Analysis of Stochastic Chemical Reaction Networks with a Hierarchy of Timescales

Abstract

We investigate a class of stochastic chemical reaction networks with $n\ge 1$ chemical species $S_1$, \ldots, $S_n$, and whose complexes are only of the form $k_i{S}_i$, $i=1$,\ldots, $n$, where $(k_i)$ are integers. The time evolution of these CRNs is driven by the kinetics of the law of mass action. A scaling analysis is done when the rates of external arrivals of chemical species are proportional to a large scaling parameter $N$. A natural hierarchy of fast processes, a subset of the coordinates of $(X_i(t))$, is determined by the values of the mapping $i\mapsto k_i$. We show that the scaled vector of coordinates $i$ such that $k_i=1$ and the scaled occupation measure of the other coordinates are converging in distribution to a deterministic limit as $N$ gets large. The proof of this result is obtained by establishing a functional equation for the limiting points of the occupation measure, by an induction on the hierarchy of timescales and with relative entropy functions.