Publications

2026

  1. Molecules Meet Language: Confound-Aware Representation Learning and Chemical Property Steering in Transformer-VAE Latent Spaces
    Zakaria Elabid, Jan Andrzejewski, Bartosz Brzoza, and Attila Cangi
    arXiv (Cornell Univ.), 2026
    DOI
    0 Google Scholar citations
  2. Machine learning time propagators for time-dependent density functional theory simulations
    Karan Shah and Attila Cangi
    Mach. Learn. Sci. Technol., 2026
    DOI
    2 Google Scholar citations

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. Prediction of atomic H adsorption energies in metalloid doped MSSe (M = Mo/W) Janus layers: A combined DFT and machine learning study
    G. Tejaswini, Anjana E Sudheer, Amrendra Kumar, M. Vallinayagam, Pavan Kumar Perepu, Attila Cangi, Mani Lokamani, M. Posselt, M. Zschornak, C. Kamal, and 2 more authors
    arXiv, 2025
    0 Google Scholar citations
  3. 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
    8 Google Scholar citations
  4. Strong geometry dependence of the x-ray Thomson scattering spectrum in single crystal silicon
    Thomas Gawne, Zhandos A. Moldabekov, Oliver Humphries, Karen Appel, Carsten Baehtz, V. Bouffetier, E. Brambrink, Attila Cangi, Céline Crépisson, Sebastian Göde, and 10 more authors
    Electron. Struct., 2025
    DOI
    8 Google Scholar citations
  5. Towards all-electron treatment in electronic structure machine learning
    Johannes Wasmer, Philipp Rüssmann, Stefano Sanvito, Attila Cangi, and Ira Assent
    JuSER (Forschungszentrum Jül.), 2025
    DOI
  6. A Vision for a World-Leading Research Software Ecosystem for the Helmholtz Association
    R. Caspart, Bernadette Fritzsch, Peter Baumgärtel, Tobias Becher, Julian Belina, Sven Berger, Julia Bicker, Maik Boltes, Michael Bussmann, Mauro Cacace, and 42 more authors
    JuSER (Forschungszentrum Jül.), 2025

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
    11 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
    6 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
    22 Google Scholar citations
  5. Accelerating Electron Dynamics Simulations through Machine Learned Time Propagators
    Karan Shah and Attila Cangi
    arXiv (Cornell Univ.), 2024
    DOI
    3 Google Scholar citations
  6. 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
    32 Google Scholar citations
  7. Machine learning-driven structure prediction for iron hydrides
    Hossein Tahmasbi, Kushal Ramakrishna, Mani Lokamani, and Attila Cangi
    Phys. Rev. Mater., 2024
    DOI
    7 Google Scholar citations
  8. Ultrahigh Resolution X-ray Thomson Scattering Measurements at the European XFEL
    Thomas Gawne, Zhandos A. Moldabekov, Oliver Humphries, Karen Appel, C. Bähtz, V. Bouffetier, E. Brambrink, Attila Cangi, Sebastian Göde, Zuzana Konôpková, and 11 more authors
    arXiv (Cornell Univ.), 2024
    DOI
    1 Google Scholar citations
  9. 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
    10 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
    0 Google Scholar citations
  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
    0 Google Scholar citations
  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
    16 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
    8 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
    16 Google Scholar citations
  7. Ab initio insights on the ultrafast strong-field dynamics of anatase TiO_2
    Sruthil Lal S. B, Lokamani, Kushal Ramakrishna, Attila Cangi, D. Murali, M. Posselt, Assa Aravindh Sasikala Devi, and Alok Sharan
    arXiv (Cornell Univ.), 2023
    DOI
  8. 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
    62 Google Scholar citations
  9. 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
    28 Google Scholar citations
  10. Transferable Interatomic Potentials 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
    arXiv (Cornell Univ.), 2023
    DOI
  11. 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
    51 Google Scholar citations
  12. 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
    25 Google Scholar citations
  13. 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
    113 Google Scholar citations
  14. 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
    86 Google Scholar citations
  15. 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
    29 Google Scholar citations
  16. 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
    34 Google Scholar citations
  17. Improved calculations of mean ionization states with an average-atom model
    Timothy J. Callow, Eli Kraisler, and Attila Cangi
    Phys. Rev. Res., 2023
    DOI
    15 Google Scholar citations

