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Galaxy Zoo: quantitative visual morphological classifications for 48 000 galaxies from CANDELS

Research output: Contribution to journalJournal articlepeer-review

  • Chris Lintott
  • Kyle W. Willett
  • Karen L. Masters
  • Jeyhan S. Kartaltepe
  • Boris Häußler
  • Sugata Kaviraj
  • Coleman Krawczyk
  • S. J. Kruk
  • Daniel H. Mcintosh
  • R. J. Smethurst
  • Robert C. Nichol
  • Claudia Scarlata
  • Kevin Schawinski
  • Christopher J. Conselice
  • Omar Almaini
  • Henry C. Ferguson
  • Lucy Fortson
  • William Hartley
  • Dale Kocevski
  • Anton M. Koekemoer
  • Alice Mortlock
  • Jeffrey A. Newman
  • Steven P. Bamford
  • N. A. Grogin
  • Ray A. Lucas
  • Nimish P. Hathi
  • Elizabeth Mcgrath
  • Michael Peth
  • Janine Pforr
  • Zachary Rizer
  • Stijn Wuyts
  • Guillermo Barro
  • Eric F. Bell
  • Marco Castellano
  • Tomas Dahlen
  • Avishai Dekel
  • Jamie Ownsworth
  • Sandra M. Faber
  • Steven L. Finkelstein
  • Adriano Fontana
  • Audrey Galametz
  • Ruth Grützbauch
  • David Koo
  • Jennifer Lotz
  • Bahram Mobasher
  • Mark Mozena
  • Mara Salvato
  • Tommy Wiklind
<mark>Journal publication date</mark>1/02/2017
<mark>Journal</mark>Monthly Notices of the Royal Astronomical Society
Issue number4
Number of pages28
Pages (from-to)4420-4447
Publication StatusPublished
<mark>Original language</mark>English


We present quantified visual morphologies of approximately 48 000 galaxies observed in three Hubble Space Telescope legacy fields by the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) and classified by participants in the Galaxy Zoo project. 90 per cent of galaxies have z ≤ 3 and are observed in rest-frame optical wavelengths by CANDELS. Each galaxy received an average of 40 independent classifications, 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 discs at 1 ≤ z ≤ 3, which may represent a dynamically warmer progenitor population to the settled disc galaxies seen at later epochs.