title: The Time Dependent Propensity Function for Acceleration of Spatial Stochastic Simulation of Reaction-Diffusion Systems.
abstract: The inhomogeneous stochastic simulation algorithm (ISSA) is a fundamental method for spatial stochastic simulation. However, when diffusion events occur more frequently than reaction events, simulating the diffusion events by ISSA is quite costly. To reduce this cost, we propose to use thetime dependent propensity functionin each step. In this way we can avoid simulating individual diffusion events, and use the time interval between two adjacent reaction events as the simulation stepsize. We demonstrate that the new algorithm can achieve orders of magnitude efficiency gains over widely-used exact algorithms, scales well with increasing grid resolution, and maintains a high level of accuracy.
authors.affiliation: Department of Computer Science, University of California, Santa Barbara.
authors.forename: Jin
authors.initials: J
authors.lastname: Fu
authors.affiliation: Department of Computer Science, University of California, Santa Barbara.
authors.forename: Sheng
authors.initials: S
authors.lastname: Wu
authors.affiliation: Teradata Inc., El Segundo, California.
authors.forename: Hong
authors.initials: H
authors.lastname: Li
authors.affiliation: Department of Computer Science, University of California, Santa Barbara.
authors.forename: Linda R
authors.initials: LR
authors.lastname: Petzold