Law of large numbers for greedy animals and paths in an ergodic environment

Fuente: arXiv
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Main Author: Verges, Julien
Format: Preprint
Published: 2024
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author Verges, Julien
author_facet Verges, Julien
contents Consider a family of random masses $\mathbf{m}(v)$ indexed by vertices of the lattice $\mathbb Z^d$. In the case where the masses are i.i.d.\ and satisfy a certain moment condition, it is known that there exists a deterministic $A\ge 0$ such that the maximal mass $A_n$ of an animal containing $0$ with cardinal $n$ satisfies $A_n/n \rightarrow A$ when $n\to \infty$, almost surely. The same also goes for self-avoiding paths. We extend this result to the case where the family of masses is an ergodic marked point process, with a suitable definition for animals in this context. Special cases include the initial model with ergodic instead of i.i.d.\ masses and marked Poisson point processes. We also discuss some sufficient or necessary conditions for integrability.
format Preprint
id arxiv_https___arxiv_org_abs_2409_14773
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Law of large numbers for greedy animals and paths in an ergodic environment
Verges, Julien
Probability
Consider a family of random masses $\mathbf{m}(v)$ indexed by vertices of the lattice $\mathbb Z^d$. In the case where the masses are i.i.d.\ and satisfy a certain moment condition, it is known that there exists a deterministic $A\ge 0$ such that the maximal mass $A_n$ of an animal containing $0$ with cardinal $n$ satisfies $A_n/n \rightarrow A$ when $n\to \infty$, almost surely. The same also goes for self-avoiding paths. We extend this result to the case where the family of masses is an ergodic marked point process, with a suitable definition for animals in this context. Special cases include the initial model with ergodic instead of i.i.d.\ masses and marked Poisson point processes. We also discuss some sufficient or necessary conditions for integrability.
title Law of large numbers for greedy animals and paths in an ergodic environment
topic Probability
url https://arxiv.org/abs/2409.14773