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Quantum pattern recognition in photonic circuits
Rui Wang, C. Hernani-Morales, J. D. Mart'in-Guerrero, E. Solano, F. Albarrán-Arriagada·July 21, 2021·DOI: 10.1088/2058-9565/ac3460
Computer SciencePhysics
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Abstract
This paper proposes a machine learning method to characterize photonic states via a simple optical circuit and data processing of photon number distributions, such as photonic patterns. The input states consist of two coherent states used as references and a two-mode unknown state to be studied. We successfully trained supervised learning algorithms that can predict the degree of entanglement in the two-mode state as well as perform the full tomography of one photonic mode, obtaining satisfactory values in the considered regression metrics.