Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/80418
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Type: Journal article
Title: Macroscopic reduction for stochastic reaction-diffusion equations
Author: Wang, W.
Roberts, A.
Citation: IMA Journal of Applied Mathematics, 2013; 78(6):1237-1264
Publisher: Oxford Univ Press
Issue Date: 2013
ISSN: 0272-4960
1464-3634
Department: Faculty of Engineering, Computer & Mathematical Sciences
Statement of
Responsibility: 
W. Wang and A. J. Roberts
Abstract: The macroscopic behavior of dissipative stochastic partial differential equations usually can be described by a finite dimensional system. This article proves that a macroscopic reduced model may be constructed for stochastic reaction-diffusion equations with cubic nonlinearity by artificial separating the system into two distinct slow-fast time parts. An averaging method and a deviation estimate show that the macroscopic reduced model should be a stochastic ordinary equation which includes the random effect transmitted from the microscopic timescale due to the nonlinear interaction. Numerical simulations of an example stochastic heat equation confirms the predictions of this stochastic modelling theory. This theory empowers us to better model the long time dynamics of complex stochastic systems.
Keywords: stochastic reaction–diffusion equations; averaging; tightness; martingale
Rights: © The authors 2012.
RMID: 0020133608
DOI: 10.1093/imamat/hxs019
Grant ID: http://purl.org/au-research/grants/arc/DP0774311
http://purl.org/au-research/grants/arc/DP0988738
Appears in Collections:Mathematical Sciences publications

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