2022

  1. Temperature analysis of X-ray Thomson scattering data
    Tobias Dornheim, Maximilian Böhme, David A. Chapman, D. Kraus, Thomas R. Preston, Zhandos A. Moldabekov, Niclas Schlünzen, Attila Cangi, T. Döppner, and Jan Vorberger
    arXiv (Cornell Univ.), 2022
    DOI
    6 Google Scholar citations
  2. Physics-Informed Neural Networks as Solvers for the Time-Dependent Schrödinger Equation
    Karan Shah, Patrick Stiller, Nico Hoffmann, and Attila Cangi
    arXiv (Cornell Univ.), 2022
    DOI
  3. 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
  4. 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
    21 Google Scholar citations
  5. 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
    23 Google Scholar citations
  6. Examining the shock response of iron using molecular-spin dynamics
    Svetoslav Nikolov, Julien Tranchida, Kushal Ramakrishna, Attila Cangi, and Mitchell Wood
    2022
    DOI
    0 Google Scholar citations
  7. 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
    44 Google Scholar citations
  8. An \textitab initio study of shock-compressed copper
    Maximilian Schörner, B. B. L. Witte, Andrew Baczewski, Attila Cangi, and R. Redmer
    arXiv (Cornell Univ.), 2022
    DOI
  9. A Scalable 5,6-Qubit Grover’s Quantum Search Algorithm
    Dinesh Reddy Vemula, Debanjan Konar, Sudeep Satheesan, Sri Mounica Kalidasu, and Attila Cangi
    arXiv (Cornell Univ.), 2022
    DOI
    0 Google Scholar citations
  10. 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
    23 Google Scholar citations
  11. 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
    160 Google Scholar citations
  12. Random Quantum Neural Networks (RQNN) for Noisy Image Recognition
    Debanjan Konar, Erol Gelenbe, Soham Bhandary, Aditya Das Sarma, and Attila Cangi
    arXiv (Cornell Univ.), 2022
    DOI
    16 Google Scholar citations
  13. 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
    25 Google Scholar citations
  14. 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
  15. 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
    42 Google Scholar citations
  16. 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
  17. 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. A Deep Dive into Machine Learning Density Functional Theory for Materials Science and Chemistry
    Lenz Fiedler, Karan Shah, Michael Bußmann, and Attila Cangi
    arXiv (Cornell Univ.), 2021
    DOI
  3. 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
  4. The relevance of electronic perturbations in the warm dense electron gas
    Zhandos Moldabekov, Tobias Dornheim, Maximilian Böhme, Jan Vorberger, and Attila Cangi
    J. Chem. Phys., 2021
    DOI
    47 Google Scholar citations
  5. 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
  6. 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
  7. 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
  8. Thermal Signals from Collective Electronic Excitations in Inhomogeneous Warm Dense Matter
    Zhandos A. Moldabekov, Tobias Dornheim, and Attila Cangi
    arXiv (Cornell Univ.), 2021
    DOI
    5 Google Scholar citations
  9. A Machine-Learning Surrogate Model for ab initio Electronic Correlations at Extreme Conditions
    Tobias Dornheim, Zhandos A. Moldabekov, and Attila Cangi
    arXiv (Cornell Univ.), 2021
    DOI
    2 Google Scholar citations
  10. The Quantum Bohm Potential for Many-Fermion Systems
    Zhandos A. Moldabekov, Tobias Dornheim, G. Gregori, Frank Graziani, M. Bönitz, and Attila Cangi
    arXiv (Cornell Univ.), 2021
    1 Google Scholar citations
  11. 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
    54 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
    104 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
    16 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
    42 Google Scholar citations

2014

  1. Bypassing the malfunction junction in warm dense matter simulations
    Attila Cangi and Aurora Pribram−Jones
    arXiv (Cornell Univ.), 2014
    DOI
    2 Google Scholar citations
  2. Uniform approximations for fermionic densities
    Raphael F. Ribeiro, Donghyung Lee, Attila Cangi, Peter Elliott, and Kieron Burke
    arXiv (Cornell Univ.), 2014
  3. Almost Exact Exchange At Almost No Cost
    Peter Elliott, Attila Cangi, Stefano Pittalis, E. K. U. Gross, and Kieron Burke
    arXiv (Cornell Univ.), 2014
    DOI
    3 Google Scholar citations
  4. 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
    38 Google Scholar citations

2012

  1. Reduced Density Matrix Functional Theory at Finite Temperature:\nTheoretical Foundations
    Tim Baldsiefen, Attila Cangi, and E. K. U. Gross
    arXiv (Cornell Univ.), 2012
    DOI

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
    54 Google Scholar citations
  2. Leading Corrections to the Local Density Approximation
    Attila Cangi, Donghyung Lee, Peter Elliott, and Kieron Burke
    arXiv (Cornell Univ.), 2010

2008

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