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Article
Coarse-grained stochastic processes and Monte Carlo simulations in lattice systems
JOURNAL OF COMPUTATIONAL PHYSICS
  • MA Katsoulakis, University of Massachusetts - Amherst
  • AJ Majda
  • DG Vlachos
Publication Date
2003
Abstract
Diverse scientific disciplines ranging from materials science to catalysis to biomolecular dynamics to climate modeling involve nonlinear interactions across a large range of physically significant length scales. Here a class of coarse-grained stochastic processes and corresponding Monte Carlo simulation methods, describing computationally feasible mesoscopic length scales, are derived directly from microscopic lattice systems. It is demonstrated below that the coarse-grained stochastic models can capture large-scale structures while retaining significant microscopic information. The requirement of detailed balance is used as a systematic design principle to guarantee correct noise fluctuations for the coarse-grained model. The coarse-grained stochastic algorithms provide large computational savings without increasing programming complexity or computer time per executive event compared to microscopic Monte Carlo simulations.
Comments

The published version is located at http://www.pnas.org/content/100/3/782

Pages
250-278
Citation Information
MA Katsoulakis, AJ Majda and DG Vlachos. "Coarse-grained stochastic processes and Monte Carlo simulations in lattice systems" JOURNAL OF COMPUTATIONAL PHYSICS Vol. 186 Iss. 1 (2003)
Available at: http://works.bepress.com/markos_katsoulakis/39/