3 papers
cond-mat.mtrl-sci2026
MANDALA: An E(3)-Equivariant Graph Neural Network Framework for Learning Electronic-Structure Operators with Observable Guidance
Bartosz Brzoza, Wiktoria Szopa, Zakaria Elabid +5
Electronic-structure calculations based on Kohn-Sham density functional theory remain indispensable in computational materials science and chemistry. Their computational cost, howe…
cond-mat.str-el2025
Two-legged approximation for building non-empirical hybrids and analyzing correlation at finite temperature
Brittany P. Harding, Francisca Sagredo, Vincent Martinetto +1
Warm dense matter is a highly energetic phase characterized by strong correlations, thermal effects, and quantum effects of electrons. Thermal density functional theory is commonly…
physics.comp-ph2023
Inverting the Kohn-Sham equations with physics-informed machine learning
Vincent Martinetto, Karan Shah, Attila Cangi +1
Electronic structure theory calculations offer an understanding of matter at the quantum level, complementing experimental studies in materials science and chemistry. One of the mo…