A Gaussian jump process formulation of the reaction–diffusion master equation enables faster exact stochastic simulations

Autor:	Tina Subic, Ivo F. Sbalzarini
Rok vydání:	2022
Předmět:	Diffusion Stochastic Processes Normal Distribution General Physics and Astronomy Computer Simulation Physical and Theoretical Chemistry Algorithms
Zdroj:	The Journal of chemical physics
ISSN:	1089-7690 0021-9606
DOI:	10.1063/5.0123073
Popis:	We propose a Gaussian jump process model on a regular Cartesian lattice for the diffusion part of the Reaction–Diffusion Master Equation (RDME). We derive the resulting Gaussian RDME (GRDME) formulation from analogy with a kernel-based discretization scheme for continuous diffusion processes and quantify the limits of its validity relative to the classic RDME. We then present an exact stochastic simulation algorithm for the GRDME, showing that the accuracies of GRDME and RDME are comparable, but exact simulations of the GRDME require only a fraction of the computational cost of exact RDME simulations. We analyze the origin of this speedup and its scaling with problem dimension. The benchmarks suggest that the GRDME is a particularly beneficial model for diffusion-dominated systems in three dimensional spaces, often occurring in systems biology and cell biology.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::17084a748476fc2803248a962afbcbe1 https://doi.org/10.1063/5.0123073 Zobrazit plný text záznamu