Probabilistic cellular automata model for reaction diffusion systems

Abstract

Class of cellular automata (CA) for modeling reaction diffusion systems has been presented. The construction of the CA is general enough to be applicable to large class of reaction

diffusion equations. The automata are based on running average procedure and on probabilistic table look up to implement diffusion reactions. The evolution of probabilistic CA simulates a spatially distributed process, given by a partial differential equation (PDE). The solutions are very isotropic despite the discreteness and the anisotropic nature of the CA. The adverse effects of discretization are overcome by the use of probabilistic rules. In order to obtain the assurance of the proposed method, the probabilistic CA approach for evolution of reaction diffusion process usually given by PDE is proposed.