Asymptotically autonomous robustness in Probability of non-autonomous random attractors for stochastic convective Brinkman-Forchheimer equations on $\mathbb{R}^3$
Kush Kinra, Manil T. Mohan, Renhai Wang

TL;DR
This paper investigates the robustness of non-autonomous random attractors for 3D stochastic convective Brinkman-Forchheimer equations on \\mathbb{R}^3, focusing on their asymptotic behavior as time tends to negative infinity under stochastic influences.
Contribution
It establishes the asymptotic robustness of non-autonomous random attractors for stochastic 3D CBF equations with specific conditions on the nonlinearity and noise, using Kuratowski's measure of noncompactness.
Findings
Proves robustness of attractors for r > 3 with any \\beta, \\mu > 0.
Shows robustness for r = 3 when 2\\beta\\mu \\geq 1.
Develops a method based on Kuratowski's measure for uniform pullback asymptotic compactness.
Abstract
This article is concerned with the \emph{asymptotically autonomous robustness} (almost surely and in probability) of non-autonomous random attractors for two stochastic versions of 3D convective Brinkman-Forchheimer (CBF) equations defined on the whole space : with initial and boundary vanishing conditions, where , and is a given time-dependent external force field. By the asymptotically autonomous robustness of a non-autonomous random attractor we mean its time-section…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStochastic processes and financial applications · Advanced Mathematical Modeling in Engineering · Numerical methods in inverse problems
