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Conferences > QIM > 2019 > F5A > F5A.22

Visual assessment of multiphoton interference

Fulvio Flamini, Nicolò Spagnolo, and Fabio Sciarrino

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Abstract

Machine learning allows to extract meaningful patterns hidden within high-dimensional data. Here we combine two such algorithms to investigate and validate multi-photon quantum interference in Boson Sampling experiments.

© 2019 The Author(s)

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