Numerical method for analyzing surface fluctuations

Cellular Automata Simulation of Two-Layer Ising and Potts Models

“…It is deterministic, reversible and nonergodic and also very fast method. Many works have been performed based on this model (Stauffer, 2000;Kremer & Wolf, 1992;Moukarzel & Parga, 1989;Stauffer, 1997;Glotzer & Stauffer, 1990;Zabolitzky & Herrmann, 1988;and MacIsaac, 1990). Although the Q2R model is deterministic and hence is fast, it was demonstrated that the probabilistic model of the CA like Metropolis algorithm (Metropolis et al, 1953) is more realistic for description of the Ising model even though the random number generation makes it slower.…”

Obtaining critical point and shift exponent for the anisotropic two-layer Ising and Potts models: Cellular automata approach

“…It is deterministic, reversible and nonergodic and also a very fast method. Many works have been performed based on this model [18][19][20][21][22][23][24]. Although the Q2R model is deterministic and hence is fast, it was demonstrated that the probabilistic model of the CA like Metropolis algorithm [25] is more realistic for the description of the Ising model even though the random number generation makes it slower.…”

A comparative study of 2d Ising model at different boundary conditions using Cellular Automata

“…The so called Q2R CA [9] (so named by Gérard Vichniac [10]) is a deterministic, reversible, nonergodic and fast method that is used for the microcanonical Ising model. Many authors have produced results based on this model [11,12,13]. The Creutz CA [14] has simulated the 2d Ising model successfully near the critical region under periodic bc and using this Creutz CA, the Ising model simulations in higher dimensions e.g., in 3D [15], 4D [16], 8D [17] have been done.…”