Issue |
A&A
Volume 602, June 2017
|
|
---|---|---|
Article Number | A86 | |
Number of page(s) | 12 | |
Section | Catalogs and data | |
DOI | https://doi.org/10.1051/0004-6361/201629552 | |
Published online | 20 June 2017 |
Research and characterisation of blazar candidates among the Fermi/LAT 3FGL catalogue using multivariate classifications⋆
1 LUTH, Observatoire de Paris, PSL Research University, CNRS, Université Paris Diderot, 5 place Jules Janssen, 92190 Meudon, France
e-mail: julien.lefaucheur@obspm.fr
2 APC, AstroParticule et Cosmologie, Université Paris Diderot, CNRS/IN2P3, CEA/Irfu, Observatoire de Paris, Sorbonne Paris Cité, 10 rue Alice Domon et Léonie Duquet, 75205 Paris Cedex 13, France
e-mail: santiago.pita@apc.in2p3.fr
Received: 19 August 2016
Accepted: 15 February 2017
Context. In the recently published 3FGL catalogue, the Fermi/LAT collaboration reports the detection of γ-ray emission from 3034 sources obtained after four years of observations. The nature of 1010 of those sources is unknown, whereas 2023 have well-identified counterparts in other wavelengths. Most of the associated sources are labelled as blazars (1717/2023), but the BL Lac or FSRQ nature of 573 of these blazars is still undetermined.
Aims. The aim of this study was two-fold. First, to significantly increase the number of blazar candidates from a search among the large number of Fermi/LAT 3FGL unassociated sources (case A). Second, to determine the BL Lac or FSRQ nature of the blazar candidates, including those determined as such in this work and the blazar candidates of uncertain type (BCU) that are already present in the 3FGL catalogue (case B).
Methods. For this purpose, multivariate classifiers – boosted decision trees and multilayer perceptron neural networks – were trained using samples of labelled sources with no caution flag from the 3FGL catalogue and carefully chosen discriminant parameters. The decisions of the classifiers were combined in order to obtain a high level of source identification along with well controlled numbers of expected false associations. Specifically for case A, dedicated classifications were generated for high (| b | >10◦) and low (| b | ≤10◦) galactic latitude sources; in addition, the application of classifiers to samples of sources with caution flag was considered separately, and specific performance metrics were estimated.
Results. We obtained a sample of 595 blazar candidates (high and low galactic latitude) among the unassociated sources of the 3FGL catalogue. We also obtained a sample of 509 BL Lacs and 295 FSRQs from the blazar candidates cited above and the BCUs of the 3FGL catalogue. The number of expected false associations is given for different samples of candidates. It is, in particular, notably low (~9/425) for the sample of high-latitude blazar candidates from case A.
Key words: gamma rays: galaxies / galaxies: active / BL Lacertae objects: general / methods: statistical / catalogs
Full Tables 5 and 7 are only available at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/602/A86
© ESO, 2017
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