Critical noise of majority-vote model on complex networks

H Chen, C Shen, G He, H Zhang, Z Hou - Physical Review E, 2015 - APS
H Chen, C Shen, G He, H Zhang, Z Hou
Physical Review E, 2015APS
The majority-vote model with noise is one of the simplest nonequilibrium statistical model
that has been extensively studied in the context of complex networks. However, the
relationship between the critical noise where the order-disorder phase transition takes place
and the topology of the underlying networks is still lacking. In this paper, we use the
heterogeneous mean-field theory to derive the rate equation for governing the model's
dynamics that can analytically determine the critical noise fc in the limit of infinite network …
The majority-vote model with noise is one of the simplest nonequilibrium statistical model that has been extensively studied in the context of complex networks. However, the relationship between the critical noise where the order-disorder phase transition takes place and the topology of the underlying networks is still lacking. In this paper, we use the heterogeneous mean-field theory to derive the rate equation for governing the model's dynamics that can analytically determine the critical noise in the limit of infinite network size . The result shows that depends on the ratio of to , where and are the average degree and the  order moment of degree distribution, respectively. Furthermore, we consider the finite-size effect where the stochastic fluctuation should be involved. To the end, we derive the Langevin equation and obtain the potential of the corresponding Fokker-Planck equation. This allows us to calculate the effective critical noise at which the susceptibility is maximal in finite-size networks. We find that the decays with in a power-law way and vanishes for . All the theoretical results are confirmed by performing the extensive Monte Carlo simulations in random -regular networks, Erdös-Rényi random networks, and scale-free networks.
American Physical Society
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