A Fast Algorithm for High-Dimensional Markov Processes with Finite Sets of Transition Rates

Abstract

The discrete class algorithm presented in this paper is an efficient simulation tool for stochastic processes governed by a reasonably small set of transition rates. The algorithm is presented, its performance compared to prevailing methods and applications to epitaxial growth and neuronal models are sketched. Source code is available from the author's WWW-site.