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The Sloan Digital Sky Survey extended point spread functions
- Source :
- Digital.CSIC. Repositorio Institucional del CSIC, instname, Monthly Notices of the Royal Astronomical Society
- Publication Year :
- 2020
- Publisher :
- Oxford University Press, 2020.
-
Abstract
- A robust and extended characterization of the point spread function (PSF) is crucial to extract the photometric information produced by deep imaging surveys. Here, we present the extended PSFs of the Sloan Digital Sky Survey (SDSS), one of the most productive astronomical surveys of all time. By stacking similar to 1000 images of individual stars with different brightness, we obtain the bidimensional SDSS PSFs extending over 8 arcmin in radius for all the SDSS filters (u, g, r, i, z). This new characterization of the SDSS PSFs is near a factor of 10 larger in extension than previous PSFs characterizations of the same survey. We found asymmetries in the shape of the PSFs caused by the drift scanning observing mode. The flux of the PSFs is larger along the drift scanning direction. Finally, we illustrate with an example how the PSF models can be used to remove the scattered light field produced by the brightest stars in the central region of the Coma cluster field. This particular example shows the huge importance of PSFs in the study of the low-surface brightness Universe, especially with the upcoming of ultradeep surveys, such as the Large Synoptic Survey Telescope (LSST). Following a reproducible science philosophy, we make all the PSF models and the scripts used to do the analysis of this paper publicly available (snapshot v0.4-0-gd966ad0). ©2019 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society<br />We thank the referee for a constructive report that helped to improve the presentation of the manuscript. This research has been supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under grants AYA2016-77237-C3-1-P and AYA2016-76219-P. We also acknowledge support from the Fundacion BBVA under its 2017 programme of assistance to scientific research groups, for the project 'Using machine-learning techniques to drag galaxies from the noise in deep imaging'. This work was partly done using the reproducible template project (Akhlaghi et al. in preparation). The reproducible template was also supported by European Union's Horizon 2020 (H2020) research and innovation programme via the RDA EU 4.0 project (ref. GA no. 777388). We thank Mohammad Akhlaghi for all his time spent in explaining how to make the core part of this project reproducible. We thank Roelof de Jong for kindly providing us the PSF profiles obtained in his work. We thank Alejandro Borlaff, Nushkia Chamba, and Simon Diaz-Garcia for their comments. This work was partly done using GNU Astronomy Utilities (Gnuastro, ascl.net/1801.009) version 0.10. Work on Gnuastro has been funded by the Japanese Ministry of Education, Culture, Sports, Science, and Technology (MEXT) scholarship and its Grant-in-Aid for Scientific Research (21244012, 24253003), the European Research Council (ERC) advanced grant 339659-MUSICOS, European Unions Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement No 721463 to the SUNDIAL ITN. Funding for the Sloan Digital Sky Survey IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS web site is www.sdss.org.SDSS-IV is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration including the Brazilian Participation Group, the Carnegie Institution for Science, Carnegie Mellon University, the Chilean Participation Group, the French Participation Group, Harvard-Smithsonian Center for Astrophysics, Instituto de Astrofisica de Canarias, The Johns Hopkins University, Kavli Institute for the Physics and Mathematics of the Universe (IPMU) / University of Tokyo, the Korean Participation Group, Lawrence Berkeley National Laboratory, Leibniz Institut fur Astrophysik Potsdam (AIP), Max-Planck-Institut fur Astronomie (MPIA Heidelberg), Max-Planck-Institut fur Astrophysik (MPA Garching), Max-Planck-Institut fur Extraterrestrische Physik (MPE), National Astronomical Observatories of China, New Mexico State University, New York University, University of Notre Dame, Observatario Nacional/MCTI, The Ohio State University, Pennsylvania State University, Shanghai Astronomical Observatory, United Kingdom Participation Group, Universidad Nacional Autonoma de Mexico, University of Arizona, University of Colorado Boulder, University of Oxford, University of Portsmouth, University of Utah, University of Virginia, University of Washington, University of Wisconsin, Vanderbilt University, and Yale University.
- Subjects :
- 010504 meteorology & atmospheric sciences
haloes [Galaxies]
FOS: Physical sciences
Library science
Techniques: image processing
Astrophysics::Cosmology and Extragalactic Astrophysics
01 natural sciences
Point spread
Methods: data analysis
0103 physical sciences
media_common.cataloged_instance
image processing [Techniques]
Instrumentation: detectors
European union
Galaxies: haloes
data analysis [Methods]
Instrumentation and Methods for Astrophysics (astro-ph.IM)
010303 astronomy & astrophysics
detectors [Instrumentation]
Astrophysics::Galaxy Astrophysics
0105 earth and related environmental sciences
Mathematics
Web site
media_common
European research
photometric [Techniques]
Astrophysics::Instrumentation and Methods for Astrophysics
Astronomy and Astrophysics
Astrophysics - Astrophysics of Galaxies
Scholarship
Space and Planetary Science
Astrophysics of Galaxies (astro-ph.GA)
Christian ministry
National laboratory
Astrophysics - Instrumentation and Methods for Astrophysics
Sundial
Techniques: photometric
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Digital.CSIC. Repositorio Institucional del CSIC, instname, Monthly Notices of the Royal Astronomical Society
- Accession number :
- edsair.doi.dedup.....1cb21db23eff37ab9b3c454fb9629b73