An introduction to stochastic partial differential equations, such as reaction-diffusion, Burgers and 2D Navier-Stokes equations, perturbed by noise. It studies several properties of corresponding transition semigroups, such as Feller and strong Feller properties, irreducibility, existence and uniqueness of invariant measures.

1 Introduction and Preliminaries.- 1.1 Introduction.- 1.2 Preliminaries ix.- 2 Stochastic Perturbations of Linear Equations.- 2.1 Introduction.- 2.2 The stochastic convolution.- 2.3 The Ornstein—Uhlenbeck semigroup Rt.- 2.4 The case when Rt is strong Feller.- 2.5 Asymptotic behaviour of solutions, invariant measures.- 2.6 The transition semigroup in Lp(H, ?).- 2.7 Poincaré and log-Sobolev inequalities.- 2.8 Some complements.- 3 Stochastic Differential Equations with Lipschitz Nonlinearities.- 3.1 Introduction and setting of the problem.- 3.2 Existence, uniqueness and approximation.- 3.3 The transition semigroup.- 3.4 Invariant measure v.- 3.5 The transition semigroup in L2 (H, v).- 3.6 The integration by parts formula and its consequences.- 3.7 Comparison of v with a Gaussian measure.- 4 Reaction-Diffusion Equations.- 4.1 Introduction and setting of the problem.- 4.2 Solution of the stochastic differential equation.- 4.3 Feller and strong Feller properties.- 4.4 Irreducibility.- 4.5 Existence of invariant measure.- 4.6 The transition semigroup in L2 (H, v).- 4.7 The integration by parts formula and its consequences.- 4.8 Comparison of v with a Gaussian measure.- 4.9 Compactness of the embedding W1,2 (H, v) ? L2 (H, v).- 4.10 Gradient systems.- 5 The Stochastic Burgers Equation.- 5.1 Introduction and preliminaries.- 5.2 Solution of the stochastic differential equation.- 5.3 Estimates for the solutions.- 5.4 Estimates for the derivative of the solution w.r.t. the initial datum.- 5.5 Strong Feller property and irreducibility.- 5.6 Invariant measure v.- 5.6.1 Estimate of some integral with respect to v.- 5.7 Kolmogorov equation.- 6 The Stochastic 2D Navier—Stokes Equation.- 6.1 Introduction and preliminaries.- 6.2 Solution of the stochastic equation.- 6.3 Estimatesfor the solution.- 6.4 Invariant measure v.- 6.5 Kolmogorov equation.

Special attention to Kolmogorov equations; it is shown that, in each case, there exists a core of smooth functions. This fact is applied to define Sobolev spaces w.r.t. invariant measures and to prove, e.g., the Poincaré and log-Sobolev inequalities Absolute continuity of the invariant measure w.r.t. a suitable Gaussian measure is studied

GPSR Compliance The European Union's (EU) General Product Safety Regulation (GPSR) is a set of rules that requires consumer products to be safe and our obligations to ensure this. If you have any concerns about our products you can contact us on ProductSafety@springernature.com. In case Publisher is established outside the EU, the EU authorized representative is: Springer Nature Customer Service Center GmbH Europaplatz 3 69115 Heidelberg, Germany ProductSafety@springernature.com