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cond-mat.mtrl-sci2026
Acceleration of Atomistic NEGF: Algorithms, Parallelization, and Machine Learning
Mathieu Luisier, Nicolas Vetsch, Alexander Maeder +8
The Non-equilibrium Green's function (NEGF) formalism is a particularly powerful method to simulate the quantum transport properties of nanoscale devices such as transistors, photo…
cond-mat.mtrl-sci2025
Learning the Electronic Hamiltonian of Large Atomic Structures
Chen Hao Xia, Manasa Kaniselvan, Alexandros Nikolaos Ziogas +4
Graph neural networks (GNNs) have shown promise in learning the ground-state electronic properties of materials, subverting ab initio density functional theory (DFT) calculations w…