A puresampling quantum Monte Carlo algorithm
Abstract
The objective of puresampling quantum Monte Carlo is to calculate physical properties that are independent of the importance sampling function being employed in the calculation, save for the mismatch of its nodal hypersurface with that of the exact wave function. To achieve this objective, we report a puresampling algorithm that combines features of forward walking methods of puresampling and reptation quantum Monte Carlo (RQMC). The new algorithm accurately samples properties from the mixed and pure distributions simultaneously in runs performed at a single set of timesteps, over which extrapolation to zero timestep is performed. In a detailed comparison, we found RQMC to be less efficient. It requires different sets of timesteps to accurately determine the energy and other properties, such as the dipole moment. We implement our algorithm by systematically increasing an algorithmic parameter until the properties converge to statistically equivalent values. As a proof in principle, we calculated the fixednode energy, static α polarizability, and other oneelectron expectation values for the groundstates of LiH and water molecules. These quantities are free from importance sampling bias, population control bias, timestep bias, extrapolationmodel bias, and the finitefield approximation. We found excellent agreement with the accepted values for the energy and amore »
 Authors:
 Departments of Chemistry and Physics, Brock University, St. Catharines, Ontario L2S 3A1 (Canada)
 Publication Date:
 OSTI Identifier:
 22415824
 Resource Type:
 Journal Article
 Resource Relation:
 Journal Name: Journal of Chemical Physics; Journal Volume: 142; Journal Issue: 2; Other Information: (c) 2015 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
 Country of Publication:
 United States
 Language:
 English
 Subject:
 71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; ALGORITHMS; APPROXIMATIONS; COMPARATIVE EVALUATIONS; DIPOLE MOMENTS; ELECTRONS; EXPECTATION VALUE; EXTRAPOLATION; GROUND STATES; LITHIUM HYDRIDES; MOLECULES; MONTE CARLO METHOD; POLARIZABILITY; WATER; WAVE FUNCTIONS
Citation Formats
Ospadov, Egor, and Rothstein, Stuart M., Email: srothstein@brocku.ca. A puresampling quantum Monte Carlo algorithm. United States: N. p., 2015.
Web. doi:10.1063/1.4905664.
Ospadov, Egor, & Rothstein, Stuart M., Email: srothstein@brocku.ca. A puresampling quantum Monte Carlo algorithm. United States. doi:10.1063/1.4905664.
Ospadov, Egor, and Rothstein, Stuart M., Email: srothstein@brocku.ca. 2015.
"A puresampling quantum Monte Carlo algorithm". United States.
doi:10.1063/1.4905664.
@article{osti_22415824,
title = {A puresampling quantum Monte Carlo algorithm},
author = {Ospadov, Egor and Rothstein, Stuart M., Email: srothstein@brocku.ca},
abstractNote = {The objective of puresampling quantum Monte Carlo is to calculate physical properties that are independent of the importance sampling function being employed in the calculation, save for the mismatch of its nodal hypersurface with that of the exact wave function. To achieve this objective, we report a puresampling algorithm that combines features of forward walking methods of puresampling and reptation quantum Monte Carlo (RQMC). The new algorithm accurately samples properties from the mixed and pure distributions simultaneously in runs performed at a single set of timesteps, over which extrapolation to zero timestep is performed. In a detailed comparison, we found RQMC to be less efficient. It requires different sets of timesteps to accurately determine the energy and other properties, such as the dipole moment. We implement our algorithm by systematically increasing an algorithmic parameter until the properties converge to statistically equivalent values. As a proof in principle, we calculated the fixednode energy, static α polarizability, and other oneelectron expectation values for the groundstates of LiH and water molecules. These quantities are free from importance sampling bias, population control bias, timestep bias, extrapolationmodel bias, and the finitefield approximation. We found excellent agreement with the accepted values for the energy and a variety of other properties for those systems.},
doi = {10.1063/1.4905664},
journal = {Journal of Chemical Physics},
number = 2,
volume = 142,
place = {United States},
year = 2015,
month = 1
}

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