Alexandros Nikolaos Ziogas

MALOQ: Massively Accelerated Learning of Operators for Quantum Transport

Manasa Kaniselvan, Alexander Maeder, Denghui Lu, Alexandros Nikolaos Ziogas, Mathieu Luisier

Machine-learned (ML) operator models can be trained to predict density functional theory (DFT) Hamiltonian/density matrices at significantly reduced computational cost, thus extending electronic-structure calculations to previously unfeasible scales. Here, we introduce MALOQ (Mas…Read more