AbstractWe prove exponential convergence to the invariant measure, in the total variation norm, for solutions of SDEs driven by α-stable noises in finite and in infinite dimensions. Two approaches are used. The first one is based on Liapunov’s function approach by Harris, and the second on Doeblin’s coupling argument in [8]. Irreducibility and uniform strong Feller property play an essential role in both approaches. We concentrate on two classes of Markov processes: solutions of finite dimensional equations, introduced in [27], with Hölder continuous drift and a general, non-degenerate, symmetric α-stable noise, and infinite dimensional parabolic systems, introduced in [29], with Lipschitz drift and cylindrical α-stable noise. We show that ...
International audienceWe prove the strong Feller property and exponential mixing for 3D stochastic N...
AbstractThis paper discusses quantitative bounds on the convergence rates of Markov chains, under co...
We prove pathwise (hence strong) uniqueness of solutions to stochastic evolution equations in Hilber...
We prove exponential convergence to the invariant measure, in the total variation norm, for solution...
AbstractMild sufficient conditions for exponential ergodicity of a Markov process defined as the sol...
summary:We study ergodic properties of stochastic dissipative systems with additive noise. We show t...
summary:We study ergodic properties of stochastic dissipative systems with additive noise. We show t...
International audienceWe study a damped stochastic non-linear Schrödinger (NLS) equation driven by a...
We show how gradient estimates for transition semigroups can be used to establish exponential mixin...
summary:We study ergodic properties of stochastic dissipative systems with additive noise. We show t...
We prove pathwise (hence strong) uniqueness of solutions to stochastic evolution equations in Hilber...
We develop a general framework for studying ergodicity of order-preserving Markov semigroups. We est...
We prove existence and uniqueness of the invariant measure and exponential mixing in the total-varia...
AbstractMild sufficient conditions for exponential ergodicity of a Markov process defined as the sol...
International audienceWe establish a general criterion which ensures exponential mixing of parabolic...
International audienceWe prove the strong Feller property and exponential mixing for 3D stochastic N...
AbstractThis paper discusses quantitative bounds on the convergence rates of Markov chains, under co...
We prove pathwise (hence strong) uniqueness of solutions to stochastic evolution equations in Hilber...
We prove exponential convergence to the invariant measure, in the total variation norm, for solution...
AbstractMild sufficient conditions for exponential ergodicity of a Markov process defined as the sol...
summary:We study ergodic properties of stochastic dissipative systems with additive noise. We show t...
summary:We study ergodic properties of stochastic dissipative systems with additive noise. We show t...
International audienceWe study a damped stochastic non-linear Schrödinger (NLS) equation driven by a...
We show how gradient estimates for transition semigroups can be used to establish exponential mixin...
summary:We study ergodic properties of stochastic dissipative systems with additive noise. We show t...
We prove pathwise (hence strong) uniqueness of solutions to stochastic evolution equations in Hilber...
We develop a general framework for studying ergodicity of order-preserving Markov semigroups. We est...
We prove existence and uniqueness of the invariant measure and exponential mixing in the total-varia...
AbstractMild sufficient conditions for exponential ergodicity of a Markov process defined as the sol...
International audienceWe establish a general criterion which ensures exponential mixing of parabolic...
International audienceWe prove the strong Feller property and exponential mixing for 3D stochastic N...
AbstractThis paper discusses quantitative bounds on the convergence rates of Markov chains, under co...
We prove pathwise (hence strong) uniqueness of solutions to stochastic evolution equations in Hilber...