On a population model with memory

Fuente: arXiv
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Main Author: Bertoin, Jean
Format: Preprint
Published: 2024
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author Bertoin, Jean
author_facet Bertoin, Jean
contents Consider first a memoryless population model described by the usual branching process with a given mean reproduction matrix on a finite space of types. Motivated by the consequences of atavism in Evolutionary Biology, we are interested in a modification of the dynamics where individuals keep full memory of their forebears and procreation involves the reactivation of a gene picked at random on the ancestral lineage. By comparing the spectral radii of the two mean reproduction matrices (with and without memory), we observe that, on average, the model with memory always grows at least as fast as the model without memory. The proof relies on analyzing a biased Markov chain on the space of memories, and the existence of a unique ergodic law is demonstrated through asymptotic coupling.
format Preprint
id arxiv_https___arxiv_org_abs_2501_00306
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle On a population model with memory
Bertoin, Jean
Probability
60J80
Consider first a memoryless population model described by the usual branching process with a given mean reproduction matrix on a finite space of types. Motivated by the consequences of atavism in Evolutionary Biology, we are interested in a modification of the dynamics where individuals keep full memory of their forebears and procreation involves the reactivation of a gene picked at random on the ancestral lineage. By comparing the spectral radii of the two mean reproduction matrices (with and without memory), we observe that, on average, the model with memory always grows at least as fast as the model without memory. The proof relies on analyzing a biased Markov chain on the space of memories, and the existence of a unique ergodic law is demonstrated through asymptotic coupling.
title On a population model with memory
topic Probability
60J80
url https://arxiv.org/abs/2501.00306