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    A multilevel adaptive reaction-splitting method for SRNs

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    Type
    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
    
    Metadata
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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)
    Collections
    Posters; Applied Mathematics and Computational Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division; Conference on Advances in Uncertainty Quantification Methods, Algorithms and Applications (UQAW 2015)

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