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arXiv · 2507.08578

Abinit 2025: New Capabilities for the Predictive Modeling of Solids and Nanomaterials

Matthieu J. Verstraete·Joao Abreu·Guillaume E. Allemand·Bernard Amadon·Gabriel Antonius·Maryam Azizi·Lucas Baguet·Clementine Barat·Louis Bastogne·Romuald Bejaud·Jean-Michel Beuken·Jordan Bieder·Augustin Blanchet·Francois Bottin·Johann Bouchet·Julien Bouquiaux·Eric Bousquet·James Boust·Fabien Brieuc·Veronique Brousseau-Couture·Nils Brouwer Fabien Bruneval·Alois Castellano·Emmanuel Castiel·Jean-Baptiste Charraud·Jean Clerouin·Michel Cote·Clement Duval·Alejandro Gallo·Frederic Gendron·Gregory Geneste·Philippe Ghosez·Matteo Giantomassi·Olivier Gingras·Fernando Gomez-Ortiz·Xavier Gonze·Felix Antoine Goudreault·Andreas Gruneis·Raveena Gupta·Bogdan Guster·Donald R. Hamann·Xu He·Olle Hellman·Natalie Holzwarth·Francois Jollet·Pierre Kestener·Ioanna-Maria Lygatsika·Olivier Nadeau·Lorien MacEnulty·Enrico Marazzi·Maxime Mignolet·David D. O'Regan·Robinson Outerovitch·Charles Paillard·Guido Petretto·Samuel Ponce·Francesco Ricci·Gian-Marco Rignanese·Mauricio Rodriguez-Mayorga·Aldo H. Romero·Samare Rostami·Miquel Royo·Marc Sarraute·Alireza Sasani·Francois Soubiran·Massimiliano Stengel·Christian Tantardini·Marc Torrent·Victor Trinquet·Vasilii Vasilchencko·David Waroquiers·Asier Zabalo·Austin Zadoks·Huazhang Zhang·Josef Zwanziger
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Abstract

Abinit is a widely used scientific software package implementing density functional theory and many related functionalities for excited states and response properties. This paper presents the novel features and capabilities, both technical and scientific, which have been implemented over the past 5 years. This evolution occurred in the context of evolving hardware platforms, high-throughput calculation campaigns, and the growing use of machine learning to predict properties based on databases of first principles results. We present new methodologies for ground states with constrained charge, spin or temperature; for density functional perturbation theory extensions to flexoelectricity and polarons; and for excited states in many-body frameworks including GW, dynamical mean field theory, and coupled cluster. Technical advances have extended abinit high-performance execution to graphical processing units and intensive parallelism. Second principles methods build effective models on top of first principles results to scale up in length and time scales. Finally, workflows have been developed in different community frameworks to automate \abinit calculations and enable users to simulate hundreds or thousands of materials in controlled and reproducible conditions.

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Matthieu J. Verstraete, Joao Abreu, Guillaume E. Allemand, Bernard Amadon, Gabriel Antonius, Maryam Azizi, Lucas Baguet, Clementine Barat, Louis Bastogne, Romuald Bejaud, Jean-Michel Beuken, Jordan Bieder, Augustin Blanchet, Francois Bottin, Johann Bouchet, Julien Bouquiaux, Eric Bousquet, James Boust, Fabien Brieuc, Veronique Brousseau-Couture, Nils Brouwer Fabien Bruneval, Alois Castellano, Emmanuel Castiel, Jean-Baptiste Charraud, Jean Clerouin, Michel Cote, Clement Duval, Alejandro Gallo, Frederic Gendron, Gregory Geneste, Philippe Ghosez, Matteo Giantomassi, Olivier Gingras, Fernando Gomez-Ortiz, Xavier Gonze, Felix Antoine Goudreault, Andreas Gruneis, Raveena Gupta, Bogdan Guster, Donald R. Hamann, Xu He, Olle Hellman, Natalie Holzwarth, Francois Jollet, Pierre Kestener, Ioanna-Maria Lygatsika, Olivier Nadeau, Lorien MacEnulty, Enrico Marazzi, Maxime Mignolet, David D. O'Regan, Robinson Outerovitch, Charles Paillard, Guido Petretto, Samuel Ponce, Francesco Ricci, Gian-Marco Rignanese, Mauricio Rodriguez-Mayorga, Aldo H. Romero, Samare Rostami, Miquel Royo, Marc Sarraute, Alireza Sasani, Francois Soubiran, Massimiliano Stengel, Christian Tantardini, Marc Torrent, Victor Trinquet, Vasilii Vasilchencko, David Waroquiers, Asier Zabalo, Austin Zadoks, Huazhang Zhang, Josef Zwanziger. 2025-07-11. Abinit 2025: New Capabilities for the Predictive Modeling of Solids and Nanomaterials. https://doi.org/10.1063/5.0288278

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