Transient bimodality in interacting particle systems

We consider a system of spins which have values ±1 and evolve according to a jump Markov process whose generator is the sum of two generators, one describing a spin-flipGlauber process, the other aKawasaki (stirring) evolution. It was proven elsewhere that if the Kawasaki dynamics is speeded up by a factor ε−2, then, in the limit ε → 0 (continuum limit), propagation of chaos holds and the local magnetization solves a reaction-diffusion equation. We choose the parameters of the Glauber interaction so that the potential of the reaction term in the reaction-diffusion equation is a double-well potential with quartic maximum at the origin. We assume further that for each ε the system is in a finite interval ofZ with ε−1 sites and periodic boundary conditions. We specify the initial measure as the product measure with 0 spin average, thus obtaining, in the continuum limit, a constant magnetic profile equal to 0, which is a stationary unstable solution to the reaction-diffusion equation. We prove that at times of the order ε−1/2 propagation of chaos does not hold any more and, in the limit as ε → 0, the state becomes a nontrivial superposition of Bernoulli measures with parameters corresponding to the minima of the reaction potential. The coefficients of such a superposition depend on time (on the scale ε−1/2) and at large times (on this scale) the coefficient of the term corresponding to the initial magnetization vanishes (transient bimodality). This differs from what was observed by De Masi, Presutti, and Vares, who considered a reaction potential with quadratic maximum and no bimodal effect was seen, as predicted by Broggi, Lugiato, and Colombo.

[1]  T. Liggett Interacting Particle Systems , 1985 .

[2]  Errico Presutti,et al.  Escape from the unstable equilibrium in a random process with infinitely many interacting particles , 1986 .

[3]  Ellen Saada,et al.  Microscopic structure at the shock in the asymmetric simple exclusion , 1989 .

[4]  P. Billingsley,et al.  Convergence of Probability Measures , 1969 .

[5]  Lebowitz,et al.  Rigorous derivation of reaction-diffusion equations with fluctuations. , 1985, Physical review letters.

[6]  D. W. Stroock,et al.  Multidimensional Diffusion Processes , 1979 .

[7]  Herbert Spohn,et al.  Microscopic models of hydrodynamic behavior , 1988 .

[8]  Pablo A. Ferrari,et al.  Reaction-diffusion equations for interacting particle systems , 1986 .

[9]  G. Nicolis,et al.  Stochastic theory of adiabatic explosion , 1983 .

[10]  Errico Presutti,et al.  The weakly asymmetric simple exclusion process , 1989 .

[11]  E. Presutti,et al.  Convergence of stochastic cellular automation to Burger's equation: fluctuations and stability , 1988 .

[12]  Antonio Galves,et al.  Metastable behavior of stochastic dynamics: A pathwise approach , 1984 .

[13]  G. Jona-Lasinio,et al.  On the stochastic quantization of field theory , 1985 .

[14]  D. Stroock,et al.  Generalized Ornstein-Uhlenbeck Processes and Infinite Particle Branching Brownian Motions , 1978 .

[15]  L. Rogers Stochastic differential equations and diffusion processes: Nobuyuki Ikeda and Shinzo Watanabe North-Holland, Amsterdam, 1981, xiv + 464 pages, Dfl.175.00 , 1982 .

[16]  D. Dawson Critical dynamics and fluctuations for a mean-field model of cooperative behavior , 1983 .