3 citations · 3 across the 3 of their papers we have counts for
3 papers
Learning the Kohn-Sham map with neural operators for quasi-linear scaling density functional theory
Danish Khan, Maurice D. Hanisch, Nikolai Argatoff +3
Kohn--Sham density functional theory (DFT) underpins electronic-structure simulations, but repeated orbital diagonalizations lead to cubic scaling, restricting quantum calculations…
OrbitAll: A Unified Quantum Mechanical Representation Deep Learning Framework for All Molecular Systems
Beom Seok Kang, Vignesh C. Bhethanabotla, Amin Tavakoli +6
We introduce OrbitAll, a geometry- and physics-informed deep learning framework that encodes any molecular system with arbitrary charges, spins, and environmental effects using ele…
Soft information decoding with superconducting qubits
Maurice D. Hanisch, Bence Hetényi, James R. Wootton
Quantum error correction promises a viable path to fault-tolerant computations, enabling exponential error suppression when the device's error rates remain below the protocol's thr…