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Real-bogus classification for the Zwicky Transient Facility using deep learning

Duev, Dmitry A. and Mahabal, Ashish and Masci, Frank J. and Graham, Matthew J. and Rusholme, Ben and Walters, Richard and Karmarkar, Ishani and Frederick, Sara and Kasliwal, Mansi M. and Rebbapragada, Umaa and Ward, Charlotte (2019) Real-bogus classification for the Zwicky Transient Facility using deep learning. Monthly Notices of the Royal Astronomical Society, 489 (3). pp. 3582-3590. ISSN 0035-8711. doi:10.1093/mnras/stz2357.

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Efficient automated detection of flux-transient, re-occurring flux-variable, and moving objects is increasingly important for large-scale astronomical surveys. We present BRAAI, a convolutional-neural-network, deep-learning real/bogus classifier designed to separate genuine astrophysical events and objects from false positive, or bogus, detections in the data of the Zwicky Transient Facility (ZTF), a new robotic time-domain survey currently in operation at the Palomar Observatory in California, USA. BRAAI demonstrates a state-of-the-art performance as quantified by its low false negative and false positive rates. We describe the open-source software tools used internally at Caltech to archive and access ZTF’s alerts and light curves (KOWALSKI ), and to label the data (ZWICKYVERSE). We also report the initial results of the classifier deployment on the Edge Tensor Processing Units that show comparable performance in terms of accuracy, but in a much more (cost-) efficient manner, which has significant implications for current and future surveys.

Item Type:Article
Related URLs:
URLURL TypeDescription Paper
Duev, Dmitry A.0000-0001-5060-8733
Mahabal, Ashish0000-0003-2242-0244
Masci, Frank J.0000-0002-8532-9395
Graham, Matthew J.0000-0002-3168-0139
Rusholme, Ben0000-0001-7648-4142
Walters, Richard0000-0002-1835-6078
Karmarkar, Ishani0000-0001-8192-208X
Frederick, Sara0000-0001-9676-730X
Kasliwal, Mansi M.0000-0002-5619-4938
Rebbapragada, Umaa0000-0002-2560-3495
Additional Information:© 2019 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model ( Accepted 2019 August 21. Received 2019 July 25; in original form 2019 June 28. Published: 26 August 2019. DAD and MJG acknowledge support from the Heising–Simons Foundation under Grant No. 12540303. AM and MJG acknowledge support from the NSF (1640818, AST-1815034), and IUSSTF (JC-001/2017). MMK acknowledges support by the GROWTH project funded by the NSF under Grant No. 1545949. Based on observations obtained with the Samuel Oschin Telescope 48-inch Telescope at the Palomar Observatory as part of the ZTF project. Major funding has been provided by the U.S. National Science Foundation under Grant No. AST-1440341 and by the ZTF partner institutions: the California Institute of Technology, the Oskar Klein Centre, the Weizmann Institute of Science, the University of Maryland, the University of Washington, Deutsches Elektronen-Synchrotron, the University of Wisconsin-Milwaukee, and the TANGO Program of the University System of Taiwan. Part of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. The authors are grateful to Eran Ofek for useful discussions.
Group:Infrared Processing and Analysis Center (IPAC), Zwicky Transient Facility, Astronomy Department
Funding AgencyGrant Number
Heising-Simons Foundation12540303
Indo-US Science and Technology ForumJC-001/2017
ZTF partner institutionsUNSPECIFIED
Subject Keywords:methods: data analysis – surveys
Issue or Number:3
Record Number:CaltechAUTHORS:20190802-110143722
Persistent URL:
Official Citation:Dmitry A Duev, Ashish Mahabal, Frank J Masci, Matthew J Graham, Ben Rusholme, Richard Walters, Ishani Karmarkar, Sara Frederick, Mansi M Kasliwal, Umaa Rebbapragada, Charlotte Ward, Real-bogus classification for the Zwicky Transient Facility using deep learning, Monthly Notices of the Royal Astronomical Society, Volume 489, Issue 3, November 2019, Pages 3582–3590,
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:97617
Deposited By: Joy Painter
Deposited On:02 Aug 2019 18:27
Last Modified:16 Nov 2021 17:33

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