Effective surface-tension in the noise-reduced voter model

TL;DR

This paper demonstrates that adding memory through noise reduction in the voter model induces an effective surface tension, leading to curvature-driven coarsening similar to phase separation dynamics.

Contribution

It introduces a simple way to incorporate memory into the voter model, revealing how noise reduction modifies scaling behavior and induces surface tension effects.

Findings

Memory addition modifies the scaling behavior of the voter model.

The model exhibits curvature-driven coarsening similar to Cahn-Allen dynamics.

Mean-field analysis explains the origin of surface tension and coarsening mechanism.

Abstract

The role of memory is crucial in determining the properties of many dynamical processes in statistical physics. We show that the simple addition of memory, in the form of noise reduction, modifies the overall scaling behavior of the voter model, introducing an effective surface tension analogous to that recently observed in memory-based models of social dynamics. The numerical results for low-dimensional lattices show a scaling behavior in good agreement with usual Cahn-Allen curvature-driven coarsening, even though slower preasymptotic regimes may be observed depending on the memory properties. Simple arguments and a mean-field analysis provide an explanation for the observed behavior that clarifies the origin of surface tension and the mechanism underlying the coarsening process.