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Merging Machine Learning with Quantum Photonics: Rapid classification of quantum sources

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Abstract

Single quantum emitters offer useful functionalities for quantum optics, but measurements of their properties are time-consuming. We demonstrate that machine learning dramatically reduces data collection time (1s), increasing the accuracy of second-order autocorrelation measurements (>90%).

© 2020 The Author(s)

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More Like This
Machine Learning Assisted Quantum Photonics

Zhaxylyk Kudyshev, Simeon Bogdanov, Theodor Isacsson, Alexander V. Kildishev, Alexandra Boltasseva, and Vladimir M. Shalaev
QM6B.3 Quantum 2.0 (QUANTUM) 2020

Machine learning assisted quantum super-resolution microscopy

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JTh4C.5 CLEO: Applications and Technology (CLEO_AT) 2021

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Jianhong Shi, Yan Zhu, Xiaoyan Wu, and Guihua Zeng
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