J/ApJS/248/23ivo://CDS.VizieR/J/ApJS/248/23doi:10.26093/cds/vizier.22480023CDSde Menezes R.D'Abrusco R.Massaro F.Gasparrini D.Nemmen R.2021-11-09T09:30:22Z2020-08-11T11:39:35ZCDS support team

CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France

cds-question@unistra.fractive-galactic-nucleigamma-ray-astronomyinfrared-sourcesradio-sourcesastronomical-object-identificationAssociating {gamma}-ray sources to their low-energy counterparts is one of the major challenges of modern {gamma}-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 {gamma}-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 {gamma}-ray blazars in 4FGL, based only on spectral parameters such as the {gamma}-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 {gamma}-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.2020ApJS..248...23Dhttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJS/248/23CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toVII/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 {gamma}-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 {gamma}-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)https://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/ApJS/248/23https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/ApJS/248/23http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/ApJS/248/23https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/ApJS/248/23https://vizier.iucaa.in/viz-bin/votable?-source=J/ApJS/248/23http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/ApJS/248/23GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/ApJS/248/23/tablea1 (Blazar candidates of an uncertain type (BCUs) associated by the likelihood ratio (LR) method based only on spectral parameters)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/ApJS/248/23/tablea1?https://vizier.iucaa.in/viz-bin/conesearch/J/ApJS/248/23/tablea1?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/ApJS/248/23/tablea1?GETtext/xml+votable180.050000true0.4165-41.94250.0055555555555555566/90 465 543 556 576 961 1032 1116 1342 1611 1626 1680 1740 2042 2255 2434 2439 2492 2643 2654 2788 2817 3237 3472 3528 3844 4079 4091 4137 4723 5314 5720 5821 6754 6774 7766 7823 7859 8004 8052 8091 8717 8792 9016 9302 10090 10171 10704 11045 11083 11216 11246 11586 11675 11899 11978 12067 12093 12225 12251 12289 12443 12588 12783 13081 13230 13321 13534 13692 13938 14369 14646 14745 14983 15300 15821 15910 15917 16086 16666 16800 17275 17601 17675 17868 18431 18484 18561 18631 18902 18927 19499 19976 20067 20136 20246 20607 20736 20873 21330 21345 21626 22116 22239 22281 22386 22452 22952 23096 23901 24134 24272 24326 24444 24623 24818-24819 24885 24927 25611 25619 25804 26169 26363 26892 26900-26901 27047 27185 27605 27798 27844 28583 28947 29322 29580 29707 29730 30091 30566 30590 30743 30857 31199 31886 31986 32068 32314 32559 32662 32729 32788 33048-33049 33128 33158 33345 33378 33406 33419 33501 33580 33818 33929 34187 34547 34569 34592 34647 34931 35033 35146 35263 35274 35376 35401 35484 35498 35502 35681 35901 35969 36120 36196 36204 36237 36251 36361 36391 36607 36614 36877 37022 37438 37472 37519 37564 37667 38186 38579 38762 38797 38937 39065 39092 39132 39146 39464 39599 39654 39717 39786 39963 39974 40024 40092 40235 40351 40392 40474 40636 40698 40786 40842 40905 40997 41047 41130 41179 41325 41982 42261 42803 42904 43412 43556 43572 43662 43696 43707 43793 43888 43996 44050 44052 44121 44449 44484 44653 44702 44713 44734 44901 45146 45214 45284 45330 45358 45406 45640 45725 45816 46200 46608 46613 47062 47152 47277 47288 47497 47533 47630 47675 47720 47865 47912 48154 48274 48366 48407 48671 48778 49043https://cdsarc.cds.unistra.fr/viz-bin/moc/J/ApJS/248/23?format=asciiGamma-rayInfraredRadiodefaultJ/ApJS/248/23/tablea1Blazar candidates of an uncertain type (BCUs) associated by the likelihood ratio (LR) method based only on spectral parametersrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordint4FGLThe 4FGL identifier (JHHMM.m+DDMM)meta.id;meta.maincharWISEAThe WISE counterpart identifier (JHHMMSS.ss+DDMMSS.s; WIBRaLS sources from D'Abrusco+, 2019, J/ApJS/242/4)meta.id.assoccharf_WISEAFlag on WISEA (1)meta.codecharLR[0.85/1] Association probability by LR method from this work (2)stat.fit.goodnessfloatRF[0.08/1] Association probability by random forest method from this work (see Section 5)stat.fit.goodnessfloatBay[0/1]? Association probability by Bayesian method used in 4FGLstat.fit.goodnessfloatnullableLR4FGL[0/1] Association probability by LR method used in 4FGLstat.fit.goodnessfloatSimbadSimbad column added by the CDSmeta.ref.urlchar_RAPositions from the 4FGL catalog (Abdollahi+, 2020, J/ApJS/247/33) (right ascension part)degpos.eq.ra;meta.main_DEPositions from the 4FGL catalog (Abdollahi+, 2020, J/ApJS/247/33) (declination part)degpos.eq.dec;meta.main