On maximal inequalities for purely discontinuous martingales in infinite dimensions

The purpose of this paper is to give a survey of a class of maximal inequalities for purely discontinuous martingales, as well as for stochastic integral and convolutions with respect to Poisson measures, in infinite dimensional spaces. Such maximal inequalities are important in the study of stochastic partial differential equations with noise of jump type.Comment: 19 pages, no figure

Well-posedness and asymptotic behavior for stochastic reaction-diffusion equations with multiplicative Poisson noise

We establish well-posedness in the mild sense for a class of stochastic semilinear evolution equations with a polynomially growing quasi-monotone nonlinearity and multiplicative Poisson noise. We also study existence and uniqueness of invariant measures for the associated semigroup in the Markovian case. A key role is played by a new maximal inequality for stochastic convolutions in $L_p$ spaces.Comment: Final versio

Rademacher's theorem on configuration spaces and applications

We consider an $L^2$-Wasserstein type distance $\rho$ on the configuration space $\Gamma_X$ over a Riemannian manifold $X$, and we prove that $\rho$-Lipschitz functions are contained in a Dirichlet space associated with a measure on $\Gamma_X$ satisfying some general assumptions. These assumptions are in particular fulfilled by a large class of tempered grandcanonical Gibbs measures with respect to a superstable lower regular pair potential. As an application we prove a criterion in terms of $\rho$ for a set to be exceptional. This result immediately implies, for instance, a quasi-sure version of the spatial ergodic theorem. We also show that $\rho$ is optimal in the sense that it is the intrinsic metric of our Dirichlet form

A Note on variational solutions to SPDE perturbed by Gaussian noise in a general class

This note deals with existence and uniqueness of (variational) solutions to the following type of stochastic partial differential equations on a Hilbert space H dX(t) = A(t,X(t))dt + B(t,X(t))dW(t) + h(t) dG(t) where A and B are random nonlinear operators satisfying monotonicity conditions and G is an infinite dimensional Gaussian process adapted to the same filtration as the cylindrical Wiener pocess W(t), t >= 0

Stochastic variational inequalities and applications to the total variation flow perturbed by linear multiplicative noise

In this work, we introduce a new method to prove the existence and uniqueness of a variational solution to the stochastic nonlinear diffusion equation $dX(t)={\rm div} [\frac{\nabla X(t)}{|\nabla X(t)|}]dt+X(t)dW(t) in (0,\infty)\times\mathcal{O},$ where $\mathcal{O}$ is a bounded and open domain in $\mathbb{R}^N$, $N\ge 1$, and $W(t)$ is a Wiener process of the form $W(t)=\sum^\infty_{k=1}\mu_k e_k\beta_k(t)$, e_k \in C^2(\bar\mathcal{O})\cap H^1_0(\mathcal{O}), and $\beta_k$, $k\in\mathbb{N}$, are independent Brownian motions. This is a stochastic diffusion equation with a highly singular diffusivity term and one main result established here is that, for all initial conditions in $L^2(\mathcal{O})$, it is well posed in a class of continuous solutions to the corresponding stochastic variational inequality. Thus one obtains a stochastic version of the (minimal) total variation flow. The new approach developed here also allows to prove the finite time extinction of solutions in dimensions $1\le N\le 3$, which is another main result of this work. Keywords: stochastic diffusion equation, Brownian motion, bounded variation, convex functions, bounded variation flow

Strong uniqueness for certain infinite dimensional Dirichlet operators and applications to stochastic quantization

Strong and Markov uniqueness problems in $L^2$ for Dirichlet operators on rigged Hilbert spaces are studied. An analytic approach based on a--priori estimates is used. The extension of the problem to the $L^p$-setting is discussed. As a direct application essential self--adjointness and strong uniqueness in $L^p$ is proved for the generator (with initial domain the bounded smooth cylinder functions) of the stochastic quantization process for Euclidean quantum field theory in finite volume $\Lambda \subset \R^2$