TY - JOUR
T1 - GPAW
T2 - An open Python package for electronic structure calculations
AU - Mortensen, Jens Jørgen
AU - Larsen, Ask Hjorth
AU - Kuisma, Mikael
AU - Ivanov, Aleksei V.
AU - Taghizadeh, Alireza
AU - Peterson, Andrew
AU - Haldar, Anubhab
AU - Dohn, Asmus Ougaard
AU - Schäfer, Christian
AU - Jónsson, Elvar Örn
AU - Hermes, Eric D.
AU - Nilsson, Fredrik Andreas
AU - Kastlunger, Georg
AU - Levi, Gianluca
AU - Jónsson, Hannes
AU - Häkkinen, Hannu
AU - Fojt, Jakub
AU - Kangsabanik, Jiban
AU - Sødequist, Joachim
AU - Lehtomäki, Jouko
AU - Heske, Julian
AU - Enkovaara, Jussi
AU - Winther, Kirsten Trøstrup
AU - Dulak, Marcin
AU - Melander, Marko M.
AU - Ovesen, Martin
AU - Louhivuori, Martti
AU - Walter, Michael
AU - Gjerding, Morten
AU - Lopez-Acevedo, Olga
AU - Erhart, Paul
AU - Warmbier, Robert
AU - Würdemann, Rolf
AU - Kaappa, Sami
AU - Latini, Simone
AU - Boland, Tara Maria
AU - Bligaard, Thomas
AU - Skovhus, Thorbjørn
AU - Susi, Toma
AU - Maxson, Tristan
AU - Rossi, Tuomas
AU - Chen, Xi
AU - Schmerwitz, Yorick Leonard A.
AU - Schiøtz, Jakob
AU - Olsen, Thomas
AU - Jacobsen, Karsten Wedel
AU - Thygesen, Kristian Sommer
N1 - Funding Information:
K.S.T. acknowledges funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program Grant No. 773122 (LIMA) and Grant Agreement No. 951786 (NOMAD CoE). K.S.T. is a Villum Investigator supported by VILLUM FONDEN (Grant No. 37789). Funding for A.O.D., G.L., and Y.L.A.S. was provided by the Icelandic Research Fund (Grant Nos. 196279, 217734, and 217751, respectively). F.N. has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant Agreement No. 899987. M.M.M. was supported by the Academy of Finland (Grant No. 338228). T.O. acknowledges support from the Villum Foundation Grant No. 00029378. S.K. and K.W.J. acknowledge support from the VILLUM Center for Science of Sustainable Fuels and Chemicals, which is funded by the VILLUM Fonden research (Grant No. 9455). T.B. was funded by the Danish National Research Foundation (DNRF Grant No. 146). J.S. acknowledges funding from the Independent Research Fund Denmark (DFF-FTP) through Grant No. 9041-00161B. C.S. acknowledges support from the Swedish Research Council (VR) through Grant No. 2016-06059 and funding from the Horizon Europe research and innovation program of the European Union under the Marie Skłodowska-Curie Grant Agreement No. 101065117. Partially funded by the European Union. The views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or REA. Neither the European Union nor the granting authority can be held responsible for them. T.S. received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (Grant Agreement No. 756277-ATMEN). O.L.-A. has been supported by Minciencias and the University of Antioquia (Colombia). K.T.W. was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division, Catalysis Science Program, and the SUNCAT Center for Interface Science and Catalysis. G.K. acknowledges funding from V-Sustain: The VILLUM Centre for the Science of Sustainable Fuels and Chemicals (Grant No. 9455). Additional funding: Knut and Alice Wallenberg Foundation (Grant No. 2019.0140; J.F. and P.E.), the Swedish Research Council (Grant No. 2020-04935; J.F. and P.E.), the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant Agreement No. 101065117 (C.S.). Computations and code development work have been enabled by the resources provided by the Niflheim Linux cluster supercomputer installed at the Department of Physics at the Technical University of Denmark, CSC–IT Center for Science, Finland, through national supercomputers and through access to the LUMI supercomputer owned by the EuroHPC Joint Undertaking, and the National Academic Infrastructure for Supercomputing in Sweden (NAISS) at NSC, PDC, and C3SE, partially funded by the Swedish Research Council through Grant Agreement No. 2022-06725. We gratefully acknowledge these organizations for providing computational resources and facilities.
Funding Information:
K.S.T. acknowledges funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program Grant No. 773122 (LIMA) and Grant Agreement No. 951786 (NOMAD CoE). K.S.T. is a Villum Investigator supported by VILLUM FONDEN (Grant No. 37789). Funding for A.O.D., G.L., and Y.L.A.S. was provided by the Icelandic Research Fund (Grant Nos. 196279, 217734, and 217751, respectively). F.N. has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant Agreement No. 899987. M.M.M. was supported by the Academy of Finland (Grant No. 338228). T.O. acknowledges support from the Villum Foundation Grant No. 00029378. S.K. and K.W.J. acknowledge support from the VILLUM Center for Science of Sustainable Fuels and Chemicals, which is funded by the VILLUM Fonden research (Grant No. 9455). T.B. was funded by the Danish National Research Foundation (DNRF Grant No. 146). J.S. acknowledges funding from the Independent Research Fund Denmark (DFF-FTP) through Grant No. 9041-00161B. C.S. acknowledges support from the Swedish Research Council (VR) through Grant No. 2016-06059 and funding from the Horizon Europe research and innovation program of the European Union under the Marie Skłodowska-Curie Grant Agreement No. 101065117. Partially funded by the European Union. The views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or REA. Neither the European Union nor the granting authority can be held responsible for them. T.S. received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (Grant Agreement No. 756277-ATMEN). O.L.-A. has been supported by Minciencias and the University of Antioquia (Colombia). K.T.W. was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division, Catalysis Science Program, and the SUNCAT Center for Interface Science and Catalysis. G.K. acknowledges funding from V-Sustain: The VILLUM Centre for the Science of Sustainable Fuels and Chemicals (Grant No. 9455). Additional funding: Knut and Alice Wallenberg Foundation (Grant No. 2019.0140; J.F. and P.E.), the Swedish Research Council (Grant No. 2020-04935; J.F. and P.E.), the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant Agreement No. 101065117 (C.S.). Computations and code development work have been enabled by the resources provided by the Niflheim Linux cluster supercomputer installed at the Department of Physics at the Technical University of Denmark, CSC-IT Center for Science, Finland, through national supercomputers and through access to the LUMI supercomputer owned by the EuroHPC Joint Undertaking, and the National Academic Infrastructure for Supercomputing in Sweden (NAISS) at NSC, PDC, and C3SE, partially funded by the Swedish Research Council through Grant Agreement No. 2022-06725. We gratefully acknowledge these organizations for providing computational resources and facilities.
Publisher Copyright:
© 2024 Author(s).
PY - 2024/3/7
Y1 - 2024/3/7
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85186997791&partnerID=8YFLogxK
U2 - 10.1063/5.0182685
DO - 10.1063/5.0182685
M3 - Article
C2 - 38450733
AN - SCOPUS:85186997791
SN - 0021-9606
VL - 160
JO - Journal of Chemical Physics
JF - Journal of Chemical Physics
IS - 9
M1 - 092503
ER -