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Main Authors: Bao, Jianhai, Majka, Mateusz B., Wang, Jian
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2412.19377
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author Bao, Jianhai
Majka, Mateusz B.
Wang, Jian
author_facet Bao, Jianhai
Majka, Mateusz B.
Wang, Jian
contents As a well-known fact, the classical Euler scheme works merely for SDEs with coefficients of linear growth. In this paper, we study a general framework of modified Euler schemes, which is applicable to SDEs with super-linear drifts and encompasses numerical methods such as the tamed Euler scheme and the truncated Euler scheme. On the one hand, by exploiting an approach based on the refined basic coupling, we show that all Euler recursions within our proposed framework are geometrically ergodic under a mixed probability distance (i.e., the total variation distance plus the $L^1$-Wasserstein distance) and the weighted total variation distance. On the other hand, by utilizing the coupling by reflection, we demonstrate that the tamed Euler scheme is geometrically ergodic under the $L^1$-Wasserstein distance. In addition, as an important application, we provide a quantitative $L^1$-Wasserstein error bound between the exact invariant probability measure of an SDE with super-linearity, and the invariant probability measure of the tamed Euler scheme which is its numerical counterpart.
format Preprint
id arxiv_https___arxiv_org_abs_2412_19377
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Geometric ergodicity of modified Euler schemes for SDEs with super-linearity
Bao, Jianhai
Majka, Mateusz B.
Wang, Jian
Probability
As a well-known fact, the classical Euler scheme works merely for SDEs with coefficients of linear growth. In this paper, we study a general framework of modified Euler schemes, which is applicable to SDEs with super-linear drifts and encompasses numerical methods such as the tamed Euler scheme and the truncated Euler scheme. On the one hand, by exploiting an approach based on the refined basic coupling, we show that all Euler recursions within our proposed framework are geometrically ergodic under a mixed probability distance (i.e., the total variation distance plus the $L^1$-Wasserstein distance) and the weighted total variation distance. On the other hand, by utilizing the coupling by reflection, we demonstrate that the tamed Euler scheme is geometrically ergodic under the $L^1$-Wasserstein distance. In addition, as an important application, we provide a quantitative $L^1$-Wasserstein error bound between the exact invariant probability measure of an SDE with super-linearity, and the invariant probability measure of the tamed Euler scheme which is its numerical counterpart.
title Geometric ergodicity of modified Euler schemes for SDEs with super-linearity
topic Probability
url https://arxiv.org/abs/2412.19377