A duality formula and a particle Gibbs sampler for continuous time Feynman-Kac measures on path spaces

TL;DR

This paper introduces a duality formula and a reversible particle Gibbs-Glauber sampler for continuous time Feynman-Kac measures on path spaces, extending existing methods from discrete to continuous models.

Contribution

It develops a new duality formula and a particle Gibbs sampler for continuous time Feynman-Kac measures, with convergence and chaos propagation estimates.

Findings

Reversible particle Gibbs-Glauber sampler designed for continuous time models

Quantitative convergence rate estimates for the sampler

First such results for continuous time Feynman-Kac measures

Abstract

Continuous time Feynman-Kac measures on path spaces are central in applied probability, partial differential equation theory, as well as in quantum physics. This article presents a new duality formula between normalized Feynman-Kac distribution and their mean field particle interpretations. Among others, this formula allows us to design a reversible particle Gibbs-Glauber sampler for continuous time Feynman-Kac integration on path spaces. This result extends the particle Gibbs samplers introduced by Andrieu-Doucet-Holenstein [2] in the context of discrete generation models to continuous time Feynman-Kac models and their interacting jump particle interpretations. We also provide new propagation of chaos estimates for continuous time genealogical tree based particle models with respect to the time horizon and the size of the systems. These results allow to obtain sharp quantitative estimates of the convergence rate to equilibrium of particle Gibbs-Glauber samplers. To the best of our knowledge these results are the first of this kind for continuous time Feynman-Kac measures.