无界域上非自治分式随机反应-扩散方程的回拉测度吸引子

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Shaoyue Mi, Ran Li, Dingshi Li
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引用次数: 0

摘要

本文关注定义在 \(\mathbb {R}^{n}\) 上的非自治分式反应扩散方程的回拉测度吸引子。我们首先证明了这类方程的回拉量吸引子的存在性和唯一性。然后,当噪声强度 \(\varepsilon \)趋于零时,我们建立了这些吸引子的上半连续性。具体地说,我们应用解的尾部均匀估计来证明解的概率分布族的渐近紧凑性,以克服无界域上通常的 Sobolev 嵌入的非紧凑性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pullback Measure Attractors for Non-autonomous Fractional Stochastic Reaction-Diffusion Equations on Unbounded Domains

This paper is concerned with the pullback measure attractors of the non-autonomous fractional reaction-diffusion equations defined on \(\mathbb {R}^{n}\). We first prove the existence and uniqueness of pullback measure attractors for such equations. Then we establish the upper semi-continuity of these attractors as the noise intensity \(\varepsilon \) tends to zero. Specifically, we apply the uniform estimates on the tails of solutions to prove the asymptotic compactness of a family of probability distributions of solutions to overcome the non-compactness of usual Sobolev embeddings on unbounded domains.

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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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