Mahabal, Ashish and Rebbapragada, U. D. and Walters, Richard and Masci, Frank J. and Blagorodnova, N. and van Roestel, Jan and Biswas, Rahul and Burdge, Kevin B. and Chang, Chan-Kao and Duev, Dmitry A. and Golkhou, V. Zach and Miller, Adam A. and Nordin, Jakob and Ward, Charlotte and Adams, Scott M. and Bellm, Eric C. and Branton, Doug and Bue, Brian D. and Cannella, C. and Connolly, Andrew and Dekany, Richard and Feindt, Ulrich and Hung, Tiara and Fortson, Lucy F. and Frederick, Sara and Fremling, C. and Gezari, Suvi and Graham, Matthew J. and Groom, Steven and Kasliwal, Mansi M. and Kulkarni, S. R. and Kupfer, Thomas and Lin, Hsing Wen and Lintott, Chris J. and Lunnan, R. and Parejko, John and Prince, Thomas A. and Riddle, Reed and Rusholme, B. and Saunders, Nicholas and Sedaghat, Nima and Shupe, David L. and Singer, Leo P. and Soumagnac, Maayane T. and Szkody, Paula and Tachibana, Yutaro and Tirumala, Kushal and van Velzen, Sjoert and Wright, Darryl (2019) Machine Learning for the Zwicky Transient Facility. Publications of the Astronomical Society of the Pacific, 131 (997). Art. No. 038002. ISSN 0004-6280. doi:10.1088/1538-3873/aaf3fa. https://resolver.caltech.edu/CaltechAUTHORS:20190131-104830427
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Abstract
The Zwicky Transient Facility is a large optical survey in multiple filters producing hundreds of thousands of transient alerts per night. We describe here various machine learning (ML) implementations and plans to make the maximal use of the large data set by taking advantage of the temporal nature of the data, and further combining it with other data sets. We start with the initial steps of separating bogus candidates from real ones, separating stars and galaxies, and go on to the classification of real objects into various classes. Besides the usual methods (e.g., based on features extracted from light curves) we also describe early plans for alternate methods including the use of domain adaptation, and deep learning. In a similar fashion we describe efforts to detect fast moving asteroids. We also describe the use of the Zooniverse platform for helping with classifications through the creation of training samples, and active learning. Finally we mention the synergistic aspects of ZTF and LSST from the ML perspective.
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| Additional Information: | © 2019. The Astronomical Society of the Pacific. Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Received 2018 September 4; accepted 2018 November 26; published 2019 January 31. 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. 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. Facilities: PO:1.2m - , PO:1.5m. - | |||||||||
| Group: | Infrared Processing and Analysis Center (IPAC), Zwicky Transient Facility, Astronomy Department | |||||||||
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| Issue or Number: | 997 | |||||||||
| DOI: | 10.1088/1538-3873/aaf3fa | |||||||||
| Record Number: | CaltechAUTHORS:20190131-104830427 | |||||||||
| Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20190131-104830427 | |||||||||
| Official Citation: | Ashish Mahabal et al 2019 PASP 131 038002 | |||||||||
| Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | |||||||||
| ID Code: | 92541 | |||||||||
| Collection: | CaltechAUTHORS | |||||||||
| Deposited By: | George Porter | |||||||||
| Deposited On: | 31 Jan 2019 23:11 | |||||||||
| Last Modified: | 16 Nov 2021 03:51 |
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