English

Convergence of kinetic Langevin samplers for non-convex potentials

Probability 2025-08-20 v2 Numerical Analysis Numerical Analysis

Abstract

We study three kinetic Langevin samplers including the Euler discretization, the BU and the UBU splitting scheme. We provide contraction results in L1L^1-Wasserstein distance for non-convex potentials. These results are based on a carefully tailored distance function and an appropriate coupling construction. Additionally, the error in the L1L^1-Wasserstein distance between the true target measure and the invariant measure of the discretization scheme is bounded. To get an ε\varepsilon-accuracy in L1L^1-Wasserstein distance, we show complexity guarantees of order O(d/ε)\mathcal{O}(\sqrt{d}/\varepsilon) for the Euler scheme and O(d1/4/ε)\mathcal{O}(d^{1/4}/\sqrt{\varepsilon}) for the UBU scheme under appropriate assumptions on the target measure. The results are applicable to interacting particle systems and provide bounds for sampling probability measures of mean-field type.

Keywords

Cite

@article{arxiv.2405.09992,
  title  = {Convergence of kinetic Langevin samplers for non-convex potentials},
  author = {Katharina Schuh and Peter A. Whalley},
  journal= {arXiv preprint arXiv:2405.09992},
  year   = {2025}
}

Comments

50 pages, 4 figures