Implementation of the self-consistent phonons method with ab initio potentials (AI-SCP).


Journal

The Journal of chemical physics
ISSN: 1089-7690
Titre abrégé: J Chem Phys
Pays: United States
ID NLM: 0375360

Informations de publication

Date de publication:
21 May 2023
Historique:
received: 15 02 2023
accepted: 24 04 2023
medline: 15 5 2023
pubmed: 15 5 2023
entrez: 15 5 2023
Statut: ppublish

Résumé

The self-consistent phonon (SCP) method allows one to include anharmonic effects when treating a many-body quantum system at thermal equilibrium. The system is then described by an effective temperature-dependent harmonic Hamiltonian, which can be used to estimate its various dynamic and static properties. In this paper, we combine SCP with ab initio (AI) potential energy evaluation in which case the numerical bottleneck of AI-SCP is the evaluation of Gaussian averages of the AI potential energy and its derivatives. These averages are computed efficiently by the quasi-Monte Carlo method utilizing low-discrepancy sequences leading to a fast convergence with respect to the number, S, of the AI energy evaluations. Moreover, a further substantial (an-order-of-magnitude) improvement in efficiency is achieved once a numerically cheap approximation of the AI potential is available. This is based on using a perturbation theory-like (the two-grid) approach in which it is the average of the difference between the AI and the approximate potential that is computed. The corresponding codes and scripts are provided.

Identifiants

pubmed: 37184023
pii: 2890485
doi: 10.1063/5.0146682
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2023 Author(s). Published under an exclusive license by AIP Publishing.

Auteurs

Colin Schiltz (C)

Department of Chemistry, University of California, Irvine, California 92697, USA.

Dmitrij Rappoport (D)

Department of Chemistry, University of California, Irvine, California 92697, USA.

Vladimir A Mandelshtam (VA)

Department of Chemistry, University of California, Irvine, California 92697, USA.

Classifications MeSH