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Testing Noise Correlations by an AI-Assisted Two-Qubit Quantum Sensor
Dario Fasone, Shreyasi Mukherjee, Mauro Paternostro, Elisabetta Paladino, Luigi Giannelli, Giuseppe A. Falci·December 30, 2025
Quantum Physicscond-mat.other
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Abstract
We introduce and validate a machine learning-assisted protocol to classify time and space correlations of classical noise acting on a quantum system, using two interacting qubits as probe. We consider different classes of noise, according to their Markovianity and spatial correlations. Leveraging the sensitivity of a coherent population transfer protocol under three distinct driving conditions, the various noises are discriminated by only measuring the final transfer efficiencies. This approach reaches around 90% accuracy with a minimal experimental overhead.