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How to verify the precision of density-functional-theory implementations via reproducible and universal workflows

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Abstract
Density-functional theory methods and codes adopting periodic boundary conditions are extensively used in condensed matter physics and materials science research. In 2016, their precision (how well properties computed with different codes agree among each other) was systematically assessed on elemental crystals: a first crucial step to evaluate the reliability of such computations. In this Expert Recommendation, we discuss recommendations for verification studies aiming at further testing precision and transferability of density-functional-theory computational approaches and codes. We illustrate such recommendations using a greatly expanded protocol covering the whole periodic table from Z = 1 to 96 and characterizing 10 prototypical cubic compounds for each element: four unaries and six oxides, spanning a wide range of coordination numbers and oxidation states. The primary outcome is a reference dataset of 960 equations of state cross-checked between two all-electron codes, then used to verify and improve nine pseudopotential-based approaches. Finally, we discuss the extent to which the current results for total energies can be reused for different goals. Verification efforts of density-functional theory (DFT) calculations are of crucial importance to evaluate the reliability of simulation results. In this Expert Recommendation, we suggest metrics for DFT verification, illustrating them with an all-electron reference dataset of 960 equations of state covering the whole periodic table (hydrogen to curium) and discuss the importance of improving pseudopotential codes. Verification efforts are critical to assess the reliability of density-functional theory (DFT) simulations and provide results with properly quantified uncertainties.Developing standard computation protocols to perform verification studies and publishing curated and FAIR reference datasets can greatly aid their use to improve codes and computational approaches.The use of fully automated workflows with common interfaces between codes can guarantee uniformity, transferability and reproducibility of results.A careful description of the numerical and methodological details needed to compare with the reference datasets is essential; we discuss and illustrate this point with a dataset of 960 all-electron equations of state.Reference datasets should always include an explanation of the target property for which they were generated, and a discussion of their limits of applicability.Further extensions of DFT verification efforts are needed to cover more functionals, more computational approaches and the treatment of magnetic and relativistic (spin-orbit) effects. They should also aim at concurrently delivering optimized protocols that not only target ultimate precision, but also optimize the computational cost for a target accuracy.
Keywords
EXTENDING HIRSHFELD-I, PSEUDOPOTENTIALS, INTERFACE, LIBRARY, ABINIT, ENERGY, TABLE, BULK

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MLA
Bosoni, Emanuele, et al. “How to Verify the Precision of Density-Functional-Theory Implementations via Reproducible and Universal Workflows.” NATURE REVIEWS PHYSICS, vol. 6, 2024, pp. 45–58, doi:10.1038/s42254-023-00655-3.
APA
Bosoni, E., Beal, L., Bercx, M., Blaha, P., Bluegel, S., Broeder, J., … Pizzi, G. (2024). How to verify the precision of density-functional-theory implementations via reproducible and universal workflows. NATURE REVIEWS PHYSICS, 6, 45–58. https://doi.org/10.1038/s42254-023-00655-3
Chicago author-date
Bosoni, Emanuele, Louis Beal, Marnik Bercx, Peter Blaha, Stefan Bluegel, Jens Broeder, Martin Callsen, et al. 2024. “How to Verify the Precision of Density-Functional-Theory Implementations via Reproducible and Universal Workflows.” NATURE REVIEWS PHYSICS 6: 45–58. https://doi.org/10.1038/s42254-023-00655-3.
Chicago author-date (all authors)
Bosoni, Emanuele, Louis Beal, Marnik Bercx, Peter Blaha, Stefan Bluegel, Jens Broeder, Martin Callsen, Stefaan Cottenier, Augustin Degomme, Vladimir Dikan, Kristjan Eimre, Espen Flage-Larsen, Marco Fornari, Alberto Garcia, Luigi Genovese, Matteo Giantomassi, Sebastiaan P. Huber, Henning Janssen, Georg Kastlunger, Matthias Krack, Georg Kresse, Thomas D. Kuehne, Kurt Lejaeghere, Georg K. H. Madsen, Martijn Marsman, Nicola Marzari, Gregor Michalicek, Hossein Mirhosseini, Tiziano M. A. Mueller, Guido Petretto, Chris J. Pickard, Samuel Ponce, Gian-Marco Rignanese, Oleg Rubel, Thomas Ruh, Michael Sluydts, Danny Vanpoucke, Sudarshan Vijay, Michael Wolloch, Daniel Wortmann, Aliaksandr V. Yakutovich, Jusong Yu, Austin Zadoks, Bonan Zhu, and Giovanni Pizzi. 2024. “How to Verify the Precision of Density-Functional-Theory Implementations via Reproducible and Universal Workflows.” NATURE REVIEWS PHYSICS 6: 45–58. doi:10.1038/s42254-023-00655-3.
Vancouver
1.
Bosoni E, Beal L, Bercx M, Blaha P, Bluegel S, Broeder J, et al. How to verify the precision of density-functional-theory implementations via reproducible and universal workflows. NATURE REVIEWS PHYSICS. 2024;6:45–58.
IEEE
[1]
E. Bosoni et al., “How to verify the precision of density-functional-theory implementations via reproducible and universal workflows,” NATURE REVIEWS PHYSICS, vol. 6, pp. 45–58, 2024.
@article{01HN0C1FG3DY1C0QA61J05DPWC,
  abstract     = {{Density-functional theory methods and codes adopting periodic boundary conditions are extensively used in condensed matter physics and materials science research. In 2016, their precision (how well properties computed with different codes agree among each other) was systematically assessed on elemental crystals: a first crucial step to evaluate the reliability of such computations. In this Expert Recommendation, we discuss recommendations for verification studies aiming at further testing precision and transferability of density-functional-theory computational approaches and codes. We illustrate such recommendations using a greatly expanded protocol covering the whole periodic table from Z = 1 to 96 and characterizing 10 prototypical cubic compounds for each element: four unaries and six oxides, spanning a wide range of coordination numbers and oxidation states. The primary outcome is a reference dataset of 960 equations of state cross-checked between two all-electron codes, then used to verify and improve nine pseudopotential-based approaches. Finally, we discuss the extent to which the current results for total energies can be reused for different goals.

