Literature DB >> 11909304

Kinetic Monte Carlo simulations with minimal searching.

T P Schulze1.   

Abstract

Kinetic Monte Carlo (KMC) simulations are used to simulate epitaxial crystal growth. Presently, the fastest reported methods use binary trees to search through a list of rates in O(log(2) M) time, where M is the number of rates. These methods are applicable to an arbitrary set of rates, but typical KMC bond-counting schemes involve only a finite set of distinct rates. This allows one to construct a faster list-based algorithm with a computation time that is essentially independent of M. It is found that this algorithm typically reduces computation time by between 30% and 50% for typical simulations, with this factor increasing for larger simulations.

Year:  2002        PMID: 11909304     DOI: 10.1103/PhysRevE.65.036704

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  4 in total

1.  Algorithms and software for stochastic simulation of biochemical reacting systems.

Authors:  Hong Li; Yang Cao; Linda R Petzold; Daniel T Gillespie
Journal:  Biotechnol Prog       Date:  2007-09-26

2.  Accelerating the Gillespie τ-Leaping Method using graphics processing units.

Authors:  Ivan Komarov; Roshan M D'Souza; Jose-Juan Tapia
Journal:  PLoS One       Date:  2012-06-08       Impact factor: 3.240

3.  Accelerating the Gillespie Exact Stochastic Simulation Algorithm using hybrid parallel execution on graphics processing units.

Authors:  Ivan Komarov; Roshan M D'Souza
Journal:  PLoS One       Date:  2012-11-09       Impact factor: 3.240

4.  Modelling non-Markovian dynamics in biochemical reactions.

Authors:  Davide Chiarugi; Moreno Falaschi; Diana Hermith; Carlos Olarte; Luca Torella
Journal:  BMC Syst Biol       Date:  2015-06-01
  4 in total

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