Interpretable delta-learning of GW quasiparticle energies from GGA-DFT

Interpretable delta-learning of GW quasiparticle energies from GGA-DFT

Accurate prediction of the ionization potential and electron affinity energies of small molecules are important for many applications. Density functional theory (DFT) is computationally inexpensive, but can be very inaccurate for frontier orbital energies or ionization energies. The GW method is suf...

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Bibliographic Details
Main Authors: Artem Fediai, Patrick Reiser, Jorge Enrique Olivares Peña, Wolfgang Wenzel, Pascal Friederich
Format: Article
Language:English
Published: IOP Publishing 2023-01-01
Series:Machine Learning: Science and Technology
Subjects:
delta learning
machine learning
GW
graph neural networks
GGA-DFT
Online Access:https://doi.org/10.1088/2632-2153/acf545

Internet

https://doi.org/10.1088/2632-2153/acf545

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