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cond-mat.mes-hall2026
Deep Learning GW Quasiparticle Hamiltonians for Many-Body Excited-State Electronic Structure at Scale
Xiaoxun Gong, Zechen Tang, Woochang Kim +4
Accurate quasiparticle electronic structures are the foundation for understanding excited-state properties of materials and explaining optoelectronic, quantum, and transport phenom…
physics.comp-ph2026
AI-accelerated metallized -bonding screening for superconductor discovery
Zechen Tang, Wen-Han Dong, Baochun Wu +11
The computational discovery of phonon-mediated superconductors is hindered by the prohibitive cost of density functional perturbation theory (DFPT). Here, guided by the metallized…
cond-mat.mtrl-sci2026
DeepH-pack: A general-purpose neural network package for deep-learning electronic structure calculations
Yang Li, Yanzhen Wang, Boheng Zhao +15
In computational physics and materials science, first-principles methods, particularly density functional theory, have become central tools for electronic structure prediction and…