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Main Authors: Yang, Qiu-Chen, Yin, Kun
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2603.03974
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author Yang, Qiu-Chen
Yin, Kun
author_facet Yang, Qiu-Chen
Yin, Kun
contents This paper establishes strong and weak convergence rates for slow-fast systems driven by $α$-stable processes with jump coefficients. Unlike existing studies on multiscale systems driven by additive Lévy white noise, our model incorporates multiplicative noise, which brings essential challenges in deriving the exponential ergodicity for the frozen process, particularly gradient estimates. We derive exponential ergodicity in two different ways: the coupling method and the spatial periodic method; then the gradient estimate is developed by heat kernel asymptotic expansion. Moreover, under sufficient Hölder regularity of the time-dependent coefficients of the slow process, we can yield an optimal strong convergence rate of order $1-\frac{1}{α_{2}}$ and a weak convergence rate of order 1. Furthermore, explicit formulas for the tangent map between tangent spaces of $S^{d-1}$ as well as its Jacobian determinant are obtained, where the map is induced by a nonlinear immersion.
format Preprint
id arxiv_https___arxiv_org_abs_2603_03974
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Strong and weak convergence rates for slow-fast system driven by multiplicative Lévy noises
Yang, Qiu-Chen
Yin, Kun
Probability
26D15, 60E15, 60G52, 60K37
This paper establishes strong and weak convergence rates for slow-fast systems driven by $α$-stable processes with jump coefficients. Unlike existing studies on multiscale systems driven by additive Lévy white noise, our model incorporates multiplicative noise, which brings essential challenges in deriving the exponential ergodicity for the frozen process, particularly gradient estimates. We derive exponential ergodicity in two different ways: the coupling method and the spatial periodic method; then the gradient estimate is developed by heat kernel asymptotic expansion. Moreover, under sufficient Hölder regularity of the time-dependent coefficients of the slow process, we can yield an optimal strong convergence rate of order $1-\frac{1}{α_{2}}$ and a weak convergence rate of order 1. Furthermore, explicit formulas for the tangent map between tangent spaces of $S^{d-1}$ as well as its Jacobian determinant are obtained, where the map is induced by a nonlinear immersion.
title Strong and weak convergence rates for slow-fast system driven by multiplicative Lévy noises
topic Probability
26D15, 60E15, 60G52, 60K37
url https://arxiv.org/abs/2603.03974