Toward a systematic improvement of the fixed-node approximation in diffusion Monte Carlo for solids - A case study in diamond

Anouar Benali, Kevin Gasperich, Kenneth D. Jordan, Thomas Applencourt, Ye Luo, M. Chandler Bennett, Jaron T. Krogel, Luke Shulenburger, Paul R.C. Kent, Pierre François Loos, Anthony Scemama, Michel Caffarel

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

While Diffusion Monte Carlo (DMC) is in principle an exact stochastic method for ab initio electronic structure calculations, in practice, the fermionic sign problem necessitates the use of the fixed-node approximation and trial wavefunctions with approximate nodes (or zeros). This approximation introduces a variational error in the energy that potentially can be tested and systematically improved. Here, we present a computational method that produces trial wavefunctions with systematically improvable nodes for DMC calculations of periodic solids. These trial wavefunctions are efficiently generated with the configuration interaction using a perturbative selection made iteratively (CIPSI) method. A simple protocol in which both exact and approximate results for finite supercells are used to extrapolate to the thermodynamic limit is introduced. This approach is illustrated in the case of the carbon diamond using Slater-Jastrow trial wavefunctions including up to one million Slater determinants. Fixed-node DMC energies obtained with such large expansions are much improved, and the fixed-node error is found to decrease monotonically and smoothly as a function of the number of determinants in the trial wavefunction, a property opening the way to a better control of this error. The cohesive energy extrapolated to the thermodynamic limit is in close agreement with the estimated experimental value. Interestingly, this is also the case at the single-determinant level, thus, indicating a very good error cancellation in carbon diamond between the bulk and atomic total fixed-node energies when using single-determinant nodes.

Original languageEnglish
Article number184111
JournalJournal of Chemical Physics
Volume153
Issue number18
DOIs
StatePublished - Nov 14 2020

Funding

The authors are grateful to Dr. Peter Doak and Dr. Qiming Sun for debugging and code implementations enabling simulations in, respectively, QMCPACK and PySCF. A.S., P.-F.L., and M.C. were supported by the ANR PhemSpec project, Grant No. ANR-18-CE30-0025-02 of the French Agence Nationale de la Recherche and the international exchange program CNRS-PICS France-USA. A.B., Y.L., M.C.B., J.T.K., P.R.C.K., and L.S. were supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Science and Engineering Division, as part of the Computational Materials Sciences Program and Center for Predictive Simulation of Functional Materials. K.G. and K.D.J. acknowledge support from the National Science Foundation under Grant No. CHE1762337. An award of computer time was provided by the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. All QMC results used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract No. DE-AC02-06CH11357 and resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract No. DE-AC05-00OR22725. For the generation of the trial wavefunction, we gratefully acknowledge the computing resources provided on Bebop, a high-performance computing cluster operated by the Laboratory Computing Resource Center at Argonne National Laboratory. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy National Nuclear Security Administration under Contract No. DE-NA0003525. This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). The authors are grateful to Dr. Peter Doak and Dr. Qim-ing Sun for debugging and code implementations enabling simulations in, respectively, QMCPACK and PySCF. A.S., P.-F.L., and M.C. were supported by the ANR PhemSpec project, Grant No. ANR-18-CE30-0025-02 of the French Agence Nationale de la Recherche and the international exchange program CNRS-PICS France-USA. A.B., Y.L., M.C.B., J.T.K., P.R.C.K., and L.S. were supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Science and Engineering Division, as part of the Computational Materials Sciences Program and Center for Predictive Simulation of Functional Materials. K.G. and K.D.J. acknowledge support from the National Science Foundation under Grant No. CHE1762337. An award of computer time was provided by the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. All QMC results used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract No. DE-AC02-06CH11357 and resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract No. DE-AC05-00OR22725. For the generation of the trial wavefunc-tion, we gratefully acknowledge the computing resources provided on Bebop, a high-performance computing cluster operated by the Laboratory Computing Resource Center at Argonne National Laboratory. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy National Nuclear Security Administration under Contract No. DE-NA0003525.

FundersFunder number
Materials Science and Engineering Division
PySCFANR-18-CE30-0025-02
U.S. Department of Energy National Nuclear Security AdministrationDE-NA0003525
National Science FoundationCHE1762337, 1762337
U.S. Department of Energy
Office of ScienceDE-AC05-00OR22725, DE-AC02-06CH11357
Basic Energy Sciences
Argonne National Laboratory
Sandia National Laboratories
Division of Materials Sciences and Engineering
Laboratory Computing Resource Center
Agence Nationale de la Recherche

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