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Autori principali: Panizo, Gonzalo, Martínez, Carlos
Natura: Preprint
Pubblicazione: 2025
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Accesso online:https://arxiv.org/abs/2507.14816
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author Panizo, Gonzalo
Martínez, Carlos
author_facet Panizo, Gonzalo
Martínez, Carlos
contents Consider the random set composed of particles initially distributed on Zd, d >= 2, according to a Poisson point process of intensity u > 0 and moving as independent simple symmetric random walks, the trap particles. We are interested in the detection by these particles of a target particle, initially at the origin and able to move with finite mean speed. The escape strategy for the target particle is to stay inside the infinite cluster of empty sites, assuming u is in the subcritical site percolation regime of particle occupation. By translating the problem to the framework of percolation of Random Interlacements we also prove that for u large enough the target doesn't escape. In doing this we extend the random interlacements formalism in order to allow non reversible random walks. As far a we know this is the first example of Random Interlacements for non-reversible Markov chains.
format Preprint
id arxiv_https___arxiv_org_abs_2507_14816
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Particle detection among Random Walks as a non-reversible Random Interlacements Process
Panizo, Gonzalo
Martínez, Carlos
Probability
Consider the random set composed of particles initially distributed on Zd, d >= 2, according to a Poisson point process of intensity u > 0 and moving as independent simple symmetric random walks, the trap particles. We are interested in the detection by these particles of a target particle, initially at the origin and able to move with finite mean speed. The escape strategy for the target particle is to stay inside the infinite cluster of empty sites, assuming u is in the subcritical site percolation regime of particle occupation. By translating the problem to the framework of percolation of Random Interlacements we also prove that for u large enough the target doesn't escape. In doing this we extend the random interlacements formalism in order to allow non reversible random walks. As far a we know this is the first example of Random Interlacements for non-reversible Markov chains.
title Particle detection among Random Walks as a non-reversible Random Interlacements Process
topic Probability
url https://arxiv.org/abs/2507.14816