Publications

2025

  1. Scalable machine learning model for energy decomposition analysis in aqueous systems
    Hossein Tahmasbi, Michael Beerbaum, Bartosz Brzoza, Attila Cangi, and Thomas D. Kühne
    J. Chem. Phys., 2025
    DOI
    0 Google Scholar citations
  2. Materials Learning Algorithms (MALA): Scalable machine learning for electronic structure calculations in large-scale atomistic simulations
    Attila Cangi, Lenz Fiedler, Bartosz Brzoza, Karan Shah, Timothy J. Callow, Daniel Kotik, Steve Schmerler, Matthew C. Barry, James Goff, Andrew Rohskopf, and 4 more authors
    Comput. Phys. Commun., 2025
    DOI
    5 Google Scholar citations
  3. Strong geometry dependence of the x-ray Thomson scattering spectrum in single crystal silicon
    Thomas Gawne, Zhandos A. Moldabekov, Oliver Humphries, Karen Appel, Carsten Bähtz, V. Bouffetier, E. Brambrink, Attila Cangi, Céline Crépisson, Sebastian Göde, and 10 more authors
    Electron. Struct., 2025
    DOI
    4 Google Scholar citations
  4. Towards all-electron treatment in electronic structure machine learning
    Johannes Wasmer, Philipp Rüssmann, Stefano Sanvito, Attila Cangi, and Ira Assent
    JuSER Publ., 2025
    DOI

2024

  1. Probing iron in Earth’s core with molecular-spin dynamics
    Svetoslav Nikolov, Kushal Ramakrishna, Andrew Rohskopf, Mani Lokamani, Julien Tranchida, John H. Carpenter, Attila Cangi, and Mitchell Wood
    Proc. Natl. Acad. Sci., 2024
    DOI
    8 Google Scholar citations
  2. Electrical conductivity of warm dense hydrogen from ohm’s law and time-dependent density functional theory
    Kushal Ramakrishna, Mani Lokamani, and Attila Cangi
    Electron. Struct., 2024
    DOI
    3 Google Scholar citations
  3. Bridging the gap in electronic structure calculations via machine learning
    Attila Cangi
    Nat. Comput. Sci., 2024
    DOI
    1 Google Scholar citations
  4. Effects of mosaic crystal instrument functions on x-ray Thomson scattering diagnostics
    Thomas Gawne, Hannah M. Bellenbaum, L. B. Fletcher, Karen Appel, Carsten Baehtz, V. Bouffetier, E. Brambrink, D. B. Brown, Attila Cangi, Adrien Descamps, and 29 more authors
    J. Appl. Phys., 2024
    DOI
    16 Google Scholar citations
  5. Ultrahigh resolution x-ray Thomson scattering measurements at the European X-ray Free Electron Laser
    Thomas Gawne, Zhandos A. Moldabekov, Oliver Humphries, Karen Appel, Carsten Baehtz, V. Bouffetier, E. Brambrink, Attila Cangi, Sebastian Göde, Zuzana Konôpková, and 11 more authors
    Phys. Rev. B, 2024
    DOI
    22 Google Scholar citations
  6. Machine learning-driven structure prediction for iron hydrides
    Hossein Tahmasbi, Kushal Ramakrishna, Mani Lokamani, and Attila Cangi
    Phys. Rev. Mater., 2024
    DOI
    5 Google Scholar citations
  7. Inverting the Kohn–Sham equations with physics-informed machine learning
    Vincent Martinetto, Karan Shah, Attila Cangi, and Aurora Pribram−Jones
    Mach. Learn. Sci. Technol., 2024
    DOI
    5 Google Scholar citations

