Mixing time for an epidemic model on graphs with external sources of infection

Fuente: arXiv
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Autori principali: KhudaBukhsh, Wasiur R., Xiang, Yangrui
Natura: Preprint
Pubblicazione: 2025
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author KhudaBukhsh, Wasiur R.
Xiang, Yangrui
author_facet KhudaBukhsh, Wasiur R.
Xiang, Yangrui
contents We study the mixing time of a Susceptible--Infected--Susceptible (SIS) model on graphs with external sources of infection, which we refer to as the noisy SIS model. Under suitable assumptions on the parameters of the dynamics, we show that the mixing time is of the order $Θ(n\log n)$ with respect to the number of vertices $n$. We further investigate the model on random graph families, including Erd{ö}s--R{é}nyi graphs, random regular multigraphs, and Galton--Watson trees. By identifying high-probability structural properties of these graphs and conditioning on typical realizations, we prove that the mixing time remains of order $Θ(n\log n)$ with high probability.
format Preprint
id arxiv_https___arxiv_org_abs_2501_07738
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Mixing time for an epidemic model on graphs with external sources of infection
KhudaBukhsh, Wasiur R.
Xiang, Yangrui
Probability
Mathematical Physics
Statistics Theory
Populations and Evolution
60J10, 60J20, 92D25
We study the mixing time of a Susceptible--Infected--Susceptible (SIS) model on graphs with external sources of infection, which we refer to as the noisy SIS model. Under suitable assumptions on the parameters of the dynamics, we show that the mixing time is of the order $Θ(n\log n)$ with respect to the number of vertices $n$. We further investigate the model on random graph families, including Erd{ö}s--R{é}nyi graphs, random regular multigraphs, and Galton--Watson trees. By identifying high-probability structural properties of these graphs and conditioning on typical realizations, we prove that the mixing time remains of order $Θ(n\log n)$ with high probability.
title Mixing time for an epidemic model on graphs with external sources of infection
topic Probability
Mathematical Physics
Statistics Theory
Populations and Evolution
60J10, 60J20, 92D25
url https://arxiv.org/abs/2501.07738