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Title: Sign Learning Kink-based (SiLK) Quantum Monte Carlo for molecular systems

The Sign Learning Kink (SiLK) based Quantum Monte Carlo (QMC) method is used to calculate the ab initio ground state energies for multiple geometries of the H{sub 2}O, N{sub 2}, and F{sub 2} molecules. The method is based on Feynman’s path integral formulation of quantum mechanics and has two stages. The first stage is called the learning stage and reduces the well-known QMC minus sign problem by optimizing the linear combinations of Slater determinants which are used in the second stage, a conventional QMC simulation. The method is tested using different vector spaces and compared to the results of other quantum chemical methods and to exact diagonalization. Our findings demonstrate that the SiLK method is accurate and reduces or eliminates the minus sign problem.
Authors:
 [1] ;  [2] ;  [3] ;  [4] ;  [5] ; ; ;  [1] ;  [3]
  1. Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70803 (United States)
  2. Department of Natural Sciences and Mathematics, Dominican University of California, San Rafael, California 94901 (United States)
  3. (United States)
  4. Center for Computation and Technology, Louisiana State University, Baton Rouge, Louisiana 70803 (United States)
  5. William R. Wiley Environmental Molecular Sciences Laboratory, Battelle, Pacific Northwest National Laboratory, Richland, Washington 99352 (United States)
Publication Date:
OSTI Identifier:
22493610
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Chemical Physics; Journal Volume: 144; Journal Issue: 1; Other Information: (c) 2016 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL CHEMISTRY; COMPARATIVE EVALUATIONS; COMPUTERIZED SIMULATION; FLUORINE; GROUND STATES; LEARNING; MOLECULES; MONTE CARLO METHOD; NITROGEN; OPTIMIZATION; PATH INTEGRALS; QUANTUM MECHANICS; SLATER METHOD; VECTORS; WATER