Majority-vote model on Opinion-Dependent Networks

Abstract

We study a nonequilibrium model with up-down symmetry and a noise parameter $q$ known as majority-vote model of M.J. Oliveira $1992$ on opinion-dependent network or Stauffer-Hohnisch-Pittnauer networks. By Monte Carlo simulations and finite-size scaling relations the critical exponents $\beta /\nu$, $\gamma /\nu$, and $1/\nu$ and points $q_c$ and $U^{\ast }$ are obtained. After extensive simulations, we obtain $\beta /\nu =0.230(3)$, $\gamma /\nu =0.535(2)$, and $1/\nu =0.475(8)$. The calculated values of the critical noise parameter and Binder cumulant are $q_c=0.166(3)$ and $U^{\ast }=0.288(3)$. Within the error bars, the exponents obey the relation $2\beta /\nu +\gamma /\nu =1$ and the results presented here demonstrate that the majority-vote model belongs to a different universality class than the equilibrium Ising model on Stauffer-Hohnisch-Pittnauer networks, but to the same class as majority-vote models on some other networks.

9 figures, accepted for publication in IJMPC

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• Statistical physics of social dynamics
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Cited by in corpus (1)

• The precursor of the critical transitions in majority vote model with the noise feedback from the vote layer