Teo, Yong Siah http://orcid.org/0000-0002-1766-6402
Shin, Seongwook
Jeong, Hyunseok
Kim, Yosep
Kim, Yoon-Ho
Struchalin, Gleb I http://orcid.org/0000-0002-8887-3361
Kovlakov, Egor V
Straupe, Stanislav S http://orcid.org/0000-0001-9810-1958
Kulik, Sergei P
Leuchs, Gerd http://orcid.org/0000-0003-1967-2766
Sánchez-Soto, Luis L http://orcid.org/0000-0002-7441-8632
Funding for this research was provided by:
Center of Excellence <<Center of Photonics>> funded by the Ministry of Science and Higher Education of the Russian Federation (075-15-2020-906)
Ministerio de Ciencia e Innovaci{\'o}n (PGC2018-099183-B-I00)
European Union's Horizon 2020 research and innovation program
ITRC support program (IITP-2020-0-01606)
Institute of Information & Communications Technology Planning & Evaluation (2020-0-01606)
Russian Foundation for Basic Research (19-32-80043)
National Research Foundation of Korea (2019M3E4A1080074)
Russian National Technological Initiative via MSU Quantum Technology Centre
Article Title: Benchmarking quantum tomography completeness and fidelity with machine learning
Journal Title: New Journal of Physics
Article Type: paper
Copyright Information: © 2021 The Author(s). Published by IOP Publishing Ltd on behalf of the Institute of Physics and Deutsche Physikalische Gesellschaft
Publication dates
Date Received: 2021-05-27
Date Accepted: 2021-08-20
Online publication date: 2021-10-14