Literature DB >> 19045380

Coarse-grained kinetic Monte Carlo models: Complex lattices, multicomponent systems, and homogenization at the stochastic level.

Stuart D Collins1, Abhijit Chatterjee, Dionisios G Vlachos.   

Abstract

On-lattice kinetic Monte Carlo (KMC) simulations have extensively been applied to numerous systems. However, their applicability is severely limited to relatively short time and length scales. Recently, the coarse-grained MC (CGMC) method was introduced to greatly expand the reach of the lattice KMC technique. Herein, we extend the previous spatial CGMC methods to multicomponent species and/or site types. The underlying theory is derived and numerical examples are presented to demonstrate the method. Furthermore, we introduce the concept of homogenization at the stochastic level over all site types of a spatially coarse-grained cell. Homogenization provides a novel coarsening of the number of processes, an important aspect for complex problems plagued by the existence of numerous microscopic processes (combinatorial complexity). As expected, the homogenized CGMC method outperforms the traditional KMC method on computational cost while retaining good accuracy.

Entities:  

Year:  2008        PMID: 19045380     DOI: 10.1063/1.3005225

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  3 in total

1.  Spatial aspects in biological system simulations.

Authors:  Haluk Resat; Michelle N Costa; Harish Shankaran
Journal:  Methods Enzymol       Date:  2011       Impact factor: 1.600

2.  An adaptive coarse graining method for signal transduction in three dimensions.

Authors:  Michelle N Archuleta; Jason E McDermott; Jeremy S Edwards; Haluk Resat
Journal:  Fundam Inform       Date:  2012       Impact factor: 1.333

3.  Adaptive coarse-grained Monte Carlo simulation of reaction and diffusion dynamics in heterogeneous plasma membranes.

Authors:  Stuart Collins; Michail Stamatakis; Dionisios G Vlachos
Journal:  BMC Bioinformatics       Date:  2010-04-29       Impact factor: 3.169

  3 in total

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