title: The slow-scale stochastic simulation algorithm.
abstract: Reactions in real chemical systems often take place on vastly different time scales, with "fast" reaction channels firing very much more frequently than "slow" ones. These firings will be interdependent if, as is usually the case, the fast and slow reactions involve some of the same species. An exact stochastic simulation of such a system will necessarily spend most of its time simulating the more numerous fast reaction events. This is a frustratingly inefficient allocation of computational effort when dynamical stiffness is present, since in that case a fast reaction event will be of much less importance to the system's evolution than will a slow reaction event. For such situations, this paper develops a systematic approximate theory that allows one to stochastically advance the system in time by simulating the firings of only the slow reaction events. Developing an effective strategy to implement this theory poses some challenges, but as is illustrated here for two simple systems, when those challenges can be overcome, very substantial increases in simulation speed can be realized.
authors.affiliation: Department of Computer Science, University of California-Santa Barbara, Santa Barbara, CA 93106, USA. ycao@engineering.ucsb.edu
authors.forename: Yang
authors.initials: Y
authors.lastname: Cao
authors.forename: Daniel T
authors.initials: DT
authors.lastname: Gillespie
authors.forename: Linda R
authors.initials: LR
authors.lastname: Petzold