36 citations · 166 across the 11 of their papers we have counts for
3 papers · 2 filters
Quantum-Noise-Driven Generative Diffusion Models
Marco Parigi, Stefano Martina, Filippo Caruso
Generative models realized with machine learning techniques are powerful tools to infer complex and unknown data distributions from a finite number of training samples in order to…
Machine-learning based noise characterization and correction on neutral atoms NISQ devices
Ettore Canonici, Stefano Martina, Riccardo Mengoni +2
Neutral atoms devices represent a promising technology that uses optical tweezers to geometrically arrange atoms and modulated laser pulses to control the quantum states. A neutral…
Deep learning enhanced noise spectroscopy of a spin qubit environment
Stefano Martina, Santiago Hernández-Gómez, Stefano Gherardini +2
The undesired interaction of a quantum system with its environment generally leads to a coherence decay of superposition states in time. A precise knowledge of the spectral content…