Lyapunov Functions, Stationary Distributions, and Non-equilibrium Potential for Reaction Networks
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We consider the relationship between stationary distributions for stochastic models of reaction systems and Lyapunov functions for their deterministic counterparts. Specifically, we derive the well-known Lyapunov function of reaction network theory as a scaling limit of the non-equilibrium potential of the stationary distribution of stochastically modeled complex balanced systems. We extend this result to general birth–death models and demonstrate via example that similar scaling limits can yield Lyapunov functions even for models that are not complex or detailed balanced, and may even have multiple equilibria.
KeywordsComplex balanced Dynamical system Birth-death process Continuous time Markov chain Long-term dynamics
We thank the American Institute of Mathematics for hosting a workshop at which this research was initiated. Anderson was supported by NSF Grants DMS-1009275 and DMS-1318832 and Army Research Office Grant W911NF-14-1-0401. Craciun was supported by NSF Grant DMS1412643 and NIH Grant R01GM086881. Wiuf was supported by the Lundbeck Foundation (Denmark), the Carlsberg Foundation (Denmark), Collstrups Fond (Denmark), and the Danish Research Council. Part of this work was carried out while Wiuf visited the Isaac Newton Institute in 2014.
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