J/A+A/550/A120ivo://CDS.VizieR/J/A+A/550/A120doi:10.26093/cds/vizier.35500120CDSSarro L.M.Debosscher J.Neiner C.Bello-Garcia A.Gonzalez-Marcos A.,Prendes-Gero B.Ordieres J.Leon G.Aerts C.de Batz B.2025-02-17T20:00:28Z2013-02-05T12:47:22ZCDS support team

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

cds-question@unistra.frvariable-starsphotometryclassificationWe present an improved method for automated stellar variability classification, using fundamental parameters derived from high resolution spectra, with the goal to improve the variability classification obtained using information derived from CoRoT light curves only. Although we focus on Giraffe spectra and CoRoT light curves in this work, the methods are much more widely applicable. In order to improve the variability classification obtained from the photometric time series, only rough estimates of the stellar physical parameters (Teff and logg) are needed because most variability types that overlap in the space of time series parameters, are well separated in the space of physical parameters (e.g. {gamma} Dor/SPB or {delta} Sct/{beta} Cep). In this work, several state-of-the-art machine learning techniques are combined to estimate these fundamental parameters from high resolution Giraffe spectra. Next, these parameters are used in a multi-stage Gaussian-Mixture classifier to perform an improved supervised variability classification of CoRoT light curves. The variability classifier can be used independently of the regression module that estimates the physical parameters, so that non-spectroscopic estimates derived e.g. from photometric colour indices can be used instead. Teff and logg are derived from Giraffe spectra, for 6832 CoRoT targets. The use of those parameters in addition to information extracted from the CoRoT light curves, significantly improves the results of our previous automated stellar variability classification. Several new pulsating stars are identified with high confidence levels, including hot pulsators such as SPB and {beta} Cep, and several {gamma} Dor-{delta} Sct hybrids. From our samples of new {gamma} Dor and {delta} Sct stars, we find strong indications that the instability domains for both types of pulsators are larger than previously thought.2013A&A...550A.120Shttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/A+A/550/A120CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toB/corot : CoRoT observation log Release 10 (CoRoT, 2012)J/MNRAS/358/30 : Automated classification of ASAS variables (Eyer+, 2005)J/A+A/475/1159 : Variable stars supervised classification (Debosscher+, 2008)J/A+A/494/739 : Automatic classification of OGLE variables (Sarro+, 2009)J/A+A/506/519 : CoRoT variables Supervised classification (Debosscher+ 2009)J/AJ/138/466 : NSVS variables automated classification (Hoffman+, 2009)J/MNRAS/414/2602 : Automated classification of HIP variables (Dubath+, 2011)J/A+A/538/A76 : Automatic stellar spectral classification (Navarro+, 2012)J/MNRAS/427/2917 : HIP variables automated classification (Rimoldini+, 2012)https://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/A+A/550/A120https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/A+A/550/A120http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/A+A/550/A120https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/A+A/550/A120https://vizier.iucaa.in/viz-bin/votable?-source=J/A+A/550/A120http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/A+A/550/A120GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/A+A/550/A120/table2 (Catalog of time series and physical parameters for 6834 CoRoT observations (corrected version, 17-Feb-2025))https://vizier.cds.unistra.fr/viz-bin/conesearch/J/A+A/550/A120/table2?https://vizier.iucaa.in/viz-bin/conesearch/J/A+A/550/A120/table2?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/A+A/550/A120/table2?GETtext/xml+votable180.050000true290.61981.551370.0055555555555555565/5510 5519 7614 6/22029 22034-22035 22046 22065 22068 22165 22167 22208 22210 29951 30122 30293 30295 30301 30437 30439 30448 30450-30451 30460 30462 30464 30466 30472-30473https://cdsarc.cds.unistra.fr/viz-bin/moc/J/A+A/550/A120?format=asciidefaultJ/A+A/550/A120/table2Catalog of time series and physical parameters for 6834 CoRoT observations (corrected version, 17-Feb-2025)RAJ2000Right ascension (J2000)degpos.eq.ra;meta.mainindexedDEJ2000Declination (J2000)degpos.eq.dec;meta.mainindexedVmag? V magnitudemagphot.mag;em.opt.VfloatnullableClassVariability type (1)meta.code;src.varcharProb[0/1] Probability of classmeta.code.class;stat.probabilityfloatMDMahalanobis distance to class centerstat.fit.residualfloatnu1First detected frequencyd**-1em.freq;src.vardoublenu2Second detected frequencyd**-1em.freq;src.vardoublea11Amplitude of the first term in the Fourier series of nu1magphys.atmol.termfloata21Amplitude of the first term in the Fourier series of nu2magphys.atmol.termfloatp1[0/1] p-value1 for nu1 in hypothesis teststat.fit.goodnessfloatp2[0/1] p-value2 for nu2 in hypothesis teststat.fit.goodnessfloatTeff1KT model effective temperatureKphys.temperature.effective;meta.modelledintlogglog(g) from KT modellog(cm.s**-2)arith.zpfloatTeff2ELODIE model effective temperatureKphys.temperature.effective;meta.modelledintSimbadSimbad column added by the CDSmeta.ref.urlcharRunRunmeta.notecharrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintCoRoTCoRoT identifier (B/corot)meta.id;meta.mainlongNNumber of estimations for this starmeta.numberint