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

• Published in: Machine learning: science and technology Vol. 4; no. 3; pp. 35045 - 35054
• Main Authors: Fediai, Artem, Reiser, Patrick, Peña, Jorge Enrique Olivares, Wenzel, Wolfgang, Friederich, Pascal
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.09.2023
• Subjects: delta learning; Density functional theory; Electron affinity; Elementary excitations; GGA-DFT; graph neural networks; Ionization potentials; Machine learning; Organic chemistry

Abstract 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 meth...