Abstract
Quantum Monte Carlo (QMC) methods are some of the most accurate methods for simulating correlated electronic systems. We investigate the compatibility, strengths, and weaknesses of two such methods, namely, diffusion Monte Carlo (DMC) and auxiliary-field quantum Monte Carlo (AFQMC). The multideterminant trial wave functions employed in both approaches are generated using the configuration interaction using a perturbative selection made iteratively (CIPSI) technique. Complete basis-set full configuration interaction energies estimated with CIPSI are used as a reference in this comparative study between DMC and AFQMC. By focusing on a set of canonical finite-size solid-state systems, we show that both QMC methods can be made to systematically converge towards the same energy once basis-set effects and systematic biases have been removed. AFQMC shows a much smaller dependence on the trial wave function than DMC while simultaneously exhibiting a much larger basis-set dependence. We outline some of the remaining challenges and opportunities for improving these approaches.
| Original language | English |
|---|---|
| Article number | 161104 |
| Journal | Physical Review B |
| Volume | 102 |
| Issue number | 16 |
| DOIs | |
| State | Published - Oct 2020 |
Funding
Acknowledgments. This work has been partially supported by U.S. DOE. ORNL is managed by UT-Battelle, LLC, under Contract No. DE-AC05-00OR22725 for the U.S. Department of Energy. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript or allows others to do so for U.S. Government purposes. This work was supported by the U.S. Department of Energy (DOE), Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division, as part of the Computational Materials Sciences Program and Center for Predictive Simulation of Functional Materials (CPSFM). M.C. was supported by the ANR PhemSpec project, Grant No. ANR-18-CE30-0025-02 of the French Agence Nationale de la Recherche, and A.B. and M.C. were partially supported by the international exchange program CNRS-PICS, France-USA. An award of computer time was provided by the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. All CIPSI and DMC calculations used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract No. DE-AC02-06CH11357. AFQMC calculations received computing support from the LLNL Institutional Computing Grand Challenge program. The work of F.D.M. and M.A.M. was performed under the auspices of the U.S. DOE by LLNL under Contract No. DE-AC52-07NA27344. Sandia National Laboratories is a multimission 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's National Nuclear Security Administration under Contract No. DE-NA0003525.