Functional central limit theorem for the subgraph count of the voter model on dynamic random graphs

Fuente: arXiv
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Auteurs principaux: Baldassarri, Simone, Kriukov, Nikolai
Format: Preprint
Publié: 2025
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author Baldassarri, Simone
Kriukov, Nikolai
author_facet Baldassarri, Simone
Kriukov, Nikolai
contents In this paper we consider two-opinion voter models on dynamic random graphs, in which the joint dynamics of opinions and graphs acts as one-way feedback, i.e., edges appear and disappear over time depending on the opinions of the two connected vertices, while the opinion dynamics is not affected by the graph structure. Our goal is to investigate the joint evolution of the entries of a voter subgraph count vector, i.e., vector of subgraphs where each vertex has a specific opinion, in the regime that the number of vertices grows large. The main result of this paper is a functional central limit theorem. In particular, we prove that, under a proper centering and scaling, the joint functional of the vector of subgraph counts converges to a specific multidimensional Gaussian process.
format Preprint
id arxiv_https___arxiv_org_abs_2503_11541
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Functional central limit theorem for the subgraph count of the voter model on dynamic random graphs
Baldassarri, Simone
Kriukov, Nikolai
Probability
In this paper we consider two-opinion voter models on dynamic random graphs, in which the joint dynamics of opinions and graphs acts as one-way feedback, i.e., edges appear and disappear over time depending on the opinions of the two connected vertices, while the opinion dynamics is not affected by the graph structure. Our goal is to investigate the joint evolution of the entries of a voter subgraph count vector, i.e., vector of subgraphs where each vertex has a specific opinion, in the regime that the number of vertices grows large. The main result of this paper is a functional central limit theorem. In particular, we prove that, under a proper centering and scaling, the joint functional of the vector of subgraph counts converges to a specific multidimensional Gaussian process.
title Functional central limit theorem for the subgraph count of the voter model on dynamic random graphs
topic Probability
url https://arxiv.org/abs/2503.11541