The time dependent propensity function for acceleration of spatial stochastic simulation of reaction–diffusion systems

Journal Article · Wed Oct 01 00:00:00 EDT 2014 · Journal of Computational Physics

DOI:https://doi.org/10.1016/J.JCP.2014.06.025· OSTI ID:22382120

Fu, Jin ^[1]; Wu, Sheng ^[1]; Li, Hong ^[2]

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1. Department of Computer Science, University of California, Santa Barbara (United States)
2. Teradata Inc., El Segundo, California (United States)

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 the time dependent propensity function in 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.

• OSTI ID: 22382120
• Journal Information: Journal of Computational Physics, Vol. 274; Other Information: Copyright (c) 2014 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA); ISSN 0021-9991
• Country of Publication: United States
• Language: English

Related Subjects

71 CLASSICAL AND QUANTUM MECHANICS
GENERAL PHYSICS
ACCELERATION
ACCURACY
ALGORITHMS
COMPUTERIZED SIMULATION
DIFFUSION
EFFICIENCY
GAIN
RESOLUTION
STOCHASTIC PROCESSES