Optimal Convergence Rates in the Averaging Principle for Slow–Fast SPDEs Driven by Multiplicative Noise-Reference-Cited by-同舟云学术

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Optimal Convergence Rates in the Averaging Principle for Slow–Fast SPDEs Driven by Multiplicative Noise

Published:2024-01-18 Issue: Volume: Page:
ISSN:2194-6701
Container-title:Communications in Mathematics and Statistics
language:en
Short-container-title:Commun. Math. Stat.

Author:

Ge Yi,Sun Xiaobin,Xie Yingchao

Funder

National Natural Science Foundation of China

Priority Academic Program Development of Jiangsu Higher Education Institutions

Qinglan Project of Jiangsu Province of China

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s40304-023-00363-5.pdf

Reference29 articles.

1. Bréhier, C.E.: Strong and weak orders in averaging for SPDEs. Stochastic Process. Appl. 122, 2553–2593 (2012)

2. Bréhier, C.E.: Analysis of an HMM time-discretization scheme for a system of stochastic PDEs. SIAM J. Numer. Anal. 51, 1185–1210 (2013)

3. Bréhier, C.E.: Orders of convergence in the averaging principle for SPDEs: the case of a stochastically forced slow component. Stochastic Process. Appl. 130, 3325–3368 (2020)

4. Bréhier, C.E., Debussche, A.: Kolmogorov equations and weak order analysis for SPDEs with nonlinear diffusion coefficient. J. Math. Pures Appl. 9(119), 193–254 (2018)

5. Cerrai, S.: A Khasminskii type averaging principle for stochastic reaction-diffusion equations. Ann. Appl. Probab. 19, 899–948 (2009)

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