Coarse-grained stochastic processes for microscopic lattice systems

@article{citeulike:2552009, 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. 10.1073/pnas.242741499}, author = {Katsoulakis, Markos A. and Majda, Andrew J. and Vlachos, Dionisios G. }, citeulike-article-id = {2552009}, doi = {10.1073/pnas.242741499}, journal = {Proceedings of the National Academy of Sciences}, month = {February}, number = {3}, pages = {782--787}, posted-at = {2008-03-18 16:27:46}, priority = {0}, title = {Coarse-grained stochastic processes for microscopic lattice systems}, url = {http://dx.doi.org/10.1073/pnas.242741499}, volume = {100}, year = {2003} }

TY - JOUR ID - citeulike:2552009 L3 - citeulike-article-id:2552009 TI - Coarse-grained stochastic processes for microscopic lattice systems JF - Proceedings of the National Academy of Sciences VL - 100 IS - 3 SP - 782 EP - 787 N2 - 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. 10.1073/pnas.242741499 AU - Katsoulakis, Markos AU - Majda, Andrew AU - Vlachos, Dionisios PY - 2003/02/04/ UR - http://dx.doi.org/10.1073/pnas.242741499 ER -