VAMPyR-A high-level Python library for mathematical operations in a multiwavelet representation.


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:
28 Apr 2024
Historique:
received: 13 02 2024
accepted: 02 04 2024
medline: 26 4 2024
pubmed: 26 4 2024
entrez: 26 4 2024
Statut: ppublish

Résumé

Wavelets and multiwavelets have lately been adopted in quantum chemistry to overcome challenges presented by the two main families of basis sets: Gaussian atomic orbitals and plane waves. In addition to their numerical advantages (high precision, locality, fast algorithms for operator application, linear scaling with respect to system size, to mention a few), they provide a framework that narrows the gap between the theoretical formalism of the fundamental equations and the practical implementation in a working code. This realization led us to the development of the Python library called VAMPyR (Very Accurate Multiresolution Python Routines). VAMPyR encodes the binding to a C++ library for multiwavelet calculations (algebra and integral and differential operator application) and exposes the required functionality to write a simple Python code to solve, among others, the Hartree-Fock equations, the generalized Poisson equation, the Dirac equation, and the time-dependent Schrödinger equation up to any predefined precision. In this study, we will outline the main features of multiresolution analysis using multiwavelets and we will describe the design of the code. A few illustrative examples will show the code capabilities and its interoperability with other software platforms.

Identifiants

pubmed: 38666572
pii: 3284896
doi: 10.1063/5.0203401
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Auteurs

Magnar Bjørgve (M)

Hylleraas Center, Department of Chemistry, UiT The Arctic University of Norway, P.O. Box 6050 Langnes, N-9037 Tromsø, Norway.

Christian Tantardini (C)

Hylleraas Center, Department of Chemistry, UiT The Arctic University of Norway, P.O. Box 6050 Langnes, N-9037 Tromsø, Norway.
Department of Materials Science and NanoEngineering, Rice University, Houston, Texas 77005, USA.

Stig Rune Jensen (SR)

Hylleraas Center, Department of Chemistry, UiT The Arctic University of Norway, P.O. Box 6050 Langnes, N-9037 Tromsø, Norway.

Gabriel A Gerez S (GA)

Hylleraas Center, Department of Chemistry, UiT The Arctic University of Norway, P.O. Box 6050 Langnes, N-9037 Tromsø, Norway.

Peter Wind (P)

Hylleraas Center, Department of Chemistry, UiT The Arctic University of Norway, P.O. Box 6050 Langnes, N-9037 Tromsø, Norway.

Roberto Di Remigio Eikås (R)

Hylleraas Center, Department of Chemistry, UiT The Arctic University of Norway, P.O. Box 6050 Langnes, N-9037 Tromsø, Norway.
Algorithmiq Ltd., Kanavakatu 3C, FI-00160 Helsinki, Finland.

Evgueni Dinvay (E)

Hylleraas Center, Department of Chemistry, UiT The Arctic University of Norway, P.O. Box 6050 Langnes, N-9037 Tromsø, Norway.

Luca Frediani (L)

Hylleraas Center, Department of Chemistry, UiT The Arctic University of Norway, P.O. Box 6050 Langnes, N-9037 Tromsø, Norway.

Classifications MeSH