Efficient Langevin sampling with position-dependent diffusion

Fuente: arXiv
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Auteurs principaux: Bronasco, Eugen, Leimkuhler, Benedict, Phillips, Dominic, Vilmart, Gilles
Format: Preprint
Publié: 2025
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author Bronasco, Eugen
Leimkuhler, Benedict
Phillips, Dominic
Vilmart, Gilles
author_facet Bronasco, Eugen
Leimkuhler, Benedict
Phillips, Dominic
Vilmart, Gilles
contents We introduce a numerical method for Brownian dynamics with position dependent diffusion tensor which is second order accurate for sampling the invariant measure while requiring only one force evaluation per timestep. Analysis of the sampling bias is performed using the algebraic framework of exotic aromatic Butcher-series. Numerical experiments confirm the theoretical order of convergence and illustrate the efficiency of the new method.
format Preprint
id arxiv_https___arxiv_org_abs_2501_02943
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Efficient Langevin sampling with position-dependent diffusion
Bronasco, Eugen
Leimkuhler, Benedict
Phillips, Dominic
Vilmart, Gilles
Numerical Analysis
60H35, 37M25, 65L06, 41A58, 05C05
We introduce a numerical method for Brownian dynamics with position dependent diffusion tensor which is second order accurate for sampling the invariant measure while requiring only one force evaluation per timestep. Analysis of the sampling bias is performed using the algebraic framework of exotic aromatic Butcher-series. Numerical experiments confirm the theoretical order of convergence and illustrate the efficiency of the new method.
title Efficient Langevin sampling with position-dependent diffusion
topic Numerical Analysis
60H35, 37M25, 65L06, 41A58, 05C05
url https://arxiv.org/abs/2501.02943