2023

  1. Physics-enhanced neural networks for equation-of-state calculations
    Timothy J. Callow, Jan Nikl, Eli Kraisler, and Attila Cangi
    Mach. Learn. Sci. Technol., 2023
    DOI
    2 Google Scholar citations
  2. Ab initio insights on the ultrafast strong-field dynamics of anatase TiO2
    Sruthil Lal S. B., Mani Lokamani, Kushal Ramakrishna, Attila Cangi, D. Murali, M. Posselt, Assa Aravindh Sasikala Devi, and Alok Sharan
    Phys. Rev. B, 2023
    DOI
  3. International Conference on “Strongly Coupled Coulomb Systems” (July 24–29, 2022, Görlitz, Germany)
    Attila Cangi, Zhandos A. Moldabekov, and D. Neilson
    Contrib. Plasma Phys., 2023
    DOI
  4. Machine learning the electronic structure of matter across temperatures
    Lenz Fiedler, Normand A. Modine, Kyle D. Miller, and Attila Cangi
    Phys. Rev. B, 2023
    DOI
    17 Google Scholar citations
  5. Impact of electronic correlations on high-pressure iron: insights from time-dependent density functional theory
    Kushal Ramakrishna, Mani Lokamani, Andrew Baczewski, Jan Vorberger, and Attila Cangi
    Electron. Struct., 2023
    DOI
    5 Google Scholar citations
  6. Transferable interatomic potential for aluminum from ambient conditions to warm dense matter
    Sandeep Kumar, Hossein Tahmasbi, Kushal Ramakrishna, Mani Lokamani, Svetoslav Nikolov, Julien Tranchida, Mitchell Wood, and Attila Cangi
    Phys. Rev. Res., 2023
    DOI
    11 Google Scholar citations
  7. Predicting electronic structures at any length scale with machine learning
    Lenz Fiedler, Normand A. Modine, Steve Schmerler, Dayton J. Vogel, Gabriel Popoola, Aidan P. Thompson, Sivasankaran Rajamanickam, and Attila Cangi
    npj Comput. Mater., 2023
    DOI
    65 Google Scholar citations
  8. Improving dynamic collision frequencies: Impacts on dynamic structure factors and stopping powers in warm dense matter
    Thomas W. Hentschel, Alina Kononov, Alexandra Olmstead, Attila Cangi, Andrew Baczewski, and Stephanie B. Hansen
    Phys. Plasmas, 2023
    DOI
    20 Google Scholar citations
  9. Imaginary-time correlation function thermometry: A new, high-accuracy and model-free temperature analysis technique for x-ray Thomson scattering data
    Tobias Dornheim, Maximilian Böhme, D. A. Chapman, D. Kraus, Thomas R. Preston, Zhandos A. Moldabekov, Niclas Schlünzen, Attila Cangi, T. Döppner, and Jan Vorberger
    Phys. Plasmas, 2023
    DOI
    43 Google Scholar citations
  10. Electrical conductivity of iron in Earth’s core from microscopic Ohm’s law
    Kushal Ramakrishna, Mani Lokamani, Andrew Baczewski, Jan Vorberger, and Attila Cangi
    Phys. Rev. B, 2023
    DOI
    20 Google Scholar citations
  11. Electronic density response of warm dense matter
    Tobias Dornheim, Zhandos A. Moldabekov, Kushal Ramakrishna, P. Tolias, Andrew Baczewski, D. Kraus, Thomas R. Preston, D. A. Chapman, Maximilian Böhme, T. Döppner, and 4 more authors
    Phys. Plasmas, 2023
    DOI
    98 Google Scholar citations
  12. A shallow hybrid classical–quantum spiking feedforward neural network for noise-robust image classification
    Debanjan Konar, Aditya Das Sarma, Soham Bhandary, Siddhartha Bhattacharyya, Attila Cangi, and Vaneet Aggarwal
    Appl. Soft Comput., 2023
    DOI
    78 Google Scholar citations
  13. Assessing the accuracy of hybrid exchange-correlation functionals for the density response of warm dense electrons
    Zhandos A. Moldabekov, Mani Lokamani, Jan Vorberger, Attila Cangi, and Tobias Dornheim
    J. Chem. Phys., 2023
    DOI
    26 Google Scholar citations
  14. Non-empirical Mixing Coefficient for Hybrid XC Functionals from Analysis of the XC Kernel
    Zhandos A. Moldabekov, Mani Lokamani, Jan Vorberger, Attila Cangi, and Tobias Dornheim
    J. Phys. Chem. Lett., 2023
    DOI
    31 Google Scholar citations
  15. Improved calculations of mean ionization states with an average-atom model
    Timothy J. Callow, Eli Kraisler, and Attila Cangi
    Phys. Rev. Res., 2023
    DOI
    14 Google Scholar citations

