Solving stochastic chemical kinetics by Metropolis Hastings sampling
This work addresses the need for faster yet accurate stochastic simulations in chemical kinetics, though the improvement is incremental over existing tau-leap methods.
The study proposes a Metropolis-Hastings sampling method for stochastic chemical kinetics, using exponential solutions of the Chemical Master Equation to improve the accuracy of the tau-leap method while maintaining the same distribution as the Stochastic Simulation Algorithm.
This study considers using Metropolis-Hastings algorithm for stochastic simulation of chemical reactions. The proposed method uses SSA (Stochastic Simulation Algorithm) distribution which is a standard method for solving well-stirred chemically reacting systems as a desired distribution. A new numerical solvers based on exponential form of exact and approximate solutions of CME (Chemical Master Equation) is employed for obtaining target and proposal distributions in Metropolis-Hastings algorithm to accelerate the accuracy of the tau-leap method. Samples generated by this technique have the same distribution as SSA and the histogram of samples show it's convergence to SSA.