4.4 Article

An optimized initialization algorithm to ensure accuracy in quantum Monte Carlo calculations

期刊

JOURNAL OF COMPUTATIONAL CHEMISTRY
卷 29, 期 14, 页码 2335-2343

出版社

WILEY
DOI: 10.1002/jcc.20965

关键词

quantum Monte Carlo; walker initialization; parallel computing; parallel efficiency

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Quantum Monte Carlo (QMC) calculations require the generation of random electronic configurations with respect to a desired probability density, Usually the square of the magnitude of the wavefunction. In most cases, the Metropolis algorithm is used to generate a sequence of configurations in a Markov chain. This method has all inherent equilibration phase, during which the configurations are not representative of the desired density and must be discarded. If statistics are gathered before the walkers have equilibrated, contamination by nonequilibrated configurations call greatly reduce the accuracy of the results. Because separate Markov chains must be equilibrated for the walkers on each processor, the use of a long equilibration phase has a profoundly detrimental effect on the efficiency of large parallel Calculations. The stratified atomic walker initialization (STRAW) shortens the equilibration phase of QMC calculations by generating statistically independent electronic configurations in regions of high probability density. This ensures the accuracy of calculations by avoiding contamination by nonequilibrated configurations. Shortening the length of the equilibration phase also results in significant improvements in the efficiency of parallel calculations, which reduces the total computational run time. For example, using STRAW rather than a standard initialization method in 512 processor calculations reduces the amount of time needed to calculate the energy expectation value of a trial function for a molecule of the energetic material RDX to within 0.01 au by 33%. (C) 2008 Wiley Periodicals, Inc.

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