J/MNRAS/428/220ivo://CDS.VizieR/J/MNRAS/428/220doi:10.26093/cds/vizier.74280220CDSHassan T.Mirabal N.Contreras J.L.Oya I.2024-07-20T20:13:18Z2014-02-06T09:48:43ZCDS support team

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

cds-question@unistra.frgamma-ray-astronomyactive-galactic-nucleiThe Fermi Gamma-ray Space Telescope (Fermi) is producing the most detailed inventory of the gamma-ray sky to date. Despite tremendous achievements approximately 25 per cent of all Fermi extragalactic sources in the Second Fermi Large Area Telescope Catalogue (2FGL) are listed as active galactic nuclei (AGN) of uncertain type. Typically, these are suspected blazar candidates without a conclusive optical spectrum or lacking spectroscopic observations. Here, we explore the use of machine-learning algorithms - random forests and support vector machines - to predict specific AGN subclass based on observed gamma-ray spectral properties. After training and testing on identified/associated AGN from the 2FGL we find that 235 out of 269 AGN of uncertain type have properties compatible with gamma-ray BL Lacertae and flat-spectrum radio quasars with accuracy rates of 85 per cent. Additionally, direct comparison of our results with class predictions made after following the infrared colour-colour space of Massaro et al. shows that the agreement rate is over four-fifths for 54 overlapping sources, providing independent cross-validation. These results can help tailor follow-up spectroscopic programmes and inform future pointed surveys with ground-based Cherenkov telescopes.2013MNRAS.428..220Hhttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/MNRAS/428/220CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toJ/ApJ/743/171 : The 2LAC catalog (Ackermann+, 2011)J/ApJS/199/31 : Fermi LAT second source catalog (2FGL) (Nolan+, 2012)J/MNRAS/424/L64 : AGN/pulsar distinction for 2FGL sources (Mirabal+, 2012)https://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/MNRAS/428/220https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/MNRAS/428/220http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/MNRAS/428/220https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/MNRAS/428/220https://vizier.iucaa.in/viz-bin/votable?-source=J/MNRAS/428/220http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/MNRAS/428/220GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/MNRAS/428/220/2fgl_class (Predictions of the classification of 2FGL objects)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/MNRAS/428/220/2fgl_class?https://vizier.iucaa.in/viz-bin/conesearch/J/MNRAS/428/220/2fgl_class?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/MNRAS/428/220/2fgl_class?GETtext/xml+votable180.050000true0.439-41.9960.0055555555555555566/172 189 289 428 720 731 813 851 968 1094 1342 1462 1538 1609 1915 2006 2028 2042 2099-2100 2331 2439 2754 2808 2879 3272 3492 3523 3616 3629 3667 3754 3784 3843 4080 4088 4480 4762 5010 5352 5448 6062 6292 6306 6498 6787 6829 6910 7131 7405 7518 7758 7767 7907 7936 7951 8004 8056 8091 8100 8173 8302 8474 8717 9175 9417 9647 9821 9855 10096 10390 10427 11290 11457 12164 12179 12207 12251 12277 12385 12410 12444 12490 12782 12902 13083 13733 13743 14608 14641 14646 14725 14745 14854 14906 14943 14976 15003 15272 15305 15373 15410 15783 15996 16086-16087 16358 16480 16534 16665 16696 16736 16816 17154 17366 17819 17842 17994 18190 18343 18366 19037 19202 19421 19525 19589 19616 19724 20021 20230 20481 20606 20836 20935 21010 21142 21164 21438 21471 21593 21626 21754 21758 21806 21898 22083 22186 22683 22849 23105 23338 23364 23513 23718 23882 23932 24444 24635 24798 24819 24836 24853 24885 24910 24980 25106 25234 25387 25468 25544 25647 25781 25820 25857 26363 26553 26848 26892 26897 27061 27138 27248 27327 27651 28290 28736 28836 28943 28947 28971 29018 29300 29336 29717 29771 29782 29803 29816 29828 29844 29991 30086 30195-30196 30241 30518 30565 30573 30743 30781 30808 30827 30836 30968 30995 31011 31093 31111 31199 31221 31262 31575 31688 31720 31778 31822 31856 31860 31976 32034 32068 32174 32185 32249 32288 32539 32581 32628 32739 32904 33030 33046 33059 33173 33198 33238 33356 33382 33464 33467 33506 33528 33611 33746 33818 33865 33898 33929 33970 34038 34085 34107 34128 34163 34375 34437 34569 34593 34656 34779 34871 34911 34956 34968 35058 35063 35074 35078 35146 35187 35227 35333 35498 35535 35826 36133 36144 36394 36615 36688 36716 36719 36770 36886 36910 36957 36973 37040 37127 37197 37246 37354 37479 37487 37519 37568 37688 37779 37829 37994 38184 38369 38488 38610 38633 38759 38873 38911 38918 38931 39092 39111 39140 39210 39466 39544 39570 39671 39752 39963 39969 39974 39998 40096 40143 40194 40205 40214 40329 40352 40392 40422 40474 40533 40633 40811 40905 41047 41058 41073 41088 41110 41298 41345 41374 41524 41619 41725 41938 41942 41988 42005 42188 42256 42261 42432 42493 42570 42779 42976 42979 42981 42989 42993 43066 43085 43112 43116 43186 43225 43280 43319 43412 43435 43531 43556 43596-43597 43643 43660 43824 43848 43862 43879 43888 43891 43985 43996 44011 44153 44241 44253 44284 44302 44313 44540 44582 44585 44592 44654 44777 44791 45011 45122 45189 45199 45242 45284 45293 45316 45397 45446 45482 45490 45586 45618 45736 45774 45820 45836 45914 46035 46280 46285 46337 46361 46370 46394 46445 46501 46534 46564 46568-46569 46613 46721 46872 47107 47154 47277 47398 47442 47461 47606 47630 47675 47894 47939 47963 48019 48528 48575 48685 48743 48773 48829 48840 48844 48868 48914 48957 48962https://cdsarc.cds.unistra.fr/viz-bin/moc/J/MNRAS/428/220?format=asciiGamma-raydefaultJ/MNRAS/428/220/2fgl_classPredictions of the classification of 2FGL objectsrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintstSimbad column added by the CDSmeta.notechar2FGL2FGL name, JHHMM.m+DDMMameta.id;meta.maincharP(bzb)RFProbabibility of bzb type from Random Forest (RF) methodstat.fit.goodnessfloatP(bzb)SVMProbabibility of bzb type from Support Vector Machines (SVMs) methodstat.fit.goodnessfloatType[bzq] Predicted type (1)src.classcharSimbadSimbad column added by the CDSmeta.ref.urlchar_RAPositions from 2FGL catalog, Nolan et al., 2012, Cat. J/ApJS/199/31 (right ascension part)degpos.eq.ra;meta.main_DEPositions from 2FGL catalog, Nolan et al., 2012, Cat. J/ApJS/199/31 (declination part)degpos.eq.dec;meta.main