Convergence of preconditioned Hamiltonian Monte Carlo on Hilbert spaces

Author:

Pidstrigach Jakiw1

Affiliation:

1. Institute of Mathematics, Universität Potsdam , Karl-Liebknecht-Straße 24-25, 14476 Potsdam, Germany

Abstract

Abstract In this article, we consider the preconditioned Hamiltonian Monte Carlo (pHMC) algorithm defined directly on an infinite-dimensional Hilbert space. In this context, and under a condition reminiscent of strong log-concavity of the target measure, we prove convergence bounds for adjusted pHMC in the standard 1-Wasserstein distance. The arguments rely on a synchronous coupling of two copies of pHMC, which is controlled by adapting elements from Bou-Rabee, Eberle and Zimmer (2020).

Publisher

Oxford University Press (OUP)

Subject

Applied Mathematics,Computational Mathematics,General Mathematics

Reference30 articles.

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4. Randomized Hamiltonian Monte Carlo;Bou-Rabee;Ann. Appl. Probab.,2017

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1. Geometric Ergodicity for Hamiltonian Monte Carlo on Compact Manifolds;SIAM Journal on Numerical Analysis;2023-12-07

2. Convergence of unadjusted Hamiltonian Monte Carlo for mean-field models;Electronic Journal of Probability;2023-01-01

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