A linearization method for probability moment equations. (6th April 2018)

• Record Type: Journal Article
• Authors: Vlysidis, Michail; Kaznessis, Yiannis N.
• Is Part Of: Computers & chemical engineering. Volume 112(2018)
• Page Start: 1
• Page End: 5
• Publication Date: 2018-04-06
• Subjects: Linearization -- Stochastic reaction networks -- Moment equations -- Chemical master equation -- Stationary Jacobian; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2018.01.015
• Languages: English
• ISSNs: 0098-1354

Abstract

Highlights: A linearization technique for solving the probability moment equation of stochastic reaction networks. The approach linearizes the moment equation through a two-term Taylor expansion. Steady state Jacobian is necessary to capture the dynamical behavior of the network. The method provides accurate results for multicomponent and multistable systems. SSA results were employed to determine accuracy. Graphical abstract: 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.