Enhanced Mean Random Attractors for Nonautonomous Mean Random Dynamical Systems in Product Bochner Spaces

Renhai Wang , Pengyu Chen

Communications in Mathematics and Statistics ›› : 1 -30.

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Communications in Mathematics and Statistics ›› : 1 -30. DOI: 10.1007/s40304-024-00396-4
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Enhanced Mean Random Attractors for Nonautonomous Mean Random Dynamical Systems in Product Bochner Spaces

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Abstract

We develop the theory of mean random attractors of nonautonomous mean random dynamical systems proposed by Wang (J. Dynam. Differ. Equ., Proc. Amer. Math. Soc., J. Differ. Equ., 2019) in a general setting. Two types of enhanced mean random attractors are introduced by improving the weak compactness and weak attraction in a space of product of finitely many Bochner spaces uniformly over some infinite time-intervals. Then we establish some theoretical results for the existence, topology structures and relations of these enhanced mean random attractors by carefully analyzing the characters and properties of enhanced $\varOmega $-limit sets under the theory of weak topology. Our theoretical results are expected to be applied to many types of stochastic models. In particular, we apply these general results to a class of locally monotone and generally coercive stochastic PDEs, a fractional stochastic reaction–diffusion equation defined on ${\mathbb {R}}^N$, and a stochastic Schrödinger lattice system with a delay diffusion term defined on ${\mathbb {Z}}^N$.

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Renhai Wang, Pengyu Chen. Enhanced Mean Random Attractors for Nonautonomous Mean Random Dynamical Systems in Product Bochner Spaces. Communications in Mathematics and Statistics 1-30 DOI:10.1007/s40304-024-00396-4

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Funding

China Postdoctoral Science Foundation under grant numbers(2020TQ0053 and 2020M680456)

the research funds of Guizhou Normal University(11904/0522100)

Qianjiaoji([2022]124)

National Natural Science Foundation of China(12061063)

the Outstanding Youth Science Fund of Gansu Province(21JR7RA159)

Funds for Innovative Fundamental Research Group Project of Gansu Province(23JRRA684)

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