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Utilizing Astroinformatics to Maximize the Science Return of the Next Generation Virgo Cluster Survey

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Astrostatistics and Data Mining

Part of the book series: Springer Series in Astrostatistics ((SSIA,volume 2))

Abstract

The Next Generation Virgo Cluster Survey is a 104-square-degree survey of the Virgo Cluster, carried out using the MegaPrime camera of the Canada–France–Hawaii Telescope, from semesters 2009A–2012A. The survey will provide coverage of this nearby dense environment in the universe to unprecedented depth, providing profound insights into Galaxy formation and evolution, including definitive measurements of the properties of galaxies in a dense environment in the local universe, such as the luminosity function. The limiting magnitude of the survey is g AB = 25.7 (10σ point source), and the 2σ surface brightness limit is g AB ≈ 29 mag arcsec−2. The data volume of the survey (approximately 50 T of images), while large by contemporary astronomical standards, is not intractable. This renders the survey amenable to the methods of astroinformatics. The enormous dynamic range of objects, from the giant elliptical Galaxy M87 at \(M(B) = -21.6\) to the faintest dwarf ellipticals at M(B)≈−6, combined with photometry in five broad bands (u* griz’) and unprecedented depth revealing many previously unseen structures, creates new challenges in object detection and classification. We present results from ongoing work on the survey, including photometric redshifts, Virgo cluster membership, and the implementation of fast data mining algorithms on the infrastructure of the Canadian Astronomy Data Centre, as part of the Canadian Advanced Network for Astronomical Research.

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Notes

  1. 1.

    https://www.astrosci.ca/NGVS/The_Next_Generation_Virgo_Cluster_Survey.

  2. 2.

    http://www.ivoa.net/cgi-bin/twiki/bin/view/IVOA/IvoaKDDguide.

  3. 3.

    http://www.astro.uvic.ca/~canfar/canfarw.

  4. 4.

    Although the present catalogue was not created utilizing the current version of CANFAR, such a catalogue is easily recreated there.

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Correspondence to Nicholas M. Ball .

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Ball, N.M. (2012). Utilizing Astroinformatics to Maximize the Science Return of the Next Generation Virgo Cluster Survey. In: Sarro, L., Eyer, L., O'Mullane, W., De Ridder, J. (eds) Astrostatistics and Data Mining. Springer Series in Astrostatistics, vol 2. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3323-1_6

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