@inproceedings{da9f692d27be403d8ea32d6d29e540c5,
title = "Bayesian machine learning of frequency-bin CNOT",
abstract = "We analyze the first experimental two-photon frequency-bin gate: a coincidence-basis CNOT. A novel characterization approach based on Bayesian machine learning is developed to estimate the gate performance with measurements in the logical basis alone.",
author = "Lu, \{Hsuan Hao\} and Lukens, \{Joseph M.\} and Williams, \{Brian P.\} and Poolad Imany and Peters, \{Nicholas A.\} and Weiner, \{Andrew M.\} and Pavel Lougovski",
note = "Publisher Copyright: {\textcopyright} 2019 The Author(s).; CLEO: QELS\_Fundamental Science, CLEO\_QELS 2019 ; Conference date: 05-05-2019 Through 10-05-2019",
year = "2019",
doi = "10.1364/CLEO-QELS.2019.FF1F.3",
language = "English",
isbn = "9781943580576",
series = "Optics InfoBase Conference Papers",
publisher = "Optica Publishing Group (formerly OSA)",
booktitle = "CLEO",
}