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GPAW: An open Python package for electronic structure calculations

GPAW: حزمة بايثون مفتوحة لحسابات البنية الإلكترونية
Authors: Jens Jørgen Mortensen; Ask Hjorth Larsen; Mikael Kuisma; Aleksei V. Ivanov; Alireza Taghizadeh; Andrew A. Peterson; Anubhab Haldar; +40 Authors

GPAW: An open Python package for electronic structure calculations

Abstract

We review the GPAW open-source Python package for electronic structure calculations. GPAW is based on the projector-augmented wave method and can solve the self-consistent density functional theory (DFT) equations using three different wave-function representations, namely real-space grids, plane waves, and numerical atomic orbitals. The three representations are complementary and mutually independent and can be connected by transformations via the real-space grid. This multi-basis feature renders GPAW highly versatile and unique among similar codes. By virtue of its modular structure, the GPAW code constitutes an ideal platform for the implementation of new features and methodologies. Moreover, it is well integrated with the Atomic Simulation Environment (ASE), providing a flexible and dynamic user interface. In addition to ground-state DFT calculations, GPAW supports many-body GW band structures, optical excitations from the Bethe–Salpeter Equation, variational calculations of excited states in molecules and solids via direct optimization, and real-time propagation of the Kohn–Sham equations within time-dependent DFT. A range of more advanced methods to describe magnetic excitations and non-collinear magnetism in solids are also now available. In addition, GPAW can calculate non-linear optical tensors of solids, charged crystal point defects, and much more. Recently, support for graphics processing unit (GPU) acceleration has been achieved with minor modifications to the GPAW code thanks to the CuPy library. We end the review with an outlook, describing some future plans for GPAW.

Keywords

Electronic Structure Calculations, optiset ominaisuudet, Physical Chemistry, 114, Resurssiviisausyhteisö, avoin lähdekoodi, Computational Chemistry, 104011 Materials chemistry, Materials Chemistry, magnetismi, Condensed Matter - Materials Science, Physics, Python (programming language), Computational science, Computational Physics (physics.comp-ph), laskennallinen kemia, Condensed Matter Physics, sähkökemia, Atomic and Molecular Physics, and Optics, Chemistry, Nanoscience Center, Physical Sciences, 103018 Materials physics, Physics - Computational Physics, Kohn-Sham equation, optical properties, Electronic structure, Atom and Molecular Physics and Optics, projector augmented wave method, Materials Science, School of Resource Wisdom, FOS: Physical sciences, 530, Quantum mechanics, Advancements in Density Functional Theory, 102009 Computer simulation, electronic structure methods, programming languages, simulointi, Theoretical Chemistry, Kemia, density functional theory, Molecular Simulations, Accelerating Materials Innovation through Informatics, tiheysfunktionaaliteoria, Fysikaalinen kemia, 103018 Materialphysik, High-Temperature Superconductivity, Materials Science (cond-mat.mtrl-sci), 540, Computer science, Bethe-Salpeter equation, 104011 Materialchemie, Operating system, Physics and Astronomy, electronic band structure, Density functional theory, nanohiukkaset, Python, 102009 Computersimulation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
170
Top 1%
Top 10%
Top 0.1%
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