Mean-field approximation and phase transitions in an Ising-voter model on directed regular random graphs

TL;DR

This paper investigates phase transitions in an Ising-voter model on directed regular random graphs, revealing how different dynamics and agent types influence the model's behavior and its alignment with mean-field predictions.

Contribution

It introduces heterogeneous modifications with voter and antivoter agents, analyzing their effects on phase transitions and the applicability of mean-field approximation.

Findings

Voter agents do not influence the Ising model dynamics.

Antivoter agents act as noise, weakening ferromagnetic order.

Heat-bath dynamics align with mean-field predictions, Metropolis does not.

Abstract

It is known that on directed graphs, the correlations between neighbours of a given site vanish and thus simple mean-field-like arguments can be used to describe exactly the behaviour of Ising-like systems. We analyse heterogeneous modifications of such models where a fraction of agents is driven by the voter or the antivoter dynamics. It turns out that voter agents do not affect the dynamics of the model and it behaves like a pure Ising model. Antivoter agents have a stronger impact since they act as a kind of noise, which weakens a ferromagnetic ordering. Only when Ising spins are driven by the heat-bath dynamics, the behaviour of the model is correctly described by the mean-field approximation. The Metropolis dynamics generates some additional correlations that render the mean-field approach approximate. Simulations on annealed networks agree with the mean-field approximation but for the model with antivoters and with the Metropolis dynamics only its heterogeneous version provides such an agreement. Calculation of the Binder cumulant confirms that critical points in our models with the heat-bath dynamics belong to the Ising mean-field universality class. For the Metropolis dynamics, the phase transition is most likely discontinuous, at least for not too many antivoters.