Quantum pattern recognition in photonic circuits
José D. Martín‐Guerrero, Carlos Hernani‐Morales, Rui Wang, E. Solano, F. Albarrán-Arriagada · Repository of Digital Objects for Teaching Research and Culture (University of Valencia) · 2021
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.