2 papers
cond-mat.mtrl-sci2026
QUBO-Compatible Active Learning for Inverse Design of High-Entropy Alloys
Giorgio Silvi, Kirsten Bark, Rolando Reiner +5
Machine-learned forward models can rapidly predict alloy properties, but their use for inverse design remains challenging when the search should also retain compatibility with quad…
quant-ph2025
A Joint Quantum Computing, Neural Network and Embedding Theory Approach for the Derivation of the Universal Functional
Martin J. Uttendorfer, Daniel Barragan-Yani, Matthias Sperl +1
We introduce a novel approach that exploits the intersection of quantum computing, machine learning and reduced density matrix functional theory to leverage the potential of quantu…