The Dual Potential, the involution kernel and Transport in Ergodic Optimization

TL;DR

This paper explores the properties of maximizing measures in ergodic optimization, the dual potentials via involution kernels, and the optimal transport problem between these measures, focusing on the graph property of the optimal plan.

Contribution

It introduces a framework connecting ergodic optimization, involution kernels, and optimal transport, analyzing the structure of optimal plans and dual potentials.

Findings

Characterization of maximizing measures for Holder potentials.

Analysis of the dual potential and involution kernel relationship.

Investigation of the graph property of the optimal transport plan.

Abstract

Consider the shift $\sigma$ acting on the Bernoulli space $\Sigma={1,2,...,n}^\mathbb{N}$. We denote $\hat{\Sigma}= {1,2,...,n}^\mathbb{Z}$. We analyze several properties of the maximizing probability $\mu_{\infty,A}$ of a Holder potential $A: \Sigma \to \mathbb{R}$. Associated to $A(x)$, via the involution kernel, $W: \hat{\Sigma} \to \mathbb{R}$, it is known that can we get the dual potential $A^*(y)$, where $(x,y)\in \hat{\Sigma}$. Consider $\mu_{\infty, A^*}$ a maximizing probability for $A^*$. We would like to consider the transport problem from $\mu_{\infty,A}$ to $\mu_{\infty,A^*}$. In this case, it is natural to consider the cost function $c(x,y) = I(x) - W(x,y) +\gamma $, where $I$ is the deviation function. The pair of functions for the Kantorovich Transport dual Problem are $(-V,-V^*$), where we denote the two calibrated sub-actions by $V$ and $V^*$, respectively, for $A$ and $A^*$ for $\mu_{\infty,A}$. We analyze the graph property for the optimal plan $\hat{\mu}$.