Mixing of metastable diffusion processes with Gibbs invariant distribution

In this article, we study the mixing properties of metastable diffusion processes which possess a Gibbs invariant distribution. For systems with multiple stable equilibria, so-called metastable transitions between these equilibria are required for mixing since the unique invariant distribution is concentrated on these equilibria. Consequently, these systems exhibit slower mixing compared to those with a unique stable equilibrium, as analyzed in Barrera and Jara (Ann. Appl. Probab. 30:1164–1208, 2020). Our proof is based on the theory of metastability, which is a primary tool for studying systems with multiple stable equilibria. Within this framework, we compute the total variation distance between the distribution of the diffusion process and its invariant distribution for any time scale larger than ϵ−1. Finally, we derive precise asymptotics for the mixing time.

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Publication Details

Journal
Electronic Journal of Probability
Published
2025-01-01
DOI
https://doi.org/10.1214/25-ejp1321
Primary Topic
stochastic dynamics and bifurcation
Type
article
Field-Weighted Citation Impact
0.00

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article

Mixing of metastable diffusion processes with Gibbs invariant distribution

Jungkyoung Lee
Electronic Journal of Probability
stochastic dynamics and bifurcation
article

Mixing of metastable diffusion processes with Gibbs invariant distribution

Jungkyoung Lee
article en

Abstract

In this article, we study the mixing properties of metastable diffusion processes which possess a Gibbs invariant distribution. For systems with multiple stable equilibria, so-called metastable transitions between these equilibria are required for mixing since the unique invariant distribution is concentrated on these equilibria. Consequently, these systems exhibit slower mixing compared to those with a unique stable equilibrium, as analyzed in Barrera and Jara (Ann. Appl. Probab. 30:1164–1208, 2020). Our proof is based on the theory of metastability, which is a primary tool for studying systems with multiple stable equilibria. Within this framework, we compute the total variation distance between the distribution of the diffusion process and its invariant distribution for any time scale larger than ϵ−1. Finally, we derive precise asymptotics for the mixing time.

Electronic Journal of ProbabilityVol. 30(none)
Korea Institute for Advanced Study (KR)
National Research Foundation, National Research Foundation of Korea, Ministry of Science and ICT, South Korea
Openalex Percentile: Top 94%
stochastic dynamics and bifurcation
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Mixing of metastable diffusion processes with Gibbs invariant distribution — Jungkyoung Lee · Electronic Journal of Probability (2025) | TGRS Research Map | TGRS