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Title: Hybrid discrete/continuum algorithms for stochastic reaction networks

Journal Article · · Journal of Computational Physics

Direct solutions of the Chemical Master Equation (CME) governing Stochastic Reaction Networks (SRNs) are generally prohibitively expensive due to excessive numbers of possible discrete states in such systems. To enhance computational efficiency we develop a hybrid approach where the evolution of states with low molecule counts is treated with the discrete CME model while that of states with large molecule counts is modeled by the continuum Fokker-Planck equation. The Fokker-Planck equation is discretized using a 2nd order finite volume approach with appropriate treatment of flux components to avoid negative probability values. The numerical construction at the interface between the discrete and continuum regions implements the transfer of probability reaction by reaction according to the stoichiometry of the system. As a result, the performance of this novel hybrid approach is explored for a two-species circadian model with computational efficiency gains of about one order of magnitude.

Research Organization:
Sandia National Lab. (SNL-CA), Livermore, CA (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
Grant/Contract Number:
AC04-94AL85000; 07-012783
OSTI ID:
1121280
Alternate ID(s):
OSTI ID: 1246992
Report Number(s):
SAND-2013-10187J; 485627
Journal Information:
Journal of Computational Physics, Vol. 281, Issue C; ISSN 0021-9991
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 11 works
Citation information provided by
Web of Science

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Cited By (3)

Approximation and inference methods for stochastic biochemical kinetics—a tutorial review journal January 2017
Hybrid framework for the simulation of stochastic chemical kinetics journal December 2016
Approximate Numerical Integration of the Chemical Master Equation for Stochastic Reaction Networks preprint January 2019

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