Journal
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
Volume 505, Issue 2, Pages 2954-2965Publisher
OXFORD UNIV PRESS
DOI: 10.1093/mnras/stab1502
Keywords
methods: data analysis; techniques: photometric; catalogues; surveys; stars: statistics
Categories
Funding
- National Science Foundation [AST-1440341, PHY-2010970, DGE-0948017, ACI-1548562]
- Office for Science & Technology of the Embassy of France in the United States
- European Research Council (ERC) under the European Union [759194]
- NSF [AST-1816492]
- U.S. Department of Energy Office of Science User Facility [DE-AC02-05CH11231]
- Extreme Science and Engineering Discovery Environment (XSEDE) COMET at SDSU [AST200016]
- Caltech, IPAC
- Weizmann Institute for Science
- Oskar Klein Center at Stockholm University
- University of Maryland
- TANGO Consortium of Taiwan
- University of Wisconsin at Milwaukee
- Lawrence Berkeley National Laboratories
- University of Washington (UW)
- Deutsches Elektronen-Synchrotron
- Humboldt University
- Los Alamos National Laboratories
- European Research Council (ERC) [759194] Funding Source: European Research Council (ERC)
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The current generation of all-sky surveys is rapidly expanding our ability to study variable and transient sources with different sensitivities, cadences, and fields of view. The data from the Zwicky Transient Facility provides an opportunity to find variables on a wide range of time-scales. Developing computational metrics and algorithms for future data releases will be essential for continued research in this field.
The current generation of all-sky surveys is rapidly expanding our ability to study variable and transient sources. These surveys, with a variety of sensitivities, cadences, and fields of view, probe many ranges of time-scale and magnitude. Data from the Zwicky Transient Facility (ZTF) yields an opportunity to find variables on time-scales from minutes to months. In this paper, we present the codebase, ztfperiodic, and the computational metrics employed for the catalogue based on ZTF's Second Data Release. We describe the publicly available, graphical-process-unit optimized period-finding algorithms employed, and highlight the benefit of existing and future graphical-process-unit clusters. We show how generating metrics as input to catalogues of this scale is possible for future ZTF data releases. Further work will be needed for future data from the Vera C. Rubin Observatory's Legacy Survey of Space and Time.
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