On Averaging and Mixing for Stochastic PDEs

Guan Huang; Sergei Kuksin

doi:10.1007/s10884-022-10202-w

On Averaging and Mixing for Stochastic PDEs

Guan Huang^*, Sergei Kuksin

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

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.

Original language	English
Journal	Journal of Dynamics and Differential Equations
DOIs	https://doi.org/10.1007/s10884-022-10202-w
Publication status	Accepted/In press - 2022
Externally published	Yes

Keywords

CGL equation
Krylov–Bogolyubov averaging
Mixing
NLW equation
Stochastic perturbations

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10.1007/s10884-022-10202-w

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@article{4c93f5a5b87a4f759d1f5581d80abe64,

title = "On Averaging and Mixing for Stochastic PDEs",

abstract = "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.",

keywords = "CGL equation, Krylov–Bogolyubov averaging, Mixing, NLW equation, Stochastic perturbations",

author = "Guan Huang and Sergei Kuksin",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.",

year = "2022",

doi = "10.1007/s10884-022-10202-w",

language = "English",

journal = "Journal of Dynamics and Differential Equations",

issn = "1040-7294",

publisher = "Springer New York",

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TY - JOUR

T1 - On Averaging and Mixing for Stochastic PDEs

AU - Huang, Guan

AU - Kuksin, Sergei

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

KW - CGL equation

KW - Krylov–Bogolyubov averaging

KW - Mixing

KW - NLW equation

KW - Stochastic perturbations

UR - http://www.scopus.com/inward/record.url?scp=85136578784&partnerID=8YFLogxK

U2 - 10.1007/s10884-022-10202-w

DO - 10.1007/s10884-022-10202-w

M3 - Article

AN - SCOPUS:85136578784

SN - 1040-7294

JO - Journal of Dynamics and Differential Equations

JF - Journal of Dynamics and Differential Equations

ER -

On Averaging and Mixing for Stochastic PDEs

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Keywords

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