Spatial Mixing for Independent Sets in Poisson Random Trees
Varsha Dani, Thomas P.Hayes, Cristopher Moore

TL;DR
This paper investigates how correlation decay and spatial mixing properties in the hard-core model behave on Poisson random trees, revealing thresholds and differences from regular trees.
Contribution
It provides new insights into the spatial mixing thresholds on Poisson trees, showing similarities and differences with regular trees and analyzing the effects of tree finiteness.
Findings
Weak spatial mixing occurs for large $d$ when $\lambda < f(d)$
Strong spatial mixing does not always coincide with weak on Poisson trees
WSM holds almost surely for $d<1.434$ but fails with positive probability for $d>1$
Abstract
We consider correlation decay in the hard-core model with fugacity on a rooted tree in which the arity of each vertex is independently Poisson distributed with mean . Specifically, we investigate the question of which parameter settings result in strong spatial mixing, weak spatial mixing, or neither. (In our context, weak spatial mixing is equivalent to Gibbs uniqueness.) For finite fugacity, a zero-one law implies that these spatial mixing properties hold either almost surely or almost never, once we have conditioned on whether is finite or infinite. We provide a partial answer to this question, which implies in particular that 1. As , weak spatial mixing on the Poisson tree occurs whenever but not when is slightly above , where is the threshold for WSM (and SSM) on the -regular…
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Taxonomy
TopicsMarkov Chains and Monte Carlo Methods · Stochastic processes and statistical mechanics · Topological and Geometric Data Analysis