2022

  1. Accelerating equilibration in first-principles molecular dynamics with orbital-free density functional theory
    Lenz Fiedler, Zhandos A. Moldabekov, Xuecheng Shao, Kaili Jiang, Tobias Dornheim, Michele Pavanello, and Attila Cangi
    Phys. Rev. Res., 2022
    DOI
    0 Google Scholar citations
  2. Training-free hyperparameter optimization of neural networks for electronic structures in matter
    Lenz Fiedler, Nils Hoffmann, Parvez Mohammed, Gabriel A. Popoola, Tamar Yovell, Vladyslav Oles, John Ellis, Sivasankaran Rajamanickam, and Attila Cangi
    Mach. Learn. Sci. Technol., 2022
    DOI
    23 Google Scholar citations
  3. Ab initio study of shock-compressed copper
    Maximilian Schörner, B. B. L. Witte, Andrew Baczewski, Attila Cangi, and R. Redmer
    Phys. Rev. B, 2022
    DOI
  4. Effective electronic forces and potentials from ab initio path integral Monte Carlo simulations
    Tobias Dornheim, P. Tolias, Zhandos A. Moldabekov, Attila Cangi, and Jan Vorberger
    J. Chem. Phys., 2022
    DOI
  5. First-principles derivation and properties of density-functional average-atom models
    Timothy J. Callow, S. B. Hansen, Eli Kraisler, and Attila Cangi
    Phys. Rev. Res., 2022
    DOI
    21 Google Scholar citations
  6. Deep dive into machine learning density functional theory for materials science and chemistry
    Lenz Fiedler, Karan Shah, Michael Bußmann, and Attila Cangi
    Phys. Rev. Mater., 2022
    DOI
    140 Google Scholar citations
  7. Towards a quantum fluid theory of correlated many-fermion systems from first principles
    Zhandos A. Moldabekov, Tobias Dornheim, G. Gregori, Frank Graziani, M. Bönitz, and Attila Cangi
    SciPost Phys., 2022
    DOI
    24 Google Scholar citations
  8. Dissociating the phononic, magnetic and electronic contributions to thermal conductivity: a computational study in alpha-iron
    Svetoslav Nikolov, Julien Tranchida, Kushal Ramakrishna, Mani Lokamani, Attila Cangi, and Mitchell Wood
    J. Mater. Sci., 2022
    DOI
    10 Google Scholar citations
  9. Benchmarking exchange-correlation functionals in the spin-polarized inhomogeneous electron gas under warm dense conditions
    Zhandos A. Moldabekov, Tobias Dornheim, Jan Vorberger, and Attila Cangi
    Phys. Rev. B, 2022
    DOI
    38 Google Scholar citations
  10. Thermal excitation signals in the inhomogeneous warm dense electron gas
    Zhandos A. Moldabekov, Tobias Dornheim, and Attila Cangi
    Sci. Rep., 2022
    DOI
    18 Google Scholar citations
  11. atoMEC: An open-source average-atom Python code
    Timothy J. Callow, Daniel Kotik, Eli Kraisler, and Attila Cangi
    Proc. Python Sci. Conf., 2022
    DOI
    5 Google Scholar citations

