3 papers
cond-mat.mtrl-sci2026
Data-driven multi-objective optimization for alloy recycling using factorization machines and quantum annealing
Thomas Plehn, Katrin Bugelnig, Silvana Tumminello +2
Quantum annealing has the potential to provide practical quantum advantage for complex optimization tasks. Here, we present a systematic assessment of an integrated factorization-m…
quant-ph2026
Efficient Operator Selection and Warm-Start Strategy for Excitations in Variational Quantum Eigensolvers
Max Haas, Thierry N. Kaldenbach, Thomas Hammerschmidt +1
We present a novel approach for efficient preparation of electronic ground states, leveraging the optimizer ExcitationSolve [Jäger et al., Comm. Phys. (2025)] and established varia…
cond-mat.mtrl-sci2025
Progress on Data-Driven, Multi-Objective Quantum Optimization
Thomas Plehn, Daniel Barragan-Yani, Eric Breitbarth +2
Here, we present two complementary approaches that advance quadratic unconstrained binary optimization (QUBO) toward practical use in data-driven materials design and other real-va…