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Approximate simulation of coupled fast and slow reactions for stochastic chemical kinetics

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Haseltine, Eric L., Rawlings, James B.·2002·The Journal of Chemical Physics

Abstract

Exact methods are available for the simulation of isothermal, well-mixed stochastic chemical kinetics. As increasingly complex physical systems are modeled, however, these methods become difficult to solve because the computational burden scales with the number of reaction events. This paper addresses one aspect of this problem: the case in which reacting species fluctuate by different orders of magnitude. By partitioning the system into subsets of “fast” and “slow” reactions, it is possible to bound the computational load by approximating “fast” reactions either deterministically or as Langevin equations. This paper provides a theoretical background for such approximations and outlines strategies for computing these approximations. Two motivating examples drawn from the fields of particle technology and biotechnology illustrate the accuracy and computational efficiency of these approximations.

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Metadata

Authors
Haseltine, E. L., & Rawlings, J. B.
Venue
The Journal of Chemical Physics
Published
2002-10-15
Volume
117
Issue
15
Pages
6959-6969
ISSN
  • 0021-9606 (ISSN-L)
  • 1089-7690
OpenAlex
W2074401358
Cited by
565
References
0
FWCI
4.97
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Approximate simulation of coupled fast and slow reactions for stochastic chemical kinetics. https://app.cochat.ai/papers/10.1063/1.1505860
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Haseltine, E. L., & Rawlings, J. B. (2002). Approximate simulation of coupled fast and slow reactions for stochastic chemical kinetics. The Journal of Chemical Physics. https://doi.org/10.1063/1.1505860

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.