3 papers
quant-ph2026
Cautious optimism for deep parameterized quantum circuits
Marie Kempkes, Elies Gil-Fuster, Carlos Bravo-Prieto +5
A central challenge in quantum machine learning is understanding the scaling behavior of parameterized quantum circuits (PQCs). In particular, it remains unclear how their performa…
quant-ph2025
Reinforcement learning of quantum circuit architectures for molecular potential energy curves
Maureen Krumtünger, Alissa Wilms, Paul K. Faehrmann +4
Quantum chemistry and optimization are two of the most prominent applications of quantum computers. Variational quantum algorithms have been proposed for solving problems in these…
quant-ph2025
Quantum reinforcement learning of classical rare dynamics: Enhancement by intrinsic Fourier features
Alissa Wilms, Laura Ohff, Andrea Skolik +3
Rare events are essential for understanding the behavior of non-equilibrium and industrial systems. It is of ongoing interest to develop methods for effectively searching for rare…