A multilevel adaptive reaction-splitting method for SRNs

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Poster
Authors
Moraes, Alvaro cc
Tempone, Raul cc
Vilanova, Pedro cc
KAUST Department
Applied Mathematics and Computational Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Date
2015-01-07
Permanent link to this record
http://hdl.handle.net/10754/624086

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Abstract
In this work, we present a novel multilevel Monte Carlo method for kinetic simulation of stochastic reaction networks specifically designed for systems in which the set of reaction channels can be adaptively partitioned into two subsets characterized by either “high” or “low” activity. To estimate expected values of observables of the system, our method bounds the global computational error to be below a prescribed tolerance, within a given confidence level. This is achieved with a computational complexity of order O (TOL-2).We also present a novel control variate technique which may dramatically reduce the variance of the coarsest level at a negligible computational cost. Our numerical examples show substantial gains with respect to the standard Stochastic Simulation Algorithm (SSA) by Gillespie and also our previous hybrid Chernoff tau-leap method.
Conference/Event name
Advances in Uncertainty Quantification Methods, Algorithms and Applications (UQAW 2015)
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Posters; Applied Mathematics and Computational Science Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Conference on Advances in Uncertainty Quantification Methods, Algorithms and Applications (UQAW 2015)