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TurboRVB: A many-body toolkit for ab initio electronic simulations by quantum Monte Carlo.
Nakano, Kousuke; Attaccalite, Claudio; Barborini, Matteo; Capriotti, Luca; Casula, Michele; Coccia, Emanuele; Dagrada, Mario; Genovese, Claudio; Luo, Ye; Mazzola, Guglielmo; Zen, Andrea; Sorella, Sandro.
Affiliation
  • Nakano K; International School for Advanced Studies (SISSA), Via Bonomea 265, 34136 Trieste, Italy.
  • Attaccalite C; Aix-Marseille Université, CNRS, CINaM UMR 7325, Campus de Luminy, 13288 Marseille, France.
  • Barborini M; CNR-NANO, Via Campi 213/a, 41125 Modena, Italy.
  • Capriotti L; New York University, Tandon School of Engineering, 6 MetroTech Center, Brooklyn, New York 11201, USA.
  • Casula M; Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie (IMPMC), Sorbonne Université, CNRS UMR 7590, IRD UMR 206, MNHN, 4 Place Jussieu, 75252 Paris, France.
  • Coccia E; Department of Chemical and Pharmaceutical Sciences, University of Trieste, Via L. Giorgieri 1, 34127 Trieste, Italy.
  • Dagrada M; Forescout Technologies, John F. Kennedylaan 2, 5612AB Eindhoven, The Netherlands.
  • Genovese C; International School for Advanced Studies (SISSA), Via Bonomea 265, 34136 Trieste, Italy.
  • Luo Y; Computational Science Division, Argonne National Laboratory, 9700 S. Cass Avenue, Lemont, Illinois 60439, USA.
  • Mazzola G; IBM Research Zurich, Säumerstrasse 4, 8803 Rüschlikon, Switzerland.
  • Zen A; Department of Earth Sciences, University College London, Gower Street, London WC1E 6BT, United Kingdom.
  • Sorella S; International School for Advanced Studies (SISSA), Via Bonomea 265, 34136 Trieste, Italy.
J Chem Phys ; 152(20): 204121, 2020 May 29.
Article in En | MEDLINE | ID: mdl-32486669
ABSTRACT
TurboRVB is a computational package for ab initio Quantum Monte Carlo (QMC) simulations of both molecular and bulk electronic systems. The code implements two types of well established QMC algorithms Variational Monte Carlo (VMC) and diffusion Monte Carlo in its robust and efficient lattice regularized variant. A key feature of the code is the possibility of using strongly correlated many-body wave functions (WFs), capable of describing several materials with very high accuracy, even when standard mean-field approaches [e.g., density functional theory (DFT)] fail. The electronic WF is obtained by applying a Jastrow factor, which takes into account dynamical correlations, to the most general mean-field ground state, written either as an antisymmetrized geminal power with spin-singlet pairing or as a Pfaffian, including both singlet and triplet correlations. This WF can be viewed as an efficient implementation of the so-called resonating valence bond (RVB) Ansatz, first proposed by Pauling and Anderson in quantum chemistry [L. Pauling, The Nature of the Chemical Bond (Cornell University Press, 1960)] and condensed matter physics [P.W. Anderson, Mat. Res. Bull 8, 153 (1973)], respectively. The RVB Ansatz implemented in TurboRVB has a large variational freedom, including the Jastrow correlated Slater determinant as its simplest, but nontrivial case. Moreover, it has the remarkable advantage of remaining with an affordable computational cost, proportional to the one spent for the evaluation of a single Slater determinant. Therefore, its application to large systems is computationally feasible. The WF is expanded in a localized basis set. Several basis set functions are implemented, such as Gaussian, Slater, and mixed types, with no restriction on the choice of their contraction. The code implements the adjoint algorithmic differentiation that enables a very efficient evaluation of energy derivatives, comprising the ionic forces. Thus, one can perform structural optimizations and molecular dynamics in the canonical NVT ensemble at the VMC level. For the electronic part, a full WF optimization (Jastrow and antisymmetric parts together) is made possible, thanks to state-of-the-art stochastic algorithms for energy minimization. In the optimization procedure, the first guess can be obtained at the mean-field level by a built-in DFT driver. The code has been efficiently parallelized by using a hybrid MPI-OpenMP protocol, which is also an ideal environment for exploiting the computational power of modern Graphics Processing Unit accelerators.

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: J Chem Phys Year: 2020 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: J Chem Phys Year: 2020 Document type: Article Affiliation country: