J/ApJ/813/28ivo://CDS.VizieR/J/ApJ/813/28doi:10.26093/cds/vizier.18130028CDSFarrell S.A.Murphy T.Lo K.K.2017-01-23T22:00:00Z2016-03-14T14:49:55ZCDS support team

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

cds-question@unistra.frx-ray-sourcesIn the current era of large surveys and massive data sets, autoclassification of astrophysical sources using intelligent algorithms is becoming increasingly important. In this paper we present the catalog of variable sources in the Third XMM-Newton Serendipitous Source catalog (3XMM) autoclassified using the Random Forest machine learning algorithm (RF). We used a sample of manually classified variable sources from the second data release of the XMM-Newton catalogs (2XMMi-DR2) to train the classifier, obtaining an accuracy of ~92%. We also evaluated the effectiveness of identifying spurious detections using a sample of spurious sources, achieving an accuracy of ~95%. Manual investigation of a random sample of classified sources confirmed these accuracy levels and showed that the Random Forest machine learning algorithm is highly effective at automatically classifying 3XMM sources. Here we present the catalog of classified 3XMM variable sources. We also present three previously unidentified unusual sources that were flagged as outlier sources by the algorithm: a new candidate supergiant fast X-ray transient, a 400s X-ray pulsar, and an eclipsing 5hr binary system coincident with a known Cepheid.2015ApJ...813...28Fhttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJ/813/28CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toB/xmm : XMM-Newton Observation Log (XMM-Newton Science Operation Center, 2012)IX/46 : XMM-Newton Serendipitous Source Catalogue 3XMM-DR5 (XMM-SSC, 2016)IX/44 : XMM-Newton Serendipitous Source Catalogue 3XMM-DR4 (XMM-SSC, 2013)J/MNRAS/414/2602 : Automated classification of HIP variables (Dubath+, 2011)J/A+A/493/339 : XMM-Newton serendipitous Survey. V. (Watson+, 2009)https://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/ApJ/813/28https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/ApJ/813/28http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/ApJ/813/28https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/ApJ/813/28https://vizier.iucaa.in/viz-bin/votable?-source=J/ApJ/813/28http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/ApJ/813/28GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/ApJ/813/28/table4 (3XMM variable source classifications using the Random Forest machine learning algorithm (RF))https://vizier.cds.unistra.fr/viz-bin/conesearch/J/ApJ/813/28/table4?https://vizier.iucaa.in/viz-bin/conesearch/J/ApJ/813/28/table4?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/ApJ/813/28/table4?GETtext/xml+votable180.050000true0.2312544.6194440.0055555555555555565/4424 8274 6/87 351 474 496 597 941 1024 1031 1048 1082 1111 1114 1115 1159 1169 1196 1198 1199 1263 1287 1405 1468 1483 1504 1505 1539 1679 1694 1698 1701 1704 1716 1796 1841 1847 2110 2154 2155 2221 2229 2248 2342 2388 2390 2409 2432 2564 2622 2623 2666 2686 2709 2735 2752 2774 2789 2866 2922 3030 3035 3058 3063 3066 3136 3193 3231 3256 3257 3308 3446 3507 3632 3712 4078 4146 4206 4221 4369 4439 4444 4447 4488 4536 4672 4691 4748 4786 4955 4965 5091 5112 5241 5287 5367 5420 5423 5434 5469 5545 5670 5699 5727 6021 6031 6036 6040 6112 6150 6241 6340 6383 6470 6534 6539 6561 6617 6694 6827 6883 6922 6977 7026 7037 7157 7178 7210 7266 7298 7309 7323 7570 7576 7606 7612 7618 7642 7743 7752 7763 7768 7784 7799 7917 8124 8173 8220 8264 8268 8299 8442 8552 8673 8843 8922 9018 9099 9168 9343 9353 9354 9401 9442 9468 9476 9512 9660 9714 9747 9831 9842 9894 9997 10166 10169 10183 10190 10191 10211 10255 10371 10379 10401 10422 10442 10605 10659 10761 10799 10888 10912 10927 11000 11027 11063 11112 11127 11191 11249 11253 11290 11354 11375 11434 11490 11573 11605 11615 11664 11690 11694 11829 11856 11936 12025 12123 12127 12240 12317 12463 12537 12553 12796 12804 12975 12983 13026 13209 13250 13256 13301 13411 13465 13511 13529 13564 13641 13707 13799 13875 13881 14000 14053 14056 14225 14251 14261 14285 14303 14305 14307 14321 14322 14341 14379 14447 14454 14458 14606 14610 14622 14628 14629 14630 14641 14653 14692 14693 14696 14697 14700 14702 14753 14755 14772 14773 14816 14960 15056 15090 15112 15363 15365 15368 15369 15370 15385 15430 15480 15481 15592 15593 15633 15679 15689 15934 16042 16056 16197 16220 16221 16280 16282 16333 16429 16490 16589 16609 16701 17075 17188 17264 17357 17450 17457 17460 17472 17676 17679 17683 17686 17687 17690 17691 17692 17695 17700 17712 18062 18084 18099 18127 18209 18365 18398 18496 18604 18607 18683 18699 18790 18968 19033 19036 19283 19383 19485 19730 19797 19842 19883 19897 20021 20034 20071 20168 20489 20520 20537 20574 20624 20706 20761 20764 20766 20875 21169 21196 21245 21247 21403 21428 21430 21436 21438 21439 21534 21641 21643 21918 22082 22095 22154 22300 22552 22605 22632 22659 22707 22722 22804 22805 22830 22848 22854 22855 22861 22862 22873 22895 22955 23028 23190 23191 23451 23476 23527 23538 23548 23549 23636 23637 23639 23704 23717 23719 23728 23952 23995 24086 24120 24151 24185 24279 24329 24829 24949 25079 25182 25327 25344 25518 25610 25658 25690 25744 25815 25906 25907 25944 25973 26002 26037 26148 26174 26186 26189 26221 26223 26270 26289 26310 26365 26563 26802 26902 26990 27026 27122 27126 27243 27256 27258 27308 27428 27462 27477 27580 27714 27742 27765 27862 27907 27913 27934 27938 27948 27982 28142 28221 28251 28346 28430 28452 28477 28492 28517 28535 28631 28654 28675 28678 28690 28703 28705 28711 28722 28728 28741 28742 28746 28751 28762 28770 28772 28779 28787 28793 28798 28804 28805 28809 28813 28816 28817 28819 28822 28823 28825 28826 28827 28830 28831 28844 28846 28849 28853 28868 28875 28877 28884 28894 28913 28918 28919 28921 28922 28925 28950 28955 29032 29070 29072 29081 29084 29090 29091 29097 29101 29113 29114 29116 29162 29184 29192 29193 29211 29221 29234 29240 29242 29253 29259 29306 29346 29384 29398 29416 29461 29463 29509 29511 29513 29522 29523 29532 29534 29535 29795 29831 29870 29906 30029 30215 30222 30244 30256 30258 30259 30262 30299 30306 30313 30317 30318 30328 30363 30417 30439 30505 30507 30543 30580 30593 30595 30607 30616 30618 30622 30716 30719 30753 31259 31313 31393 31537 31628 31774 31804 31880 31898 31932 32112 32500 32765 32994 33004 33030 33047 33073 33094 33095 33100 33102 33106 33107 33110 33116 33121 33193 33295 33297 33298 33304 33306 33317 33328 33578 33619 33649 33668 33713 33716 33795 33801 33804 33866 33930 33937 33986 34023 34034 34038 34054 34064 34065 34070 34088 34104 34191 34273 34294 34297 34412 34443 34531 34533 34534 34535 34845 34881 34910 35045 35064 35150 35240 35243 35256 35390 35393 35446 35512 35536 35542 35611 35623 35629 35755 35770 35935 36012 36082 36234 36237 36487 36697 36700 36712 36733 36764 36774 36775 36792 36829 36956 36957 37012 37022 37071 37128 37187 37196 37247 37252 37303 37306 37342 37368 37388 37473 37474 37475 37512 37592 37593 37611 37789 37790 37863 37866 37869 37871 37874 37875 37880 37881 37901 37904 37906 37910 37924 37925 37926 37930 37936 37937 38016 38018 38028 38081 38139 38210 38268 38322 38442 38492 38528 38653 38655 38702 38704 38926 38946 38965 39118 39140 39181 39183 39192 39209 39216 39234 39235 39238 39241 39247 39266 39272 39326 39327 39335 39376 39396 39397 39520 39545 39773 39775 39785 39825 39853 39888 39916 39937 40018 40271 40432 40433 40513 40613 40642 40786 40809 40941 40952 40988 41001 41134 41270 41271 41279 41311 41384 41399 41444 41526 41530 41584 41586 41591 41618 41630 41654 41655 41658 41660 41670 41676 41679 41682 41685 41696 41697 41698 41701 41713 41758 41760 41761 41763 41812 41814 41823 41876 42120 42121 42157 42159 42170 42171 42173 42196 42206 42207 42210 42211 42213 42214 42215 42216 42220 42224 42226 42228 42229 42290 42314 42315 42347 42371 42387 42391 42392 42394 42409 42416 42417 42429 42433 42434 42435 42441 42444 42451 42453 42460 42464 42468 42483 42496 42502 42533 42547 42652 42664 42666 42678 42684 42700 42704 42841 42889 42910 42969 42970 42981 42989 42990 42991 43012 43024 43042 43065 43105 43107 43227 43321 43342 43391 43420 43544 43572 43626 43632 43785 43787 43803 43806 43825 43836 43874 43881 43908 43947 44008 44169 44316 44356 44381 44551 44554 44861 45336 45350 45649 45752 45754 45779 45791 45815 45821 45855 45906 45912 45914 45942 45948 45959 45984 46162 46172 46181 46196 46207 46281 46398 46399 46568 46738 46882 46987 47047 47120 47136 47154 47169 47188 47235 47244 47414 47589 47648 47649 47805 47824 47828 48105 48423 48481 48500 48966 49042 49048 49053https://cdsarc.cds.unistra.fr/viz-bin/moc/J/ApJ/813/28?format=asciiX-raydefaultJ/ApJ/813/28/table43XMM variable source classifications using the Random Forest machine learning algorithm (RF)P(XRB)RF classifier probability; XRB source classstat.fit.goodnessfloatrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordint3XMM3XMM IAU designation (JHHMMSS.s+DDMMSS)meta.id;meta.maincharP(AGN)RF classifier probability; AGN source classstat.fit.goodnessfloatP(CV)RF classifier probability; CV source classstat.fit.goodnessfloatP(GRB)RF classifier probability; GRB source classstat.fit.goodnessfloatP(STAR)RF classifier probability; STAR source classstat.fit.goodnessfloatP(ULX)RF classifier probability; ULX source classstat.fit.goodnessfloatP(Max)Max RF classifier probability over all source classesstat.fit.goodnessfloatP(Spur)RF classifier probability that the source is spuriousstat.fit.goodnessfloatClSource class assigned by RF classifier (1)src.classcharOut[-1/2891] Outlier measure of the source (2)stat.likelihoodintMargin[-0.6/1] Classification margin of the source (3)stat.fit.goodnessfloat_RAPositions from 3XMM names (right ascension part)degpos.eq.ra;meta.main_DEPositions from 3XMM names (declination part)degpos.eq.dec;meta.main