Ergodicity analysis and antithetic integral control of a class of stochastic reaction networks with delays

Abstract

Delays are important phenomena arising in a wide variety of real world systems, including biological ones, because of diffusion/propagation effects or as simplifying modeling elements. We propose here to consider delayed stochastic reaction networks, a class of networks that has been relatively few studied until now. The difficulty in analyzing them resides in the fact that their state-space is infinite-dimensional. We demonstrate here that by restricting the delays to be phase-type distributed, one can represent the associated delayed reaction network as a reaction network with finitedimensional state-space. This can be achieved by suitably adding chemical species and reactions to the delay-free network following a simple algorithm which is fully characterized. Since phase-type distributions are dense in the set of probability distributions, they can approximate any distribution arbitrarily closely and this makes their consideration only a bit restrictive. As the state-space remains finite-dimensional, usual tools developed for non-delayed reaction network directly apply. In particular, we prove, for unimolecular mass-action reaction networks, that the delayed stochastic reaction network is ergodic if and only if the delay-free network is ergodic as well. Bimolecular reactions are more difficult to consider but slightly stronger analogous results are nevertheless obtained. These results demonstrate that delays have little to no harm to the ergodicity property of reaction networks as long as the delays are phase-type distributed, and this holds regardless the complexity of their distribution. We also prove that the presence of those delays adds convolution terms in the moment equation but does not change the value of the stationary means compared to the delay-free case. The covariance, however, is influenced by the presence of the delays. Finally, the control of a certain class of delayed stochastic reaction network using a delayed antithetic integral controller is considered. It is proven that this controller achieves its goal provided that the delay-free network satisfy the conditions of ergodicity and output-controllability. IntroductionDelays are omnipresent physical phenomena induced by memory, propagation or transport effects [12,24,30,42,50,52]. They naturally arise in population dynamics [28], ecology [29], epidemiology [19], biology [11,20,21,25,39] and engineering [12,30,43,52]. It is commonly understood that delays have, in general, detrimental effects in engineering as they may lead to instabilities such as oscillations. While this destabilizing effect is undesirable in this setting, their role can be crucial in biology when one wants, for instance, to design oscillators [11,48,58]. In the stochastic setting, delays have indeed been shown to be helpful for generating oscillations [11], but also to accelerate signaling [40] and to be responsible for an increase in intrinsic variability [55]. Delays can be easily incorporated in the dynamics of a deterministic reaction network by simply substituting del...

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