Explicit Integration of Stiff Stochastic Differential Equations via an Efficient Implementation of Stochastic Computational Singular Perturbation (Communications in Computational Physics, 2019)
Numerical integration of stiff stochastic differential equations based onstochastic computational singular perturbation (SCSP) was recently developed in [62].In this paper, a modified stochastic computational singular perturbation (MSCSP)method is considered. Similar to what was proposed in [26] for deterministic chemicalreaction systems, the current study applies the sensitivity derivatives of the forcingterms with respect to the state variables to measure the reaction scales, which leadsto a quasi-steady state equation for the fast species. This yields explicit large-step integrators for stochastic fast-slow stiff differential equations systems, which removesthe expensive eigen-calculations of the standard SCSP integrators. The efficiency ofthe MSCSP integrators is demonstrated with the benchmark stochastic Davis-Skodjemodel and a nonlinear catalysis model under certain stochastic disturbances.