activity
20182026
most citedMachine learning-based classification of vector vortex beams

150 citations · 351 across the 15 of their papers we have counts for

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Showing 2020Show all

5 papers · 1 filter

quant-ph2020

Experimental robust self-testing of the state generated by a quantum network

Iris Agresti, Beatrice Polacchi, Davide Poderini +7

Self-testing is a method of quantum state and measurement estimation that does not rely on assumptions about the inner working of the used devices. Its experimental realization has…

quant-ph2020

Robust calibration of multiparameter sensors via machine learning at the single-photon level

Valeria Cimini, Emanuele Polino, Mauro Valeri +7

Calibration of sensors is a fundamental step to validate their operation. This can be a demanding task, as it relies on acquiring a detailed modelling of the device, aggravated by…

quant-ph2020150 cited

Machine learning-based classification of vector vortex beams

Taira Giordani, Alessia Suprano, Emanuele Polino +6

Structured light is attracting significant attention for its diverse applications in both classical and quantum optics. The so-called vector vortex beams display peculiar propertie…

quant-ph2020

Photonic Quantum Metrology

Emanuele Polino, Mauro Valeri, Nicolò Spagnolo +1

Quantum Metrology is one of the most promising application of quantum technologies. The aim of this research field is the estimation of unknown parameters exploiting quantum resour…

quant-ph2020

Experimental adaptive Bayesian estimation of multiple phases with limited data

Mauro Valeri, Emanuele Polino, Davide Poderini +6

Achieving ultimate bounds in estimation processes is the main objective of quantum metrology. In this context, several problems require measurement of multiple parameters by employ…