Binomial distribution based tau-leap accelerated stochastic simulation
Publication Date
2005
Journal or Book Title
JOURNAL OF CHEMICAL PHYSICS
Abstract
Recently, Gillespie introduced the τ-leap approximate, accelerated stochastic Monte Carlo method for well-mixed reacting systems [J. Chem. Phys. 115, 1716 (2001)]. In each time increment of that method, one executes a number of reaction events, selected randomly from a Poisson distribution, to enable simulation of long times. Here we introduce a binomial distribution τ-leap algorithm (abbreviated as BD-τ method). This method combines the bounded nature of the binomial distribution variable with the limiting reactant and constrained firing concepts to avoid negative populations encountered in the original τ-leap method of Gillespie for large time increments, and thus conserve mass. Simulations using prototype reaction networks show that the BD-τ method is more accurate than the original method for comparable coarse-graining in time.
Pages
-
Volume
122
Issue
2
Recommended Citation
Chatterjee, A; Vlachos, DG; and Katsoulakis, MA, "Binomial distribution based tau-leap accelerated stochastic simulation" (2005). JOURNAL OF CHEMICAL PHYSICS. 455.
Retrieved from https://scholarworks.umass.edu/math_faculty_pubs/455
Comments
The published version is located at http://jcp.aip.org/resource/1/jcpsa6/v122/i2/p024112_s1