Author

Sofiène Jerbi

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#machine learning Preprint Sep 2026

Towards Surrogate Based Dequantization of Quantum Reinforcement Learning

In recent years, the utility of parameterized quantum circuits as function approximators has been widely studied. In the context of reinforcement learning, this approach has led to variational quantum algorithms such as quantum Q-learning. While these methods show promising empirical results, and can provide provable a...

Pablo Rodriguez-Grasa, Sofiène Jerbi, Mikel Sanz et al. · 0 citations

Jul 2026

Provable learning separation for predicting time-evolution of quantum many-body systems

The results demonstrate a rigorous learning separation for a natural ML task based on Hamiltonian evolution, while building connections between quantum learning theory, quantum simulation, and QML.

Rahul Bandyopadhyay, Riccardo Molteni, Jens Eisert et al. · arXiv.org · 1 citation