Adaptive Tempering Monte Carlo Method

Authors: Dong, Xiao; Blaisten-Barojas, Estela

Source: Journal of Computational and Theoretical Nanoscience, Volume 3, Number 1, February 2006 , pp. 118-127(10)

Publisher: American Scientific Publishers

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Abstract:

The Adaptive Tempering Monte Carlo (ATMC) optimization method based on multi-canonical Monte Carlo is proposed in this work to optimize the preferred structure of atomic clusters. The method also works well to obtain the structure of solid crystals at low temperatures resulting from an annealing process. The weights that link the sub-canonical ensembles are adapted progressively during the simulation. The method was tested on Morse atomic clusters containing 10–155 atoms, for which the global minimum structures were obtained at the end of quenches from high temperature to zero temperature. A second example was the structural optimization of quantum tight-binding clusters of calcium containing 13 to 32 atoms. A third example is the solidification of a Lennard-Jones liquid system, which yielded a crystal with few defects in a single pass of the tempering method. The ATMC proves to be very efficient for optimization of ordered structures, and can be used in classical and quantum approaches.
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