Volume 120, Number 1, October 2017
|Number of page(s)||6|
|Section||Interdisciplinary Physics and Related Areas of Science and Technology|
|Published online||27 December 2017|
Quenched mean-field theory for the majority-vote model on complex networks
1 School of Mathematics and Physics, Anhui Jianzhu University - Hefei, 230601, China
2 School of Physics and Material Science, Anhui University - Hefei, 230601, China
3 Department of Physics, Anqing Normal University - Anqing, 246011, China
Received: 28 August 2017
Accepted: 24 November 2017
The majority-vote (MV) model is one of the simplest nonequilibrium Ising-like model that exhibits a continuous order-disorder phase transition at a critical noise. In this paper, we present a quenched mean-field theory for the dynamics of the MV model on networks. We analytically derive the critical noise on arbitrary quenched unweighted networks, which is determined by the largest eigenvalue of a modified network adjacency matrix. By performing extensive Monte Carlo simulations on synthetic and real networks, we find that the performance of the quenched mean-field theory is superior to a heterogeneous mean-field theory proposed in a previous paper (Chen H. et al., Phys. Rev. E, 91 (2015) 022816), especially for directed networks.
PACS: 89.75.Hc – Networks and genealogical trees / 05.45.-a – Nonlinear dynamics and chaos / 64.60.Cn – Order-disorder transformations
© EPLA, 2017
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