Automated morphological classification of Sloan Digital Sky Survey red sequence galaxies

  1. Get@NRC: Automated morphological classification of Sloan Digital Sky Survey red sequence galaxies (Opens in a new window)
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Journal titleMonthly Notices of the Royal Astronomical Society
Pages727747; # of pages: 21
Subjectgalaxies: bulges; galaxies: elliptical and lenticular, cD; galaxies: evolution; galaxies: structure
AbstractIn the last decade, the advent of enormous galaxy surveys has motivated the development of automated morphological classification schemes to deal with large data volumes. Existing automated schemes can successfully distinguish between early- and late-type galaxies and identify merger candidates, but are inadequate for studying detailed morphologies of red sequence galaxies. To fill this need, we present a new automated classification scheme that focuses on making finer distinctions between early types roughly corresponding to Hubble types E, S0 and Sa. We visually classify a sample of 984 non-star-forming Sloan Digital Sky Survey galaxies with apparent sizes > 14 arcsec. We then develop an automated method to closely reproduce the visual classifications, which both provides a check on the visual results and makes it possible to extend morphological analysis to much larger samples. We visually classify the galaxies into three bulge classes (BC) by the shape of the light profile in the outer regions: discs have sharp edges and bulges do not, while some galaxies are intermediate. We separately identify galaxies with features: spiral arms, bars, clumps, rings and dust. We find general agreement between BC and the bulge fraction B/T measured by the galaxy modelling package gim2d, but many visual discs have B/T > 0.5. Three additional automated parameters - smoothness, axial ratio and concentration - can identify many of these high-B/T discs to yield automated classifications that agree similar to 70 per cent with the visual classifications (> 90 per cent within one BC). Tests versus disc inclination indicate that both methods identify most face-on discs, but visually, features are lost in edge-on discs. 80 per cent of face-on visual discs have features while few visual bulges do, strongly validating the visual classifications. Given the good agreement between the visual and automated methods, we believe that the automated method can be applied to a much larger sample with confidence. Both methods are used to study the bulge versus disc frequency as a function of four measures of galaxy 'size': luminosity, stellar mass, velocity dispersion (Sigma) and radius (R). All size indicators show a fall in disc fraction and a rise in bulge fraction among larger galaxies.
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AffiliationNational Research Council Canada; NRC Herzberg Institute of Astrophysics
Peer reviewedYes
NPARC number19793787
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Record identifier60617431-14c1-49de-97d8-e917c0259e16
Record created2012-04-10
Record modified2016-05-09
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