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A Multi-Time-Scale Analysis of Stochastic Chemical Reaction Networks

Tuesday, May 13, 2014 - 1:30pm - 2:30pm
Lind 305
Xingye Kan (University of Minnesota, Twin Cities)
We consider stochastic descriptions of reaction networks in
which there are both fast and slow reactions, and the time scales are
widely separated. We obtain a reduced equation on a slow time scale by
applying a state space decomposition method to the full governing equation
and describe our reduction method on the reaction simplex. Based on the
analytic results, we approximate reaction probabilities, or so-called
propensity functions and present an efficient stochastic simulation
algorithm for the slow time scale dynamics. We illustrate the numerical
accuracy of the approximation by simulating several motivating examples.

This is an ongoing joint project with Chang Hyeong Lee and Hans G. Othmer.