Quantum Information and Measurement (QIM)

Machine Learning For Experimental Single Shot Phase Estimation

Emanuele Polino, Alessandro Lumino, Adil Syed Rab, Giorgio Milani, Nicolò Spagnolo, Fabio Sciarrino, Nathan Wiebe

Published Jan 1, 2019• 0 citations

Abstract

We implement adaptive machine learning techniques to enhance the sensitivity in the estimation of a relative phase shift between two paths of an interferometer. The estimation is realized through single photons measured shot by shot.

DOI: 10.1364/qim.2019.t5a.41

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