Self-switching random walks on Erdös-Rényi random graphs feel the phase transition

Fuente: arXiv
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Hauptverfasser: Iacobelli, Giulio, Ost, Guilherme, Takahashi, Daniel Y.
Format: Preprint
Veröffentlicht: 2023
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author Iacobelli, Giulio
Ost, Guilherme
Takahashi, Daniel Y.
author_facet Iacobelli, Giulio
Ost, Guilherme
Takahashi, Daniel Y.
contents We study random walks on Erdös-Rényi random graphs in which, every time the random walk returns to the starting point, first an edge probability is independently sampled according to a priori measure $μ$, and then an Erdös-Rényi random graph is sampled according to that edge probability. When the edge probability $p$ does not depend on the size of the graph $n$ (dense case), we show that the proportion of time the random walk spends on different values of $p$ -- {\it occupation measure} -- converges to the a priori measure $μ$ as $n$ goes to infinity. More interestingly, when $p=λ/n$ (sparse case), we show that the occupation measure converges to a limiting measure with a density that is a function of the survival probability of a Poisson branching process. This limiting measure is supported on the supercritial values for the Erdös-Rényi random graphs, showing that self-witching random walks can detect the phase transition.
format Preprint
id arxiv_https___arxiv_org_abs_2310_12355
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Self-switching random walks on Erdös-Rényi random graphs feel the phase transition
Iacobelli, Giulio
Ost, Guilherme
Takahashi, Daniel Y.
Probability
Mathematical Physics
We study random walks on Erdös-Rényi random graphs in which, every time the random walk returns to the starting point, first an edge probability is independently sampled according to a priori measure $μ$, and then an Erdös-Rényi random graph is sampled according to that edge probability. When the edge probability $p$ does not depend on the size of the graph $n$ (dense case), we show that the proportion of time the random walk spends on different values of $p$ -- {\it occupation measure} -- converges to the a priori measure $μ$ as $n$ goes to infinity. More interestingly, when $p=λ/n$ (sparse case), we show that the occupation measure converges to a limiting measure with a density that is a function of the survival probability of a Poisson branching process. This limiting measure is supported on the supercritial values for the Erdös-Rényi random graphs, showing that self-witching random walks can detect the phase transition.
title Self-switching random walks on Erdös-Rényi random graphs feel the phase transition
topic Probability
Mathematical Physics
url https://arxiv.org/abs/2310.12355