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Gaussian estimates for symmetric simple exclusion processes

Abstract

We prove Gaussian tail estimates for the transition probability of nn particles evolving as symmetric exclusion processes on \bb Z^d, improving results obtained in \cite{l}. We derive from this result a non-equilibrium Boltzmann-Gibbs principle for the symmetric simple exclusion process in dimension 1 starting from a product measure with slowly varying parameter

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