 Verification efforts of density-functional theory (DFT) calculations are of crucial importance to evaluate the reliability of simulation results. In this Expert Recommendation, we suggest metrics for DFT verification, illustrating them with an all-electron reference dataset of 960 equations of state covering the whole periodic table (hydrogen to curium) and discuss the importance of improving pseudopotential codes.

 Verification efforts are critical to assess the reliability of density-functional theory (DFT) simulations and provide results with properly quantified uncertainties.Developing standard computation protocols to perform verification studies and publishing curated and FAIR reference datasets can greatly aid their use to improve codes and computational approaches.The use of fully automated workflows with common interfaces between codes can guarantee uniformity, transferability and reproducibility of results.A careful description of the numerical and methodological details needed to compare with the reference datasets is essential; we discuss and illustrate this point with a dataset of 960 all-electron equations of state.Reference datasets should always include an explanation of the target property for which they were generated, and a discussion of their limits of applicability.Further extensions of DFT verification efforts are needed to cover more functionals, more computational approaches and the treatment of magnetic and relativistic (spin-orbit) effects. They should also aim at concurrently delivering optimized protocols that not only target ultimate precision, but also optimize the computational cost for a target accuracy.}},
  author       = {{Bosoni, Emanuele and  Beal, Louis and  Bercx, Marnik and  Blaha, Peter and  Bluegel, Stefan and  Broeder, Jens and Callsen, Martin and Cottenier, Stefaan and  Degomme, Augustin and  Dikan, Vladimir and  Eimre, Kristjan and  Flage-Larsen, Espen and  Fornari, Marco and  Garcia, Alberto and  Genovese, Luigi and  Giantomassi, Matteo and  Huber, Sebastiaan P. and  Janssen, Henning and  Kastlunger, Georg and  Krack, Matthias and  Kresse, Georg and  Kuehne, Thomas D. and Lejaeghere, Kurt and  Madsen, Georg K. H. and  Marsman, Martijn and  Marzari, Nicola and  Michalicek, Gregor and  Mirhosseini, Hossein and  Mueller, Tiziano M. A. and  Petretto, Guido and  Pickard, Chris J. and  Ponce, Samuel and  Rignanese, Gian-Marco and  Rubel, Oleg and Ruh, Thomas and Sluydts, Michael and Vanpoucke, Danny and  Vijay, Sudarshan and  Wolloch, Michael and  Wortmann, Daniel and  Yakutovich, Aliaksandr V. and  Yu, Jusong and  Zadoks, Austin and  Zhu, Bonan and  Pizzi, Giovanni}},
  issn         = {{2522-5820}},
  journal      = {{NATURE REVIEWS PHYSICS}},
  keywords     = {{EXTENDING HIRSHFELD-I,PSEUDOPOTENTIALS,INTERFACE,LIBRARY,ABINIT,ENERGY,TABLE,BULK}},
  language     = {{eng}},
  pages        = {{45--58}},
  title        = {{How to verify the precision of density-functional-theory implementations via reproducible and universal workflows}},
  url          = {{http://doi.org/10.1038/s42254-023-00655-3}},
  volume       = {{6}},
  year         = {{2024}},
}

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