Speaker
Description
This talk addresses recent developments in the design and analysis of structure-preserving numerical methods for selected classes of stochastic differential equations and stochastic partial differential equations, endowed with intrinsic invariance properties. Particular attention is devoted to the numerical preservation mean-square dissipativity, by means of stochastic $\theta$-methods. We show that, in this framework, the conservation of mean-square dissipativity emerges through conditional stability properties of the numerical method under consideration. Theoretical results are complemented by numerical experiments on selected test problems.
The talk is based on recent papers in collaboration with H. Biscevic (Gran Sasso Science Insitute), E. Buckwar (Johannes Kepler University of Linz), S. Di Giovacchino (University of L'Aquila).
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