A new approach to simulating stochastic delayed systems.

Math Biosci

Department of Mathematics, University of Sussex, Falmer, Brighton BN1 9QH, UK. Electronic address:

Published: April 2020

In this paper we present a new method for deriving Itô stochastic delay differential equations (SDDEs) from delayed chemical master equations (DCMEs). Considering alternative formulations of SDDEs that can be derived from the same DCME, we prove that they are equivalent both in distribution, and in sample paths they produce. This allows us to formulate an algorithmic approach to deriving equivalent Itô SDDEs with a smaller number of noise variables, which increases the computational speed of simulating stochastic delayed systems. The new method is illustrated on a simple model of two interacting species and a model with bistability, and in both cases it shows excellent agreement with the results of direct stochastic simulations, while also demonstrating a much superior speed of performance.

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http://dx.doi.org/10.1016/j.mbs.2020.108327DOI Listing

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