J/ApJS/250/23ivo://CDS.VizieR/J/ApJS/250/23doi:10.26093/cds/vizier.22500023CDSLeahy D.A.Chen Y.2021-09-10T14:35:25Z2021-03-01T12:42:57ZCDS support team

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

cds-question@unistra.frgalaxiesx-ray-sourcesultraviolet-photometryextinctionglobular-star-clustersx-ray-binary-starsAn ultraviolet (UV) survey of M31 has been carried out during 2017-19 with the Ultra-Violet Imaging Telescope (UVIT) instrument on board the AstroSat Observatory. Here we match the M31 UVIT source catalog with the Chandra source catalog. We find 67 UVIT/Chandra sources detected in a varying number of UV and X-ray bands. The UV and X-ray photometry is analyzed using power-law and blackbody models. The X-ray types include 15 low-mass X-ray binaries (LMXBs) and five active galactic nuclei. Crossmatches with catalogs of stars, clusters, and other source types yield the following: 20 of the UVIT/Chandra sources match with M31 globular clusters, and nine with foreground stars. Three more globular clusters and two more foreground stars are consistent with the UVIT source positions although outside the Chandra match radius of 1". The UV emission of the UVIT/Chandra sources associated with globular clusters is consistent with emission from blue horizontal branch stars rather than from the X-ray source. The LMXBs in globular clusters are among the most luminous globular clusters in M31. Comparison with stellar evolutionary tracks shows that the UVIT/Chandra sources with high UV blackbody temperatures are consistent with massive (10-30M_{sun}_) stars in M31.2020ApJS..250...23Lhttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJS/250/23CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toB/chandra : The Chandra Archive Log (CXC, 1999-2014)I/345 : Gaia DR2 (Gaia Collaboration, 2018)I/347 : Distances to 1.33 billion stars in Gaia DR2 (Bailer-Jones+, 2018)J/ApJ/663/320 : IR-through-UV extinction curve (Fitzpatrick+, 2007)J/A+A/534/A55 : Deep XMM-Newton Survey of M31 (Stiele+, 2011)J/ApJ/802/127 : PHAT stellar cluster survey. II. AP catalog (Johnson+, 2015)J/other/RAA/15.1438 : LAMOST new QSOs in M31 and M33 vicinity (Huo+, 2015)J/ApJ/824/42 : Star clusters in M31. VII. GCs velocities (Caldwell+, 2016)J/ApJ/829/116 : H-band spectroscopy of 25 bright M31 GCs (Sakari+, 2016)J/MNRAS/461/3443 : M31 deepest Chandra catalog of point sources (Vulic+, 2016)J/A+A/620/A28 : XMM northern disc of M31 sources (Sasaki+, 2018)J/ApJS/239/13 : Chandra PHAT X-ray catalog of the M31 disk (Williams+, 2018)J/ApJS/247/47 : Ultraviolet survey of M31 with UVIT on AstroSat (Leahy+, 2020)https://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/ApJS/250/23https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/ApJS/250/23http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/ApJS/250/23https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/ApJS/250/23https://vizier.iucaa.in/viz-bin/votable?-source=J/ApJS/250/23http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/ApJS/250/23GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/ApJS/250/23/table1 (AstroSat/UVIT sources matched with Chandra sources and power law indices)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/ApJS/250/23/table1?https://vizier.iucaa.in/viz-bin/conesearch/J/ApJS/250/23/table1?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/ApJS/250/23/table1?GETtext/xml+votable180.050000true10.93587541.402750.0055555555555555566/2622 2623 2666 2705 2708 27097.013462727736068e-19 1.5339351055263043e-18https://cdsarc.cds.unistra.fr/viz-bin/moc/J/ApJS/250/23?format=asciiX-rayUVdefaultJ/ApJS/250/23/table1AstroSat/UVIT sources matched with Chandra sources and power law indicesrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintSeq[1/67] Source running numbermeta.idintprimaryCXOUCXOU name (HHMMSS.ss+DDMMSS.s; J2000; <CXOU JHHMMSS.s+DDMMSS> in Simbad)meta.id;meta.maincharRAdeg[9.59/11.58] Right Ascension (J2000)degpos.eq.raDEdeg[40.21/41.72] Declination (J2000)degpos.eq.decF148Wmag[19.3/24.3]? Astrosat/UVIT F148W filter AB magnitudemagphot.mag;em.UV.100-200nmfloatnullablee_F148Wmag[0.05/0.4]? 1{sigma} uncertainty in F148Wmagmagstat.errorfloatnullablen_F148Wmag[e] Flag on F148Wmag (5)meta.notecharF169Mmag[21.1/22.2]? Astrosat/UVIT F169M filter AB magnitudemagphot.mag;em.UV.100-200nmfloatnullablee_F169Mmag[0.09/0.2]? The 1{sigma} uncertainty in F169Mmagmagstat.errorfloatnullableF172Mmag[18.8/22.7]? Astrosat/UVIT F172M filter AB magnitudemagphot.mag;em.UV.100-200nmfloatnullablee_F172Mmag[0.07/0.4]? The 1{sigma} uncertainty in F172Mmagmagstat.errorfloatnullableN219Mmag[16.6/22.5]? Astrosat/UVIT N219M filter AB magnitudemagphot.mag;em.UV.200-300nmfloatnullablee_N219Mmag[0.04/0.3]? The 1{sigma} uncertainty in N219Mmagmagstat.error;phot.magfloatnullablen_N219Mmag[e] Flag on N219Mmag (5)meta.notecharN279Nmag[15.18/22]? Astrosat/UVIT N279N filter AB magnitudemagphot.mag;em.UV.200-300nmfloatnullablee_N279Nmag[0.03/0.4]? The 1{sigma} uncertainty in N279Nmagmagstat.error;phot.magfloatnullablen_N279Nmag[e] Flag on N279Nmag (5)meta.notecharFilterFilters with match separation between 1-2" (1)meta.code;instr.filtercharXInd[-1.5/5.4]? X-ray spectral index (2)spect.indexfloatnullableE_XInd[0.01/6.7]? Upper 90% uncertainty in XIndstat.error;stat.maxfloatnullablee_XInd[0.01/2.7]? Lower 90% uncertainty in XIndstat.errorfloatnullableU-XInd[0.7/2.6]? UV-to-X-ray spectral index (3)spect.indexfloatnullableE_U-XInd[0.01/0.6]? Upper uncertainty in U-XIndstat.error;stat.maxfloatnullablee_U-XInd[0.01/0.2]? Lower uncertainty in U-XIndstat.errorfloatnullableClassX-ray class (4)meta.code.classcharOptOptical counterpart (5)meta.code.classcharFitDisplay the Blackbody (BB) and power-law (PL) fits to UVIT photometry (link to Table 2)meta.ref.urlcharL20Display data from Leahy+, 2020, J/ApJS/247/47, within 3"meta.ref.urlchar_RARight ascension (derived from CXOU) for Eq=J2000degpos.eq.ra;meta.main_DEDeclination (derived from CXOU) for Eq=J2000degpos.eq.dec;meta.mainJ/ApJS/250/23/table2Blackbody (BB) and power-law (PL) fits to UVIT photometryBBChi2[0/95] Chi-square of BB fitstat.fit.param;meta.modelledfloatrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintSeq[2/60] Source numbermeta.idintfgIdentified as foreground star (1)meta.codecharCXOUCXOU name (HHMMSS.ss+DDMMSS.s; J2000)meta.id;meta.maincharFilterUVIT filters with a detected magnitude (2)meta.code;instr.filtercharBBAv[0/1.83] Foreground extinction from BB fit (3)magphys.absorptionfloatE_BBAv[0.01/0.2]? 90% upper error in BBAvmagstat.error;stat.maxfloatnullablee_BBAv[0.02/0.2]? 90% lower error in BBAvmagstat.errorfloatnullableBBRad[0.0069/466] Radius from BB fit (4)solRadphys.size.radiusdoubleE_BBRad[0.0001/31] 90% upper error in BBRadsolRadstat.error;stat.maxdoublee_BBRad[8e-5/28] 90% lower error in BBRadsolRadstat.errordoubleBBTeff[5.4/26.3] Effective temperature from BB fit1000Kphys.temperature.effectivefloatE_BBTeff[0.03/1.5] 90% upper error in BBTeff1000Kstat.error;stat.maxfloate_BBTeff[0.03/1.3] 90% lower error in BBTeff1000Kstat.errorfloatBBrChi2[0/10]? Reduced {chi}^2^ of BB fit (5)stat.fit.param;meta.modelledfloatnullablePLAv[0/1.31] Foreground extinction from PL fit (3)magphys.absorptionfloatE_PLAv[0.01/0.2]? 90% upper error in PLAvmagstat.error;stat.maxfloatnullablee_PLAv[0.01/0.2]? 90% lower error in PLAvmagstat.errorfloatnullablePLNorm[0.38/76.6] Norm from PL fit1e-28mW.m**-2.Hz**-1stat.fit.paramfloatE_PLNorm[0.1/6] 90% upper error in PLNorm1e-28mW.m**-2.Hz**-1stat.error;stat.maxfloate_PLNorm[0.08/5.5] 90% lower error in PLNorm1e-28mW.m**-2.Hz**-1stat.errorfloatPLInd[0.2/9.1] Spectral index from PL fitspect.indexfloatE_PLInd[0.2/1.3] 90% upper error in PLIndstat.error;stat.maxfloate_PLInd[0.2/1.3] 90% lower error in PLIndstat.errorfloatPLChi2[0/340] Chi-square from PL fitmeta.notefloatPLrChi2[0.02/111]? Reduced chi-square from PL fit (5)meta.notefloatnullableBBbestIdentify BB as the best-fit modelmeta.codecharPLbestIdentify PL as the best-fit modelmeta.codechar