Contractive kinetic Langevin samplers beyond global Lipschitz continuity

• URL: http://arxiv.org/abs/2509.12031v1
• Date: Mon, 15 Sep 2025 15:14:45 GMT
• Title: Contractive kinetic Langevin samplers beyond global Lipschitz continuity
• Authors: Iosif Lytras, Panagiotis Mertikopoulos,
• Abstract summary: We show that two novel discretizations of the kinetic Langevin SDE satisfy a log-Sobolev inequality.<n>We establish a series of non-asymptotic bounds in $2$-Wasserstein distance between the law reached by each algorithm and the underlying measure.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• 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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