Approximation and simulation of Lévy-driven SPDE

‚ÄčNumerical analysis of stochastic partial differential equations is a quite young and very active area of research. Since analytical solutions of these equations are only rarely available, approximation of sample paths, moments, or probabilities is necessary. The quantity of interest depends on the type of application, e.g., finance, engineering, or filtering. The goal of the project is to answer some current open questions in the research area with methods from stochastic analysis, numerical analysis, and mathematical statistics. The research questions are related to different definitions of consistency of approximation schemes, the Lax equivalence theorem, weak convergence results using Malliavin calculus, construction of efficient algorithms for random fields, statistical properties of multilevel Monte Carlo algorithms, and mean-square stability regions.

Participants

Annika Lang (contact)

Docent vid Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Adam Andersson

Forskare vid Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

David Bolin

Universitetslektor vid Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Stig Larsson

Professor vid Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Andreas Petersson

Doktorand vid Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Collaborations

Johannes Kepler University of Linz (JKU)

Linz, Austria

Technische Universität Berlin

Berlin, Germany

Funding

Swedish Research Council (VR)

Funding years 2015–2018

More information

Project Web Page at Chalmers

http://www.chalmers.se/en/projects/Pages/A...

Latest update

2015-09-11