Efficient Langevin sampling with position-dependent diffusion
Numerical Analysis
2025-01-09 v2 Numerical Analysis
Abstract
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.
Cite
@article{arxiv.2501.02943,
title = {Efficient Langevin sampling with position-dependent diffusion},
author = {Eugen Bronasco and Benedict Leimkuhler and Dominic Phillips and Gilles Vilmart},
journal= {arXiv preprint arXiv:2501.02943},
year = {2025}
}
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31 pages