Kawasaki dynamics beyond the uniqueness threshold

Fuente: arXiv
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Hauptverfasser: Bauerschmidt, Roland, Bodineau, Thierry, Dagallier, Benoit
Format: Preprint
Veröffentlicht: 2023
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author Bauerschmidt, Roland
Bodineau, Thierry
Dagallier, Benoit
author_facet Bauerschmidt, Roland
Bodineau, Thierry
Dagallier, Benoit
contents Glauber dynamics of the Ising model on a random regular graph is known to mix fast below the tree uniqueness threshold and exponentially slowly above it. We show that Kawasaki dynamics of the canonical ferromagnetic Ising model on a random $d$-regular graph mixes fast beyond the tree uniqueness threshold when $d$ is large enough (and conjecture that it mixes fast up to the tree reconstruction threshold for all $d\geq 3$). This result follows from a more general spectral condition for (modified) log-Sobolev inequalities for conservative dynamics of Ising models. The proof of this condition in fact extends to perturbations of distributions with log-concave generating polynomial.
format Preprint
id arxiv_https___arxiv_org_abs_2310_04609
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Kawasaki dynamics beyond the uniqueness threshold
Bauerschmidt, Roland
Bodineau, Thierry
Dagallier, Benoit
Probability
Data Structures and Algorithms
Mathematical Physics
Glauber dynamics of the Ising model on a random regular graph is known to mix fast below the tree uniqueness threshold and exponentially slowly above it. We show that Kawasaki dynamics of the canonical ferromagnetic Ising model on a random $d$-regular graph mixes fast beyond the tree uniqueness threshold when $d$ is large enough (and conjecture that it mixes fast up to the tree reconstruction threshold for all $d\geq 3$). This result follows from a more general spectral condition for (modified) log-Sobolev inequalities for conservative dynamics of Ising models. The proof of this condition in fact extends to perturbations of distributions with log-concave generating polynomial.
title Kawasaki dynamics beyond the uniqueness threshold
topic Probability
Data Structures and Algorithms
Mathematical Physics
url https://arxiv.org/abs/2310.04609