Open AccessA partial-propensity variant of the composition-rejection stochastic simulation algorithm for chemical reaction networks
Author(s) -
Rajesh Ramaswamy,
Ivo F. Sbalzarini
Publication year - 2010
Publication title -
the journal of chemical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.071
H-Index - 357
eISSN - 1089-7690
pISSN - 0021-9606
DOI - 10.1063/1.3297948
Subject(s) - composition (language) , constant (computer programming) , bounded function , chemical reaction , scaling , stochastic simulation , chemical composition , mathematics , algorithm , chemistry , computer science , physics , thermodynamics , statistics , mathematical analysis , organic chemistry , philosophy , linguistics , geometry , programming language
We present the partial-propensity stochastic simulation algorithm with composition-rejection sampling (PSSA-CR). It is an exact formulation of the stochastic simulation algorithm (SSA) for well-stirred systems of coupled chemical reactions. The new formulation is a partial-propensity variant [R. Ramaswamy, N. Gonzalez-Segredo, and I. F. Sbalzarini, J. Chem. Phys. 130, 244104 (2009)] of the composition- rejection SSA [A. Slepoy, A. P. Thompson, and S. J. Plimpton, J. Chem. Phys. 128, 205101 (2008)]. The computational cost of this new formulation is bounded by a constant for weakly coupled reaction networks, and it increases at most linearly with the number of chemical species for strongly coupled reaction networks. PSSA-CR thus combines the advantages of partial-propensity methods and the composition-rejection SSA, providing favorable scaling of the computational cost for all classes of reaction networks
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