A constrained approach to multiscale stochastic simulation of chemically reacting systems

Simon L. Cotter, Konstantinos C. Zygalakis, Ioannis G. Kevrekidis, Radek Erban

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Abstract

Stochastic simulation of coupled chemical reactions is often computationally intensive, especially if a chemical system contains reactions occurring on different time scales. In this paper, we introduce a multiscale methodology suitable to address this problem, assuming that the evolution of the slow species in the system is well approximated by a Langevin process. It is based on the conditional stochastic simulation algorithm (CSSA) which samples from the conditional distribution of the suitably defined fast variables, given values for the slow variables. In the constrained multiscale algorithm (CMA) a single realization of the CSSA is then used for each value of the slow variable to approximate the effective drift and diffusion terms, in a similar manner to the constrained mean-force computations in other applications such as molecular dynamics. We then show how using the ensuing Fokker-Planck equation approximation, we can in turn approximate average switching times in stochastic chemical systems. © 2011 American Institute of Physics.
Original languageEnglish (US)
Pages (from-to)094102
JournalThe Journal of Chemical Physics
Volume135
Issue number9
DOIs
StatePublished - Sep 2 2011
Externally publishedYes

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