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General Correlated Geminal Ansatz for Electronic Structure Calculations: Exploiting Pfaffians in Place of Determinants

Genovese C.
•
Shirakawa T.
•
Nakano K.
•
Sorella S.
2020
  • journal article

Periodico
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
Abstract
We propose here a single Pfaffian correlated variational ansatz that dramatically improves the accuracy with respect to the single determinant one, while remaining at a similar computational cost. A much larger correlation energy is indeed determined by the most general two electron pairing function, including both singlet and triplet channels, combined with a many-body Jastrow factor, including all possible spin-spin, spin-density, and density-density terms. The main technical ingredient to exploit this accuracy is the use of the Pfaffian for antisymmetrizing a highly correlated pairing function, thus recovering the Fermi statistics for electrons with an affordable computational cost. Moreover, the application of the diffusion Monte Carlo, within the fixed node approximation, allows us to obtain very accurate binding energies for the first preliminary calculations reported in this study: C2, N2, and O2 and the benzene molecule. This is promising and remarkable, considering that they represent extremely difficult molecules even for computationally demanding multideterminant approaches, and opens therefore the way for realistic and accurate electronic simulations with an algorithm scaling at most as the fourth power of the number of electrons.
DOI
10.1021/acs.jctc.0c00165
WOS
WOS:000580954000013
Archivio
http://hdl.handle.net/20.500.11767/115146
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85092944874
https://pubs.acs.org/doi/10.1021/acs.jctc.0c00165
https://arxiv.org/abs/2002.03347v3
Diritti
closed access
Soggetti
  • Pfaffian wave functio...

  • Quantum Monte Carlo

  • Settore FIS/03 - Fisi...

Scopus© citazioni
7
Data di acquisizione
Jun 14, 2022
Vedi dettagli
Web of Science© citazioni
11
Data di acquisizione
Mar 28, 2024
Visualizzazioni
1
Data di acquisizione
Apr 19, 2024
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