Quantitative ergodicity for the symmetric exclusion process with stationary initial data
Probability
2022-11-07 v2
Abstract
We consider the symmetric exclusion process on the -dimensional lattice with translational invariant and ergodic initial data. It is then known that as diverges the distribution of the process at time converges to a Bernoulli product measure. Assuming a summable decay of correlations of the initial data, we prove a quantitative version of this convergence by obtaining an explicit bound on the Ornstein -distance. The proof is based on the analysis of a two species exclusion process with annihilation.
Cite
@article{arxiv.2101.02487,
title = {Quantitative ergodicity for the symmetric exclusion process with stationary initial data},
author = {L. Bertini and N. Cancrini and G. Posta},
journal= {arXiv preprint arXiv:2101.02487},
year = {2022}
}