Accurate mean-field equation for voter model dynamics on scale-free networks

Fuente: arXiv
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Main Authors: Lücke, Marvin, Winkelmann, Stefanie, Koltai, Péter
Format: Preprint
Published: 2025
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author Lücke, Marvin
Winkelmann, Stefanie
Koltai, Péter
author_facet Lücke, Marvin
Winkelmann, Stefanie
Koltai, Péter
contents Understanding the emergent macroscopic behavior of dynamical systems on networks is a crucial but challenging task. One of the simplest and most effective methods to construct a reduced macroscopic model is given by mean-field theory. The resulting approximations perform well on dense and homogeneous networks but poorly on scale-free networks, which, however, are more realistic in many applications. In this paper, we introduce a modified version of the mean-field approximation for voter model dynamics on scale-free networks. The two main deviations from classical theory are that we use degree-weighted shares as coarse variables and that we introduce a correlation factor that can be interpreted as slowing down dynamics induced by interactions. We observe that, for moderate noise and comparable interaction rates, the correlation factor is only a property of the network and not of the state or of parameters of the process. This approach achieves a significantly smaller approximation error than standard methods without increasing dimensionality.
format Preprint
id arxiv_https___arxiv_org_abs_2509_13485
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Accurate mean-field equation for voter model dynamics on scale-free networks
Lücke, Marvin
Winkelmann, Stefanie
Koltai, Péter
Physics and Society
Understanding the emergent macroscopic behavior of dynamical systems on networks is a crucial but challenging task. One of the simplest and most effective methods to construct a reduced macroscopic model is given by mean-field theory. The resulting approximations perform well on dense and homogeneous networks but poorly on scale-free networks, which, however, are more realistic in many applications. In this paper, we introduce a modified version of the mean-field approximation for voter model dynamics on scale-free networks. The two main deviations from classical theory are that we use degree-weighted shares as coarse variables and that we introduce a correlation factor that can be interpreted as slowing down dynamics induced by interactions. We observe that, for moderate noise and comparable interaction rates, the correlation factor is only a property of the network and not of the state or of parameters of the process. This approach achieves a significantly smaller approximation error than standard methods without increasing dimensionality.
title Accurate mean-field equation for voter model dynamics on scale-free networks
topic Physics and Society
url https://arxiv.org/abs/2509.13485