On Averaging and Mixing for Stochastic PDEs

We examine the convergence in the Krylov–Bogolyubov averaging for nonlinear stochastic perturbations of linear PDEs with pure imaginary spectrum and show that if the involved effective equation is mixing, then the convergence is uniform in time. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Авторы
Huang G. , Kuksin S.
Номер выпуска
3
Язык
Английский
Страницы
2041-2056
Статус
Опубликовано
Том
36
Год
2024
Организации
  • 1 Yau Mathematical Sciences Center, Tsinghua University, Beijing, China
  • 2 Institut de Mathémathiques de Jussieu–Paris Rive Gauche, CNRS, UMR 7586, Sorbonne Paris Cité, Université Paris Diderot, Paris, 75013, France
  • 3 Peoples’ Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya St, Moscow, 117198, Russian Federation
Ключевые слова
CGL equation; Krylov–Bogolyubov averaging; Mixing; NLW equation; Stochastic perturbations
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