Allan
Probability
We consider the stochastic Ising model on sparse Erdos-Renyi graphs $G(n,d/n)$ with $d>1$ at the critical temperature $β_c=\tanh^{-1}(d^{-1})$ and prove that with high probability, the mixing time is at most polynomial in $n$. Our approach combines the recent stochastic localization framework of Chen and Eldan, which yields spectral gap bounds in the well-behaved bulk of the graph, together with classical results on the relaxation time of Glauber dynamics on trees to handle regions where we cannot apply the Chen-Eldan method directly because of atypically large local neighborhoods.
title Polynomial mixing of the critical Ising model on sparse Erdos-Renyi graphs
topic Probability
url https://arxiv.org/abs/2510.07254