Semi-Empirical Shadow Molecular Dynamics: A PyTorch Implementation.
Journal
Journal of chemical theory and computation
ISSN: 1549-9626
Titre abrégé: J Chem Theory Comput
Pays: United States
ID NLM: 101232704
Informations de publication
Date de publication:
13 Jun 2023
13 Jun 2023
Historique:
medline:
10
5
2023
pubmed:
10
5
2023
entrez:
10
5
2023
Statut:
ppublish
Résumé
Extended Lagrangian Born-Oppenheimer molecular dynamics (XL-BOMD) in its most recent shadow potential energy version has been implemented in the semiempirical PyTorch-based software PySeQM. The implementation includes finite electronic temperatures, canonical density matrix perturbation theory, and an adaptive Krylov subspace approximation for the integration of the electronic equations of motion within the XL-BOMB approach (KSA-XL-BOMD). The PyTorch implementation leverages the use of GPU and machine learning hardware accelerators for the simulations. The new XL-BOMD formulation allows studying more challenging chemical systems with charge instabilities and low electronic energy gaps. The current public release of PySeQM continues our development of modular architecture for large-scale simulations employing semi-empirical quantum-mechanical treatment. Applied to molecular dynamics, simulation of 840 carbon atoms, one integration time step executes in 4 s on a single Nvidia RTX A6000 GPU.
Identifiants
pubmed: 37163680
doi: 10.1021/acs.jctc.3c00234
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM