Literature DB >> 25983341

An Integration Factor Method for Stochastic and Stiff Reaction-Diffusion Systems.

Catherine Ta1, Dongyong Wang1, Qing Nie1.   

Abstract

Stochastic effects are often present in the biochemical systems involving reactions and diffusions. When the reactions are stiff, existing numerical methods for stochastic reaction diffusion equations require either very small time steps for any explicit schemes or solving large nonlinear systems at each time step for the implicit schemes. Here we present a class of semi-implicit integration factor methods that treat the diffusion term exactly and reaction implicitly for a system of stochastic reaction-diffusion equations. Our linear stability analysis shows the advantage of such methods for both small and large amplitudes of noise. Direct use of the method to solving several linear and nonlinear stochastic reaction-diffusion equations demonstrates good accuracy, efficiency, and stability properties. This new class of methods, which are easy to implement, will have broader applications in solving stochastic reaction-diffusion equations arising from models in biology and physical sciences.

Entities:  

Keywords:  IIF-Maruyama; Integration Factor method; Stochastic reaction-diffusion systems; activator-susbtrate system; patterns

Year:  2015        PMID: 25983341      PMCID: PMC4430728          DOI: 10.1016/j.jcp.2015.04.028

Source DB:  PubMed          Journal:  J Comput Phys        ISSN: 0021-9991            Impact factor:   3.553


  10 in total

1.  A Robust and Efficient Method for Steady State Patterns in Reaction-Diffusion Systems.

Authors:  Wing-Cheong Lo; Long Chen; Ming Wang; Qing Nie
Journal:  J Comput Phys       Date:  2012-06-01       Impact factor: 3.553

Review 2.  Reaction-diffusion model as a framework for understanding biological pattern formation.

Authors:  Shigeru Kondo; Takashi Miura
Journal:  Science       Date:  2010-09-24       Impact factor: 47.728

Review 3.  Stochastic modelling for quantitative description of heterogeneous biological systems.

Authors:  Darren J Wilkinson
Journal:  Nat Rev Genet       Date:  2009-02       Impact factor: 53.242

4.  Turing's model for biological pattern formation and the robustness problem.

Authors:  Philip K Maini; Thomas E Woolley; Ruth E Baker; Eamonn A Gaffney; S Seirin Lee
Journal:  Interface Focus       Date:  2012-02-08       Impact factor: 3.906

5.  Compact integration factor methods in high spatial dimensions.

Authors:  Qing Nie; Frederic Y M Wan; Yong-Tao Zhang; Xin-Feng Liu
Journal:  J Comput Phys       Date:  2008       Impact factor: 3.553

6.  Array-representation Integration Factor Method for High-dimensional Systems.

Authors:  Dongyong Wang; Lei Zhang; Qing Nie
Journal:  J Comput Phys       Date:  2014-02-01       Impact factor: 3.553

7.  Compact integration factor methods for complex domains and adaptive mesh refinement.

Authors:  Xinfeng Liu; Qing Nie
Journal:  J Comput Phys       Date:  2010-08-10       Impact factor: 3.553

8.  A critical quantity for noise attenuation in feedback systems.

Authors:  Liming Wang; Jack Xin; Qing Nie
Journal:  PLoS Comput Biol       Date:  2010-04-29       Impact factor: 4.475

9.  Noise drives sharpening of gene expression boundaries in the zebrafish hindbrain.

Authors:  Lei Zhang; Kelly Radtke; Likun Zheng; Anna Q Cai; Thomas F Schilling; Qing Nie
Journal:  Mol Syst Biol       Date:  2012       Impact factor: 11.429

10.  Spatial stochastic dynamics enable robust cell polarization.

Authors:  Michael J Lawson; Brian Drawert; Mustafa Khammash; Linda Petzold; Tau-Mu Yi
Journal:  PLoS Comput Biol       Date:  2013-07-25       Impact factor: 4.475

  10 in total
  1 in total

1.  A HYBRID METHOD FOR STIFF REACTION-DIFFUSION EQUATIONS.

Authors:  Yuchi Qiu; Weitao Chen; Qing Nie
Journal:  Discrete Continuous Dyn Syst Ser B       Date:  2019-12       Impact factor: 1.327

  1 in total

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