van Roestel, Jan and Duev, Dmitry A. and Mahabal, Ashish A. and Coughlin, Michael W. and Mróz, Przemek and Burdge, Kevin and Drake, Andrew and Graham, Matthew J. and Hillenbrand, Lynne and Bellm, Eric C. and Kupfer, Thomas and Delacroix, Alexandre and Fremling, C. and Golkhou, V. Zach and Hale, David and Laher, Russ R. and Masci, Frank J. and Riddle, Reed and Rosnet, Philippe and Rusholme, Ben and Smith, Roger and Soumagnac, Maayane T. and Walters, Richard and Prince, Thomas A. and Kulkarni, S. R. (2021) The ZTF Source Classification Project. I. Methods and Infrastructure. Astronomical Journal, 161 (6). Art. No. 267. ISSN 1538-3881. doi:10.3847/1538-3881/abe853. https://resolver.caltech.edu/CaltechAUTHORS:20210505-070438281
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Abstract
The Zwicky Transient Facility (ZTF) has been observing the entire northern sky since the start of 2018 down to a magnitude of 20.5 (5σ for 30 s exposure) in the g, r, and i filters. Over the course of two years, ZTF has obtained light curves of more than a billion sources, each with 50–1000 epochs per light curve in g and r, and fewer in i. To be able to use the information contained in the light curves of variable sources for new scientific discoveries, an efficient and flexible framework is needed to classify them. In this paper, we introduce the methods and infrastructure that will be used to classify all ZTF light curves. Our approach aims to be flexible and modular and allows the use of a dynamical classification scheme and labels, continuously evolving training sets, and the use of different machine-learning classifier types and architectures. With this setup, we are able to continuously update and improve the classification of ZTF light curves as new data become available, training samples are updated, and new classes need to be incorporated.
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| Additional Information: | © 2021. The American Astronomical Society. Received 2020 August 5; revised 2021 February 18; accepted 2021 February 19; published 2021 May 14. We thank the referee for useful and constructive feedback on the manuscript. Based on observations obtained with the Samuel Oschin Telescope 48 inch and the 60 inch Telescope at the Palomar Observatory as part of the Zwicky Transient Facility project. ZTF is supported by the National Science Foundation under grant No. AST-1440341 and a collaboration including Caltech, IPAC, the Weizmann Institute for Science, the Oskar Klein Center at Stockholm University, the University of Maryland, the University of Washington (UW), Deutsches Elektronen-Synchrotron and Humboldt University, Los Alamos National Laboratories, the TANGO Consortium of Taiwan, the University of Wisconsin at Milwaukee, and Lawrence Berkeley National Laboratories. Operations are conducted by Caltech Optical Observatories, IPAC, and UW. D.A.D. acknowledges support from the Heising-Simons Foundation under grant No. 12540303. A.A.M. acknowledges support from the NSF grant OAC-1640818. M.W.C. acknowledges support from the National Science Foundation with grant No. PHY-2010970. The authors acknowledge support from Google Cloud. The authors acknowledge the Minnesota Supercomputing Institute 23 (MSI) at the University of Minnesota for providing resources that contributed to the research results reported within this paper under project "Identification of Variable Objects in the Zwicky Transient Facility." This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility operated under contract No. DE-AC02-05CH11231 under project "Toward a complete catalog of variable sources to support efficient searches for compact binary mergers and their products." This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562. This work used the Extreme Science and Engineering Discovery Environment (XSEDE) COMET at SDSU through allocation AST200016. Facility: ZTF. - Software: astropy (Astropy Collaboration et al. 2018), keras (Chollet & Others 2015), keras-tuner (O'Malley et al. 2019), kowalski (Duev et al. 2019), matplotlib (Hunter 2007), numpy (van der Walt et al. 2011), pandas (pandas development team 2020), tensorflow (Abadi et al. 2015), xgboost (Chen & Guestrin 2016). | ||||||||||||||||||||||||||||||||||||||||||||
| Group: | Astronomy Department, Zwicky Transient Facility, Infrared Processing and Analysis Center (IPAC) | ||||||||||||||||||||||||||||||||||||||||||||
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| Subject Keywords: | Surveys; Intrinsic variable stars; Variable stars; Catalogs; Celestial objects catalogs | ||||||||||||||||||||||||||||||||||||||||||||
| Issue or Number: | 6 | ||||||||||||||||||||||||||||||||||||||||||||
| Classification Code: | Unified Astronomy Thesaurus concepts: Surveys (1671); Intrinsic variable stars (859); Variable stars (1761); Catalogs (205); Celestial objects catalogs (212) | ||||||||||||||||||||||||||||||||||||||||||||
| DOI: | 10.3847/1538-3881/abe853 | ||||||||||||||||||||||||||||||||||||||||||||
| Record Number: | CaltechAUTHORS:20210505-070438281 | ||||||||||||||||||||||||||||||||||||||||||||
| Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20210505-070438281 | ||||||||||||||||||||||||||||||||||||||||||||
| Official Citation: | Jan van Roestel et al 2021 AJ 161 267 | ||||||||||||||||||||||||||||||||||||||||||||
| Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||||||||||||||||||||||||||||||||||||||||
| ID Code: | 108969 | ||||||||||||||||||||||||||||||||||||||||||||
| Collection: | CaltechAUTHORS | ||||||||||||||||||||||||||||||||||||||||||||
| Deposited By: | Tony Diaz | ||||||||||||||||||||||||||||||||||||||||||||
| Deposited On: | 05 May 2021 18:30 | ||||||||||||||||||||||||||||||||||||||||||||
| Last Modified: | 14 May 2021 21:18 |
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