2021

  1. Higher harmonics in complex plasmas with alternating screening
    Zhandos A. Moldabekov, Ye. K. Aldakul, N. Kh. Bastykova, Sita Sundar, and Attila Cangi
    Phys. Rev. Res., 2021
    DOI
    5 Google Scholar citations
  2. Dataset and scripts for A Deep Dive into Machine Learning Density Functional Theory for Materials Science and Chemistry
    Lenz Fiedler, Karan Shah, Attila Cangi, and Michael Bußmann
    RODARE, 2021
    DOI
  3. Data associated with the publication "The relevance of electronic perturbations in the warm dense electron gas"
    Zhandos A. Moldabekov, Tobias Dornheim, Maximilian Böhme, Jan Vorberger, and Attila Cangi
    RODARE, 2021
    DOI
  4. Accelerating finite-temperature Kohn-Sham density functional theory with deep neural networks
    John Ellis, Lenz Fiedler, Gabriel A. Popoola, Normand A. Modine, J. A. Stephens, Aidan P. Thompson, Attila Cangi, and Sivasankaran Rajamanickam
    Phys. Rev. B, 2021
    DOI
    102 Google Scholar citations
  5. LDOS/SNAP data for MALA: Aluminium at 298K and 933K
    John Ellis, Lenz Fiedler, Gabriel A. Popoola, Normand A. Modine, John A. Stephens, Aidan P. Thompson, Attila Cangi, and S. Rajamanickam
    RODARE, 2021
    DOI
  6. First-principles modeling of plasmons in aluminum under ambient and extreme conditions
    Kushal Ramakrishna, Attila Cangi, Tobias Dornheim, Andrew Baczewski, and Jan Vorberger
    Phys. Rev. B, 2021
    DOI
    48 Google Scholar citations

2020

  1. Effective Static Approximation: A Fast and Reliable Tool for Warm-Dense Matter Theory
    Tobias Dornheim, Attila Cangi, Kushal Ramakrishna, Maximilian Böhme, Shigenori Tanaka, and Jan Vorberger
    Phys. Rev. Lett., 2020
    DOI
    94 Google Scholar citations

2017

  1. Exchange-correlation approximations for reduced-density-matrix-functional theory at finite temperature: Capturing magnetic phase transitions in the homogeneous electron gas
    Tim Baldsiefen, Attila Cangi, F. G. Eich, and E. K. U. Gross
    Phys. rev., A/Physical rev. A, 2017
    DOI
    10 Google Scholar citations

2015

  1. Efficient formalism for warm dense matter simulations
    Attila Cangi and Aurora Pribram−Jones
    Phys. Rev. B, 2015
    DOI
    15 Google Scholar citations
  2. Almost exact exchange at almost no computational cost in electronic structure
    Peter Elliott, Attila Cangi, Stefano Pittalis, E. K. U. Gross, and Kieron Burke
    Phys. Rev. A, 2015
    DOI
    18 Google Scholar citations
  3. Corrections to Thomas-Fermi Densities at Turning Points and Beyond
    Raphael F. Ribeiro, Donghyung Lee, Attila Cangi, Peter Elliott, and Kieron Burke
    Phys. Rev. Lett., 2015
    DOI
    41 Google Scholar citations

2014

  1. Virial theorem and exact properties of density functionals for periodic systems
    Hossein Mirhosseini, Attila Cangi, Tim Baldsiefen, Antonio Sanna, C. R. Proetto, and E. K. U. Gross
    Phys. Rev. B, 2014
    DOI
    1 Google Scholar citations

2013

  1. Potential functionals versus density functionals
    Attila Cangi, E. K. U. Gross, and Kieron Burke
    Phys. Rev. A, 2013
    DOI
    37 Google Scholar citations

2011

  1. Electronic Structure via Potential Functional Approximations
    Attila Cangi, Donghyung Lee, Peter Elliott, Kieron Burke, and E. K. U. Gross
    Phys. Rev. Lett., 2011
    DOI
    55 Google Scholar citations

2010

  1. Leading corrections to local approximations
    Attila Cangi, Donghyung Lee, Peter Elliott, and Kieron Burke
    Phys. Rev. B, 2010
    DOI
    52 Google Scholar citations

2008

  1. Semiclassical Origins of Density Functionals
    Peter Elliott, Donghyung Lee, Attila Cangi, and Kieron Burke
    Phys. Rev. Lett., 2008
    DOI
    120 Google Scholar citations