Renormalisation of Stochastic Partial Differential Equations

Stochastic Partial Differential Equations

Applications of Stochastic Partial Differential Equations

s of the talks Robert Adler, Technion-Israel Institute of Technology, Israel On quantifying shape, with two applications to stochastic processes I shall discuss some classical Integral and Differential Geometric ways to classify shape, and describe 1. A new class of results about the excursion sets of smooth random fields which uses them. 2. An application of these classifiers to the study of t...

A Primer on Stochastic Partial Differential Equations

These notes form a brief introductory tutorial to elements of Gaussian noise analysis and basic stochastic partial differential equations (SPDEs) in general, and the stochastic heat equation, in particular. The chief aim here is to get to the heart of the matter quickly. We achieve this by studying a few concrete equations only. This chapter provides sufficient preparation for learning more adv...

On quasi-linear stochastic partial differential equations

We prove existence and uniqueness of the solution of a parabolic SPDE in one space dimension driven by space-time white noise, in the case of a measurable drift and a constant diffusion coefficient, as well as a comparison theorem.

Introduction to stochastic partial differential equations

We introduce the Hilbert space-valued Wiener process and the corresponding stochastic integral of Itô type. This is then used together with semigroup theory to obtain existence and uniqueness of weak solutions of linear and semilinear stochastic evolution problems in Hilbert space. Finally, this abstract theory is applied to the linear heat and wave equations driven by additive noise.