# Poincar\'e and logarithmic Sobolev constants for metastable Markov chains via capacitary inequalities

## TL;DR

This paper introduces a new approach to analyze metastability in reversible Markov chains, providing precise transition times and sharp estimates on key functional inequalities, with applications to the Curie-Weiss model.

## Contribution

It defines a novel concept of metastability and derives asymptotically sharp bounds on Poincaré and logarithmic Sobolev constants using capacitary inequalities.

## Key findings

- Precise mean transition times between metastable sets
- Sharp asymptotic estimates of Poincaré and logarithmic Sobolev constants
- Application to the random field Curie-Weiss model

## Abstract

We investigate the metastable behavior of reversible Markov chains on possibly countable infinite state spaces. Based on a new definition of metastable Markov processes, we compute precisely the mean transition time between metastable sets. Under additional size and regularity properties of metastable sets, we establish asymptotic sharp estimates on the Poincar\'e and logarithmic Sobolev constant. The main ingredient in the proof is a capacitary inequality along the lines of V. Maz'ya that relates regularity properties of harmonic functions and capacities. We exemplify the usefulness of this new definition in the context of the random field Curie-Weiss model, where metastability and the additional regularity assumptions are verifiable.