Classification of Stationary distributions for the stochastic vertex models

2022/05/21 by Yier Lin, Lin, Yier
Mathematics · #Random Matrices and Applications #Markov Chains and Monte Carlo Methods

paper · pdf · doi:10.48550/arxiv.2205.10654

Abstract

In this paper, we study the stationary distributions for the stochastic vertex models. Our main focus is the stochastic six vertex (S6V) model. We show that the extremal stationary distributions of the S6V model are given by product Bernoulli measures. Moreover, for the S6V model under a moving frame of speed 1, we show that the extremal stationary distributions are given by product Bernoulli measures and blocking measures. Finally, we generalize our results to the stochastic higher spin six vertex model. Our proof relies on the coupling of the S6V models introduced in [Aggarwal, 2020], the analysis of current and the method of fusion.

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