J/ApJS/248/23     4FGL sources with IR/Rad associations     (de Menezes+, 2020)

On the physical association of Fermi-LAT blazars with their low-energy counterparts. de Menezes R., D'Abrusco R., Massaro F., Gasparrini D., Nemmen R. <Astrophys. J. Suppl. Ser., 248, 23 (2020)> =2020ApJS..248...23D 2020ApJS..248...23D
ADC_Keywords: Active gal. nuclei; Gamma rays; Infrared sources; Radio sources; Cross identifications Keywords: Gamma-ray astronomy ; Active galactic nuclei ; Astronomical methods Abstract: Associating γ-ray sources to their low-energy counterparts is one of the major challenges of modern γ-ray astronomy. In the context of the Fourth Fermi Large Area Telescope Source Catalog (4FGL), the associations rely mainly on parameters such as apparent magnitude, integrated flux, and angular separation between the γ-ray source and its low-energy candidate counterpart. In this work, we propose a new use of the likelihood ratio (LR) and a complementary supervised learning technique to associate γ-ray blazars in 4FGL, based only on spectral parameters such as the γ-ray photon index, mid-infrared colors, and radio-loudness. In the LR approach, we crossmatch the Wide-field Infrared Survey Explorer Blazar-Like Radio-Loud Sources catalog with 4FGL and compare the resulting candidate counterparts with the sources listed in the γ-ray blazar locus to compute an association probability (AP) for 1138 counterparts. In the supervised learning approach, we train a random forest algorithm with 869 high-confidence blazar associations and 711 fake associations and then compute an AP for 1311 candidate counterparts. A list with all 4FGL blazar candidates of uncertain type associated by our method is provided to guide future optical spectroscopic follow-up observations. File Summary: -------------------------------------------------------------------------------- FileName Lrecl Records Explanations -------------------------------------------------------------------------------- ReadMe 80 . This file tablea1.dat 59 283 Blazar candidates of an uncertain type (BCUs) associated by the likelihood ratio (LR) method based only on spectral parameters -------------------------------------------------------------------------------- See also: VII/169 : Optical Identifications of IRAS Point Sources (Wang+ 1986,87,91) VII/274 : The Roma BZCAT - 5th edition (Massaro+, 2015) II/328 : AllWISE Data Release (Cutri+ 2013) J/PASP/113/10 : Sub-mJy radio sources complete sample (Masci+, 2001) J/ApJS/188/405 : Fermi-LAT first source catalog (1FGL) (Abdo+, 2010) J/ApJ/743/171 : The 2LAC catalog (Ackermann+, 2011) J/ApJ/748/68 : WISE IR colors of gamma-ray blazars (D'Abrusco+, 2012) J/MNRAS/424/L64 : AGN/pulsar distinction for 2FGL sources (Mirabal+, 2012) J/ApJS/199/31 : Fermi LAT second source catalog (2FGL) (Nolan+, 2012) J/ApJS/206/12 : Blazars with γ-ray counterparts. I. (D'Abrusco+, 2013) J/MNRAS/428/220 : Gamma-ray AGN type determination (Hassan+, 2013) J/ApJS/209/10 : UGSs. V. kernel approach (Massaro+, 2013) J/ApJS/215/14 : WISE γ-ray blazar radio sources (D'Abrusco+, 2014) J/ApJ/782/41 : 231 AGN candidates from the 2FGL catalog (Doert+, 2014) J/ApJS/218/23 : Fermi LAT third source catalog (3FGL) (Acero+, 2015) J/ApJS/217/2 : Refined associations of Fermi/LAT sources (Massaro+, 2015) J/MNRAS/462/3180 : 3FGL Blazar of Unknown Type classification (Chiaro+, 2016) J/ApJ/820/8 : 3FGL sources statistical classif. (Saz Parkinson+, 2016) J/A+A/602/A86 : Blazar cand. among Fermi/LAT 3FGL cat. (Lefaucheur+, 2017) J/MNRAS/470/1291 : Classifying 3FGL with ANN (Salvetti+, 2017) J/ApJS/242/4 : Two new catalogs of blazar candidates (D'Abrusco+, 2019) J/ApJS/247/33 : The Fermi LAT fourth source cat. (4FGL) (Abdollahi+, 2020) J/MNRAS/493/1926 : 4FGL blazar classification neural network (Kovacevic+, 2020) Byte-by-byte Description of file: tablea1.dat -------------------------------------------------------------------------------- Bytes Format Units Label Explanations -------------------------------------------------------------------------------- 1- 4 A4 --- --- [4FGL] 6- 17 A12 --- 4FGL The 4FGL identifier (JHHMM.m+DDMM) 19- 37 A19 --- WISEA The WISE counterpart identifier (JHHMMSS.ss+DDMMSS.s; WIBRaLS sources from D'Abrusco+, 2019, J/ApJS/242/4) 38- 39 A2 --- f_WISEA Flag on WISEA (1) 41- 44 F4.2 --- LR [0.85/1] Association probability by LR method from this work (2) 46- 49 F4.2 --- RF [0.08/1] Association probability by random forest method from this work (see Section 5) 51- 54 F4.2 --- Bay [0/1]? Association probability by Bayesian method used in 4FGL 56- 59 F4.2 --- LR4FGL [0/1] Association probability by LR method used in 4FGL -------------------------------------------------------------------------------- Note (1): Flag as follows: * = confirmed blazar. Optical spectra available in de Menezes+ 2020Ap&SS.365...12D 2020Ap&SS.365...12D (13 occurrences). ** = confirmed blazar, Optical spectra available in Pena-Herazo et al. (2020, in prep -- 4 occurrences). Note (2): The likelihood ratio (LR) method we adopt to estimate the association probability is a modification of the LR method described in Sutherland & Saunders (1992MNRAS.259..413S 1992MNRAS.259..413S) and Ackermann+ (2011, J/ApJ/743/171). See Section 4. -------------------------------------------------------------------------------- History: From electronic version of the journal
(End) Prepared by [AAS], Emmanuelle Perret [CDS] 20-Jul-2020
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