title: Binomial distribution based tau-leap accelerated stochastic simulation.
abstract: Recently, Gillespie introduced the tau-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 tau-leap algorithm (abbreviated as BD-tau 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 tau-leap method of Gillespie for large time increments, and thus conserve mass. Simulations using prototype reaction networks show that the BD-tau method is more accurate than the original method for comparable coarse-graining in time.
authors.affiliation: Department of Chemical Engineering and Center for Catalytic Science and Technology, University of Delaware, Newark, Delaware 19716, USA.
authors.forename: Abhijit
authors.initials: A
authors.lastname: Chatterjee
authors.forename: Dionisios G
authors.initials: DG
authors.lastname: Vlachos
authors.forename: Markos A
authors.initials: MA
authors.lastname: Katsoulakis