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Workshop Series on Advances on Scientific and Engineering Computing (II) —— High Performance Computation: Theory and Applications

Probabilistic Superiority of Stochastic Symplectic Methods via Large Deviations Principle

Speaker

Jialin Hong , Chinese Academy of Sciences

Time

17 Oct, 14:00 - 14:35

Abstract

Plenty of numerical experiments show that stochastic symplectic methods are superior to non-symplectic ones especially in long-time computation, when applied to stochastic Hamiltonian systems. In this talk we first review some basic results on stochastic symplectic methods of stochastic Hamiltonian systems, such as the theory of stochastic generating functions, variational integrators, pseudo-symplectic methods, etc. Then we present the probabilistic superiority of stochastic symplectic methods of stochastic Hamiltonian systems via large deviations principle. (In collaboration with Dr. Chuchu Chen, Dr. Diancong Jin and Dr. Liying Sun)