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Preprint Sep 2026

Deep Learning GW Quasiparticle Hamiltonians for Many-Body Excited-State Electronic Structure at Scale

Accurate quasiparticle electronic structures are the foundation for understanding excited-state properties of materials and explaining optoelectronic, quantum, and transport phenomena. First-principles GW calculations nevertheless remain computationally intensive for large or configurationally complex systems. Here we...

Xiao-Xun Gong, Ze-Chen Tang, Woochang Kim et al. · 0 citations
Preprint Aug 2026

Ab initio-based Deep-Learning Prediction of Carrier Mobility in Strongly Anharmonic Materials

Predicting charge transport in strongly anharmonic materials, particularly ultralow thermal conductors, remains a major challenge for first-principles methods. In such systems, perturbative treatments of electron-phonon interactions and the harmonic phonon picture often break down, necessitating non-perturbative approa...

Juan Zhang, Boheng Zhao, Yang Li et al. · 0 citations

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