J-PLUS: Morphological star/galaxy classification by PDF analysis

¹ Centro de Estudios de Física del Cosmos de Aragón, Plaza San Juan 1, 44001 Teruel, Spain
e-mail: clsj@cefca.es
² APC, AstroParticule et Cosmologie, Université Paris Diderot, CNRS/IN2P3, CEA/lrfu, Observatoire de Paris, Sorbonne Paris Cité, 10 rue Alice Domon et Léonie Duquet, 75205 Paris Cedex 13, France
³ Departamento de Astronomia, Instituto de Física, Universidade Federal do Rio Grande do Sul, Porto Alegre, R.S, Brazil
⁴ Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, 05508-090 São Paulo, Brazil
⁵ Observatório Nacional/MCTIC, Rua Gen. José Cristino 77, 20921-400, Rio de Janeiro, Brazil
⁶ Department of Astronomy, University of Michigan, Ann Arbor, MI 48109-1107, USA
⁷ PITT PACC, Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA 15260, USA
⁸ Department of Physics and JINA Center for the Evolution of the Elements, University of Notre Dame, Notre Dame, IN 46556, USA

Received: 17 December 2017
Accepted: 3 May 2018

Abstract

Aims. Our goal is to morphologically classify the sources identified in the images of the J-PLUS early data release (EDR) as compact (stars) or extended (galaxies) using a dedicated Bayesian classifier.

Methods. J-PLUS sources exhibit two distinct populations in the r-band magnitude versus concentration plane, corresponding to compact and extended sources. We modelled the two-population distribution with a skewed Gaussian for compact objects and a log-normal function for the extended objects. The derived model and the number density prior based on J-PLUS EDR data were used to estimate the Bayesian probability that a source is a star or a galaxy. This procedure was applied pointing-by-pointing to account for varying observing conditions and sky positions. Finally, we combined the morphological information from the g, r, and i broad bands in order to improve the classification of low signal-to-noise sources.

Results. The derived probabilities are used to compute the pointing-by-pointing number counts of stars and galaxies. The former increases as we approach the Milky Way disk, and the latter are similar across the probed area. The comparison with SDSS in the common regions is satisfactory up to r ~ 21, with consistent numbers of stars and galaxies, and consistent distributions in concentration and (g−i) colour spaces.

Conclusions. We implement a morphological star/galaxy classifier based on probability distribution function analysis, providing meaningful probabilities for J-PLUS sources to one magnitude deeper (r ~ 21) than a classical Boolean classification. These probabilities are suited for the statistical study of 150 thousand stars and 101 thousand galaxies with 15 < r ≤ 21 present in the 31.7 deg² of the J-PLUS EDR. In a future version of the classifier, we will include J-PLUS colour information from 12 photometric bands.