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        Galaxy Zoo: Quantitative Visual Morphological Classifications for 48,000 galaxies from CANDELS

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        Author
        Simmons, B. D.
        Lintott, Chris
        Willett, Kyle W.
        Masters, Karen L.
        Kartaltepe, Jeyhan S.
        Häußler, Boris
        Kaviraj, Sugata
        Krawczyk, Coleman
        Kruk, S. J.
        McIntosh, Daniel H.
        Smethurst, R. J.
        Nichol, Robert C.
        Scarlata, Claudia
        Schawinski, Kevin
        Conselice, Christopher J.
        Almaini, Omar
        Ferguson, Henry C.
        Fortson, Lucy
        Hartley, William
        Kocevski, Dale
        Koekemoer, Anton M.
        Mortlock, Alice
        Newman, Jeffrey A.
        Bamford, Steven P.
        Grogin, N. A.
        Lucas, Ray A.
        Hathi, Nimish P.
        McGrath, Elizabeth
        Peth, Michael
        Pforr, Janine
        Rizer, Zachary
        Wuyts, Stijn
        Barro, Guillermo
        Bell, Eric F.
        Castellano, Marco
        Dahlen, Tomas
        Ownsworth, Avishai Dekel Jamie
        Faber, Sandra M.
        Finkelstein, Steven L.
        Fontana, Adriano
        Galametz, Audrey
        Grützbauch, Ruth
        Koo, David
        Lotz, Jennifer
        Mobasher, Bahram
        Mozena, Mark
        Salvato, Mara
        Wiklind, Tommy
        Attention
        2299/19396
        Abstract
        We present quantified visual morphologies of approximately 48,000 galaxies observed in three Hubble Space Telescope legacy fields by the Cosmic And Near-infrared Deep Extragalactic Legacy Survey (CANDELS) and classified by participants in the Galaxy Zoo project. 90% of galaxies have z 6 3 and are observed in rest-frame optical wavelengths by CANDELS. Each galaxy received an average of 40 independent classifi- cations, which we combine into detailed morphological information on galaxy features such as clumpiness, bar instabilities, spiral structure, and merger and tidal signatures. We apply a consensus-based classifier weighting method that preserves classifier independence while effectively down-weighting significantly outlying classifications. After analysing the effect of varying image depth on reported classifications, we also provide depth-corrected classifications which both preserve the information in the deepest observations and also enable the use of classifications at comparable depths across the full survey. Comparing the Galaxy Zoo classifications to previous classifications of the same galaxies shows very good agreement; for some applications the high number of independent classifications provided by Galaxy Zoo provides an advantage in selecting galaxies with a particular morphological profile, while in others the combination of Galaxy Zoo with other classifications is a more promising approach than using any one method alone. We combine the Galaxy Zoo classifications of “smooth” galaxies with parametric morphologies to select a sample of featureless disks at 1 6 z 6 3, which may represent a dynamically warmer progenitor population to the settled disk galaxies seen at later epochs.
        Publication date
        2017-02-01
        Published in
        Monthly Notices of the Royal Astronomical Society
        Published version
        https://doi.org/10.1093/mnras/stw2587
        Other links
        http://hdl.handle.net/2299/19396
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