Revisiting the Hubble sequence in the SDSS DR7 spectroscopic sample: a publicly available Bayesian automated classification^⋆

¹ GEPI, Paris-Meudon Observatory, 5 Place Jules Janssen, 92190 Meudon, France
e-mail: marc.huertas@obspm.fr
² Université Paris Diderot, 75205 Paris Cedex 13, France
³ Instituto de Astrofísica de Canarias, C/ Vía Láctea s/n, 38200 La Laguna, Spain
⁴ Department of Physics & Astronomy, University of Pennsylvania, 209 S. 33rd St., Philadelphia, PA 19104, USA

Received: 10 September 2010
Accepted: 14 October 2010

Abstract

We present an automated morphological classification in 4 types (E, S0, Sab, Scd) of  ~700   000 galaxies from the SDSS DR7 spectroscopic sample based on support vector machines. The main new property of the classification is that we associate a probability to each galaxy of being in the four morphological classes instead of assigning a single class. The classification is therefore better adapted to nature where we expect a continuous transition between different morphological types. The algorithm is trained with a visual classification and then compared to several independent visual classifications including the Galaxy Zoo first-release catalog. We find a very good correlation between the automated classification and classical visual ones. The compiled catalog is intended for use in different applications and is therefore freely available through a dedicated webpage^⋆ and soon from the CasJobs database.