Contractive kinetic Langevin samplers beyond global Lipschitz continuity

Iosif Lytras; Panayotis Mertikopoulos

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arXiv · 2509.12031

Contractive kinetic Langevin samplers beyond global Lipschitz continuity

Iosif Lytras·Panayotis Mertikopoulos

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Abstract

In this paper, we examine the problem of sampling from log-concave distributions with (possibly) superlinear gradient growth under kinetic (underdamped) Langevin algorithms. Using a carefully tailored taming scheme, we propose two novel discretizations of the kinetic Langevin SDE, and we show that they are both contractive and satisfy a log-Sobolev inequality. Building on this, we establish a series of non-asymptotic bounds in $2$-Wasserstein distance between the law reached by each algorithm and the underlying target measure.

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BibTeX RIS

Iosif Lytras, Panayotis Mertikopoulos. 2025-09-15. Contractive kinetic Langevin samplers beyond global Lipschitz continuity. https://arxiv.org/abs/2509.12031

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