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Title: Communication: Energy benchmarking with quantum Monte Carlo for water nano-droplets and bulk liquid water

Abstract

In this work, we show the feasibility of using quantum Monte Carlo (QMC) to compute benchmark energies for configuration samples of thermal-equilibrium water clusters and the bulk liquid containing up to 64 molecules. Evidence that the accuracy of these benchmarks approaches that of basis-set converged coupled-cluster calculations is noted. We illustrate the usefulness of the benchmarks by using them to analyze the errors of the popular BLYP approximation of density functional theory (DFT). Finally, the results indicate the possibility of using QMC as a routine tool for analyzing DFT errors for non-covalent bonding in many types of condensed-phase molecular system.

Authors:
 [1];  [2];  [2];  [1]
+ Show Author Affiliations
  1. Univ. College London, Bloomsbury (United Kingdom)
  2. Univ. of Cambridge (United Kingdom)
Publication Date:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1565006
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Chemical Physics
Additional Journal Information:
Journal Volume: 138; Journal Issue: 22; Journal ID: ISSN 0021-9606
Publisher:
American Institute of Physics (AIP)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY

Citation Formats

Alfè, D., Bartók, A. P., Csányi, G., and Gillan, M. J. Communication: Energy benchmarking with quantum Monte Carlo for water nano-droplets and bulk liquid water. United States: N. p., 2013. Web. doi:10.1063/1.4810882.
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Alfè, D., Bartók, A. P., Csányi, G., & Gillan, M. J. Communication: Energy benchmarking with quantum Monte Carlo for water nano-droplets and bulk liquid water. United States. https://doi.org/10.1063/1.4810882
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Alfè, D., Bartók, A. P., Csányi, G., and Gillan, M. J. Wed . "Communication: Energy benchmarking with quantum Monte Carlo for water nano-droplets and bulk liquid water". United States. https://doi.org/10.1063/1.4810882. https://www.osti.gov/servlets/purl/1565006.
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@article{osti_1565006,
title = {Communication: Energy benchmarking with quantum Monte Carlo for water nano-droplets and bulk liquid water},
author = {Alfè, D. and Bartók, A. P. and Csányi, G. and Gillan, M. J.},
abstractNote = {In this work, we show the feasibility of using quantum Monte Carlo (QMC) to compute benchmark energies for configuration samples of thermal-equilibrium water clusters and the bulk liquid containing up to 64 molecules. Evidence that the accuracy of these benchmarks approaches that of basis-set converged coupled-cluster calculations is noted. We illustrate the usefulness of the benchmarks by using them to analyze the errors of the popular BLYP approximation of density functional theory (DFT). Finally, the results indicate the possibility of using QMC as a routine tool for analyzing DFT errors for non-covalent bonding in many types of condensed-phase molecular system.},
doi = {10.1063/1.4810882},
journal = {Journal of Chemical Physics},
number = 22,
volume = 138,
place = {United States},
year = {Wed Jun 12 00:00:00 EDT 2013},
month = {Wed Jun 12 00:00:00 EDT 2013}
}
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Journal Article:
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Publisher's Version of Record
https://doi.org/10.1063/1.4810882
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Cited by: 27 works
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Figures / Tables:

FIG. 1 FIG. 1: Energy errors of BLYP functional after correction for 1-body (BLYP-1), 1- and 2-body (BLYP-2) and 1-, 2-, and 3-body (BLYP-3) errors for thermal samples of 100 configurations of the (H2O)6 (left panel) and (H2O)15 (right panel) clusters. Errors (deviations from DMC benchmarks) are plotted against squared radius of gyrationmore » $R$$^{2}_{gyr}$ of the cluster. Configurations are from a single simulation with the TTM3-F model for the 6-mer but from two separate simulations (identified as tf and te) for the 15-mer. Units: m$E$h/monomer.« less
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