Neural network distillation of orbital dependent density functional theory

Density functional theory (DFT) offers a desirable balance between quantitative accuracy and computational efficiency in practical many-electron calculations. Its central component, the exchange-correlation energy functional, has been approximated with increasing levels of complexity ranging from st...

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Veröffentlicht in:	arXiv.org 2024-10
Hauptverfasser:	Medvidović, Matija, Umana, Jaylyn C, Ahmadabadi, Iman, Domenico Di Sante, Flick, Johannes, Rubio, Angel
Format:	Artikel
Sprache:	eng
Schlagworte:	Approximation Artificial neural networks Complexity Datasets Density functional theory Functionals Kinetic energy Molecular structure Neural networks Nonlinear response Response functions
Online-Zugang:	Volltext
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