A linearization method for probability moment equations
M Vlysidis, YN Kaznessis - Computers & Chemical Engineering, 2018 - Elsevier
Computers & Chemical Engineering, 2018•Elsevier
We present a new method for calculating the time-transient behavior of stochastic reaction
networks. We first derive the set of equations for the moments of the master probability
distribution. We then linearize these equations calculating the Jacobian matrix around the
stationary probability distribution. In order to demonstrate the method, we present examples
of stochastic reaction networks and compute their dynamic behavior. We find that the
calculations are accurate and significantly more efficient than stochastic simulation …
networks. We first derive the set of equations for the moments of the master probability
distribution. We then linearize these equations calculating the Jacobian matrix around the
stationary probability distribution. In order to demonstrate the method, we present examples
of stochastic reaction networks and compute their dynamic behavior. We find that the
calculations are accurate and significantly more efficient than stochastic simulation …
Abstract
We present a new method for calculating the time-transient behavior of stochastic reaction networks. We first derive the set of equations for the moments of the master probability distribution. We then linearize these equations calculating the Jacobian matrix around the stationary probability distribution. In order to demonstrate the method, we present examples of stochastic reaction networks and compute their dynamic behavior. We find that the calculations are accurate and significantly more efficient than stochastic simulation algorithms based on Gillespie’s algorithms.
Elsevier
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