Programming discrete distributions with chemical reaction networks - Cardelli, L; Kwiatkowska, M; Laurenti, L (Springer Netherlands, 2017)
We explore the range of probabilistic behaviours that can be engineered with Chemical Reaction Networks (CRNs). We give methods to “program” CRNs so that their steady state is chosen from some desired target distribution that has finite support in Nm, with m ≥ 1. Moreover, any distribution with countable infinite support can be approximated with arbitrarily small error under the L1 norm. We also give optimized schemes for special distributions, including the uniform distribution. Finally, we formulate a calculus to compute on distributions that is complete for finite support distributions, and can be compiled to a restricted class of CRNs that at steady state realize those distributions.