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Nonlinear Stochastic Evolution Equations: Analysis and NumericsNonlinear Stochastic Evolution Equations: Analysis and Numerics

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Nonlinear Stochastic Evolution Equations: Analysis and Numerics


This workshop intends to bring together experts on nonlinear stochastic evolution equations and to discuss recent developments in this field of research.

November 3rd - 5th, 2016, Berlin

Organised by:

Raphael Kruse

Etienne Emmrich

Petra Wittbold

Supported by Technische Universit├Ąt Berlin, Universit├Ąt Duisburg-Essen, Einstein Center for Mathematics and German Research Foundation through DFG research unit FOR 2402.

Since the 1970s the analysis of stochastic partial differential equations (SPDEs) is one of the most active research fields within mathematics, which has led to many new and fruitful collaborations of several mathematical branches such as differential equations, stochastic analysis, numerics or functional analysis. Nowadays, SPDEs are often used to model complex phenomena, which are influenced by uncertainties or stochastic perturbations. Typically, the presence of noise leads to a loss of regularity which prevents the application of traditional (deterministic) solution theory or approximation methods.

The goal of this workshop is to discuss open problems and recent progress made in the mathematical treatment of nonlinear stochastic evolution equations. For instance, in the case of quasilinear stochastic evolution equations, such as the stochastic p-Laplace equation, the question of existence of solutions can often be positively answered by the help of variational methods. However, it often remains an open problem of how to determine the optimal regularity of such a solution. Moreover, the development and analysis of numerical methods for such equations is still in its infancy.


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