Majority-vote model with a bimodal distribution of noises

We consider the majority-vote dynamics where the noise parameter, associated with each spin on a two-dimensional square lattice, is a bimodally distributed random variable defined as q with probability ( 1 − f ) or zero with probability f , where 0 ≤ f ≤ 1 is the proportion of noiseless sites. We use Monte Carlo simulations and finite size scaling theory to characterize the ordered and disordered phases and study the phase transition of the model. We conclude that in the thermodynamic limit, the value of the critical noise below which there exists an ordered phase increases with f , the fraction of sites with zero noise. The calculation of the critical exponents shows that the introduction of disorder in the noise parameter does not alter the Ising critical behavior of the model system.