Abstract

We study the joint effect of the non-linearity of interactions and noise on coevolutionary dynamics. We choose the coevolving voter model as a prototype framework for this problem. By numerical simulations and analytical approximations we find three main phases that differ in the absolute magnetisation and the size of the largest component: a consensus phase, a coexistence phase, and a dynamical fragmentation phase. More detailed analysis reveals inner differences in these phases, allowing us to divide two of them further. In the consensus phase we can distinguish between a weak or alternating consensus and a strong consensus, in which the system remains in the same state for the whole realisation of the stochastic dynamics. In the coexistence phase we distinguish a fully-mixing phase and a structured coexistence phase, where the number of active links drops significantly due to the formation of two homogeneous communities. Our numerical observations are supported by an analytical description using a pair approximation approach and an ad-hoc calculation for the transition between the coexistence and dynamical fragmentation phases. Our work shows how simple interaction rules including the joint effect of non-linearity, noise, and coevolution lead to complex structures relevant in the description of social systems.

Highlights

  • We study the joint effect of the non-linearity of interactions and noise on coevolutionary dynamics

  • In this paper we introduce a coevolving voter model (CVM) in which noise and non-linearities are jointly taken into account

  • We explore the space of possible values of the parameters ( p, q, ǫ ) by means of computer simulations and analytical approximations

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Summary

Introduction

We study the joint effect of the non-linearity of interactions and noise on coevolutionary dynamics. Our work shows how simple interaction rules including the joint effect of non-linearity, noise, and coevolution lead to complex structures relevant in the description of social systems. There are three important elements that have been considered within the general research area of exploring consequences of empirically identified mechanisms that modify interactions in simple models: coevolution, non-linearity and noise. Coevolution models incorporate microscopic assumptions in better agreement with empirical observations, and they produce new macroscopic results Another essential feature of many real-world systems is the non-linearity associated with non-dyadic interactions. From a single node point of view it means selecting one of its neighbours at random for the interaction This leads to a linear relation between the number of neighbours in a given state and the probability of choosing one of them. The coevolving voter model on a certain class of hypergraphs has been c­ onsidered[30]

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