Model reduction for slow-fast stochastic systems with metastable behaviour

Abstract

The quasi-steady-state approximation (or stochastic averaging principle) is a useful tool in the study of multiscale stochastic systems, giving a practical method by which to reduce the number of degrees of freedom in a model. The method is extended here to slow-fast systems in which the fast variables exhibit metastable behaviour. The key parameter that determines the form of the reduced model is the ratio of the timescale for the switching of the fast variables between metastable states to the timescale for the evolution of the slow variables. The method is illustrated with two examples: one from biochemistry (a fast-species-mediated chemical switch coupled to a slower-varying species), and one from ecology (a predator-prey system). Numerical simulations of each model reduction are compared with those of the full system.

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Cited by in corpus (3)

• Stochastic effects in autoimmune dynamics
• On Moment Matching for Stochastic Systems
• The effects of intrinsic noise on the behaviour of bistable cell regulatory systems under quasi-steady state conditions