172 research outputs found

    Random attractors for stochastic evolution equations driven by fractional Brownian motion

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    The main goal of this article is to prove the existence of a random attractor for a stochastic evolution equation driven by a fractional Brownian motion with H(1/2,1)H\in (1/2,1). We would like to emphasize that we do not use the usual cohomology method, consisting of transforming the stochastic equation into a random one, but we deal directly with the stochastic equation. In particular, in order to get adequate a priori estimates of the solution needed for the existence of an absorbing ball, we will introduce stopping times to control the size of the noise. In a first part of this article we shall obtain the existence of a pullback attractor for the non-autonomous dynamical system generated by the pathwise mild solution of an nonlinear infinite-dimensional evolution equation with non--trivial H\"older continuous driving function. In a second part, we shall consider the random setup: stochastic equations having as driving process a fractional Brownian motion with H(1/2,1)H\in (1/2,1). Under a smallness condition for that noise we will show the existence and uniqueness of a random attractor for the stochastic evolution equation

    The random case of Conley's theorem

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    The well-known Conley's theorem states that the complement of chain recurrent set equals the union of all connecting orbits of the flow ϕ\phi on the compact metric space XX, i.e. XCR(ϕ)=[B(A)A]X-\mathcal{CR}(\phi)=\bigcup [B(A)-A], where CR(ϕ)\mathcal{CR}(\phi) denotes the chain recurrent set of ϕ\phi, AA stands for an attractor and B(A)B(A) is the basin determined by AA. In this paper we show that by appropriately selecting the definition of random attractor, in fact we define a random local attractor to be the ω\omega-limit set of some random pre-attractor surrounding it, and by considering appropriate measurability, in fact we also consider the universal σ\sigma-algebra Fu\mathcal F^u-measurability besides F\mathcal F-measurability, we are able to obtain the random case of Conley's theorem.Comment: 15 page

    Smooth stable and unstable manifolds for stochastic partial differential equations

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    Invariant manifolds are fundamental tools for describing and understanding nonlinear dynamics. In this paper, we present a theory of stable and unstable manifolds for infinite dimensional random dynamical systems generated by a class of stochastic partial differential equations. We first show the existence of Lipschitz continuous stable and unstable manifolds by the Lyapunov-Perron's method. Then, we prove the smoothness of these invariant manifolds

    Random attractors for degenerate stochastic partial differential equations

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    We prove the existence of random attractors for a large class of degenerate stochastic partial differential equations (SPDE) perturbed by joint additive Wiener noise and real, linear multiplicative Brownian noise, assuming only the standard assumptions of the variational approach to SPDE with compact embeddings in the associated Gelfand triple. This allows spatially much rougher noise than in known results. The approach is based on a construction of strictly stationary solutions to related strongly monotone SPDE. Applications include stochastic generalized porous media equations, stochastic generalized degenerate p-Laplace equations and stochastic reaction diffusion equations. For perturbed, degenerate p-Laplace equations we prove that the deterministic, infinite dimensional attractor collapses to a single random point if enough noise is added.Comment: 34 pages; The final publication is available at http://link.springer.com/article/10.1007%2Fs10884-013-9294-

    The random case of Conley's theorem: III. Random semiflow case and Morse decomposition

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    In the first part of this paper, we generalize the results of the author \cite{Liu,Liu2} from the random flow case to the random semiflow case, i.e. we obtain Conley decomposition theorem for infinite dimensional random dynamical systems. In the second part, by introducing the backward orbit for random semiflow, we are able to decompose invariant random compact set (e.g. global random attractor) into random Morse sets and connecting orbits between them, which generalizes the Morse decomposition of invariant sets originated from Conley \cite{Con} to the random semiflow setting and gives the positive answer to an open problem put forward by Caraballo and Langa \cite{CL}.Comment: 21 pages, no figur
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