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Main Authors: Hao, Zimo, Lê, Khoa, Ling, Chengcheng
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2602.18411
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author Hao, Zimo
Lê, Khoa
Ling, Chengcheng
author_facet Hao, Zimo
Lê, Khoa
Ling, Chengcheng
contents We study the weak convergence of a generic tamed Euler-Maruyama scheme for kinetic stochastic differential equations (SDEs) with integrable drifts. We show that the marginal density of the considered scheme converges at rate 1/2 to the corresponding marginal density of the SDE. The convergence rate is independent from the criticality gap, which is new compared to previous results.
format Preprint
id arxiv_https___arxiv_org_abs_2602_18411
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Weak approximation of kinetic SDEs: closing the criticality gap
Hao, Zimo
Lê, Khoa
Ling, Chengcheng
Probability
We study the weak convergence of a generic tamed Euler-Maruyama scheme for kinetic stochastic differential equations (SDEs) with integrable drifts. We show that the marginal density of the considered scheme converges at rate 1/2 to the corresponding marginal density of the SDE. The convergence rate is independent from the criticality gap, which is new compared to previous results.
title Weak approximation of kinetic SDEs: closing the criticality gap
topic Probability
url https://arxiv.org/abs/2602.18411