An Automated Galaxy Classification System

Mathematics – Logic

Scientific paper

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Scientific paper

We describe an automated morphological classification system that is useful for the study of faint objects detected on CCD frames. The fundamental parameter in our system is the central concentration of light. This parameter traces both the disk-to-bulge ratio and the effective radius of the galactic bulge component. We show that our classification system is less sensitive to seeing degradation than the Hubble system. The fundamental parameter of our classification system is of physical interest as a tracer of stellar population. In some respects our system might be regarded as an automated version of Morgan's Yerkes system. Our classification scheme is illustrated by using wide-field CCD data of the core of the galaxy cluster Abell 957. Many of the galaxies in the core of this cluster are poorly described by the Hubble system, but are well-described by a classification system based on central concentration of light. We have also artificially redshifted our wide-field CCD image to mimic the appearance of an intermediate redshift cluster seen under excellent seeing conditions, and show that our procedure makes it possible to morphologically classify faint galaxies out to z ~ 0.5 using ground-based data. Monte Carlo simulations are used to quantify the statistical uncertainties inherent in our morphological classifications.

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