Large Deviations for Stochastic Models of Two-Dimensional Second Grade Fluids

Weak Solutions of a Stochastic Model for Two-Dimensional Second Grade Fluids

Strong solution for a stochastic model of two-dimensional second grade fluids : existence, uniqueness and asymptotic behaviour

We investigate a stochastic evolution equation for the motion of a second grade fluid filling a bounded domain of R. Global existence and uniqueness of strong probabilistic solution is established. In contrast to previous results on this model we show that the sequence of Galerkin approximation converges in mean square to the exact strong probabilistic solution of the problem. We also give two ...

Large Deviations for Infinite Dimensional Stochastic Dynamical Systems

The large deviations analysis of solutions to stochastic differential equations and related processes is often based on approximation. The construction and justification of the approximations can be onerous, especially in the case where the process state is infinite dimensional. In this paper we show how such approximations can be avoided for a variety of infinite dimensional models driven by s...

Large Deviations for Stochastic Processes

The purpose of these lectures is to introduce you to the basics of large deviation theory. The emphasis will be on the use of compactness ideas (more extensive results are in Puhalskii [13]). Other approaches to large deviation theory are considered in Dembo and Zeitouni [3], den Hollander [4], Deuschel and Stroock [6], Dupuis and Ellis [7], Freidlin and Wentzell [9], Kallenberg [12], Shwartz a...

Large Deviations for Stochastic Processes

The notes are devoted to results on large deviations for sequences of Markov processes following closely the book by Feng and Kurtz ([FK06]). We outline how convergence of Fleming’s nonlinear semigroups (logarithmically transformed nonlinear semigroups) implies large deviation principles analogous to the use of convergence of linear semigroups in weak convergence. The latter method is based on ...