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A Markov chain model for spatially distributed autocatalytic systems with a quadratic reaction rate is considered. An approximate solution for the local probability distribution is obtained in the form of a perturbation expansion for the regimes where diffusion is relatively fast. Using this approximate distribution, properties of the chemical wave fronts found in these autocatalytic systems are studied, and deviations of the minimum propagation velocity and the concentration profile from deterministic predictions are analyzed. A comparison with numerical results from lattice-gas automaton simulations is also provided., Comment: 10 pages, 2 figures. To appear in J. Chem. Phys

Spatially-distributed, nonequilibrium chemical systems described by a Markov chain model are considered. The evolution of such systems arises from a combination of local birth-death reactive events and random walks executed by the particles on a lattice. The parameter \gamma, the ratio of characteristic time scales of reaction and diffusion, is used to gauge the relative contributions of these two processes to the overall dynamics. For the case of relatively fast diffusion, i.e. \gamma << 1, an approximate solution to the Markov chain in the form of a perturbation expansion in powers of \gamma is derived. Kinetic equations for the average concentrations differ from the mass-action law and contain memory terms. For a reaction- diffusion system with Willamowski-Rossler reaction mechanism, we further derive the following two results: a) in the limit of \gamma --> 0 these memory terms vanish and the mass-action law is recovered; b) the memory kernel is found to assume a simple exponential form. A comparison with numerical results from lattice gas automaton simulations is also carried out., Comment: 18 pages, 5 figures. To appear in J. Chem. Phys