Author

N. Gullo

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#machine learning Preprint Oct 2026

On linearity or non-linearity in machine learning for quantum chaotic dynamics

Accurately simulating chaotic quantum many-body dynamics remains a major computational challenge for classical methods, due to the rapid buildup and spatial spreading of entanglement during the evolution. This raises the question of whether machine learning can provide an effective alternative for predicting quantum dy...

Francesco Perciavalle, Agostino Gallo, F. Plastina et al. · 0 citations

Preprint Sep 2026

Revealing Many-Body Phases at finite temperatures through Quantum Coherence Distribution

We introduce a diagnostic framework based on the full probability distribution of quantum coherence to probe single-particle and many-body phases at finite temperature. We first apply this approach to the localization transition in the non-interacting Aubry-Andr\'e model and then extend the analysis to its interacting...

Antonio Palamara, N. Gullo, A. Sindona et al. · 0 citations