3 papers
quant-ph2026
Software Between Quantum and Machine Learning -- And Down to Pulses
Maja Franz, Melvin Strobl, Jonathan Hunz +5
Contemporary quantum computing platforms remain, in essence, programmable physical systems whose control is typically mediated through unitary gate abstractions. While such abstrac…
quant-ph2026
A Transferable Machine Learning Approach to Predict Optimized Orbitals for Electronic Structure Problems
Lucas van der Horst, Maniraman Periyasamy, Abhishek Y. Dubey +3
Variational quantum eigensolver ansätze hold considerable promise for ground-state energy calculations on near-term quantum hardware, yet most promising ansatz designs currently s…
quant-ph2025
Fourier Fingerprints of Ansatzes in Quantum Machine Learning
Melvin Strobl, M. Emre Sahin, Lucas van der Horst +3
Typical schemes to encode classical data in variational quantum machine learning (QML) lead to quantum Fourier models with Fourier basis functions in the num…