Machine learning assisted quantum photonics

Zhaxylyk Kudyshev, Simeon Bogdanov, Theodor Isacsson, Alexander V. Kildishev, Alexandra Boltasseva, Vladimir M. Shalaev

Research output: Contribution to journalConference articlepeer-review


The characterization of single quantum emitters is a time-consuming process. We have demonstrated that machine learning methods can dramatically reduce data collection time(<1s), and increase measurement accuracy of second-order fluorescence autocorrelation(>90%).

Original languageEnglish (US)
Article numberQM6B.3
JournalOptics InfoBase Conference Papers
StatePublished - 2020
EventOSA Quantum 2.0 Conference, QUANTUM 2020 - Virtual, Online, United States
Duration: Sep 14 2020Sep 17 2020

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Mechanics of Materials


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