J/A+A/697/A39ivo://CDS.VizieR/J/A+A/697/A39doi:10.26093/cds/vizier/bc-ns/ldjCDSKang D.E.Itrich D.Ksoll V.F.Testi L.Klessen R.S.Molinari S.2026-02-10T20:02:48Z2025-05-05T09:38:08ZCDS support team

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

cds-question@unistra.fropen-star-clusterspre-main-sequence-starsspectroscopyeffective-temperaturestellar-spectral-typesstellar-agesWe introduce an updated version of our deep learning tool that predicts effective temperature, surface gravity, extinction, and veiling from the optical spectra of young low-mass stars with intermediate spectral resolution. We determine the stellar parameters of 2051 stars in Trumpler 14 (Tr14) in the Carina Nebula Complex, observed with VLT/MUSE. We adopt a conditional invertible neural network (cINN) architecture to infer the posterior distribution of stellar parameters and train our cINN on two Phoenix stellar atmosphere model libraries (Settl and Dusty). Compared to the cINNs presented in our first study, the updated cINN considers the influence of the relative flux error on the parameter estimation and predicts an additional fourth parameter, veiling. We test the prediction performance of cINN on synthetic test models to quantify the intrinsic error of the cINN as a function of relative flux error and on 36 class III template stars to validate the performance on real spectra. We provide Teff, logg, Av, and veiling values of 2051 stars in Tr14 measured by our cINN as well as stellar ages and masses derived from the Hertzsprung-Russell diagram based on the measured parameters. Our parameter estimates generally agree well with those measured by template fitting. However, for K- and G-type stars, the Teff derived from template fitting is, on average, 2-3 subclasses hotter than the cINN estimates, while the corresponding veiling values from template fitting appear to be underestimated compared to the cINN predictions. We obtain an average age of 0.7_-0.6_^+3.2^Myr for the Tr14 stars. By examining the impact of veiling on the equivalent width-based classification, we demonstrate that the main cause of temperature overestimation for K- and G-type stars in the previous study is that veiling and effective temperature are not considered simultaneously in their process. Our cINN performs comparably to the multi-dimensional template fitting method while being significantly faster and capable of consistently analysing stars across a wide temperature range (2600-7000K).2025A&A...697A..39Khttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/A+A/697/A39CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toJ/ApJS/194/10 : NIR properties of YSO in the CCCP (Preibisch+, 2011)J/A+A/603/A81 : Trumpler 14 and 16 in the Carina nebula (Damiani+, 2017)J/A+A/658/A198 : CHIPS II. O stars in Trumpler 14 CHIPS-Tr14 (Rainot+, 2022)J/A+A/685/A100 : Young low-mass stars population in Trumpler 14 (Itrich+, 2024)https://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/A+A/697/A39https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/A+A/697/A39http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/A+A/697/A39https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/A+A/697/A39https://vizier.iucaa.in/viz-bin/votable?-source=J/A+A/697/A39http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/A+A/697/A39GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/A+A/697/A39/table1 (Catalouge of low-mass stars in Trumpler 14 with stellar parameters measured by cINN)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/A+A/697/A39/table1?https://vizier.iucaa.in/viz-bin/conesearch/J/A+A/697/A39/table1?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/A+A/697/A39/table1?GETtext/xml+votable180.050000true161.0349322306667-59.48667410320.0055555555555555566/38016https://cdsarc.cds.unistra.fr/viz-bin/moc/J/A+A/697/A39?format=asciidefaultJ/A+A/697/A39/table1Catalouge of low-mass stars in Trumpler 14 with stellar parameters measured by cINNrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintIDStar's identification numbermeta.id;meta.maincharRAJ2000Right ascension (J2000)pos.eq.ra;meta.mainDEJ2000Declination (J2000)pos.eq.dec;meta.mainSample[Clean Uncertain] Name of sample groupmeta.id;src.sample;pos.lgcharSigMedMedian of relative flux error%stat.errorfloatTeffEffective temperatureKphys.temperature.effectivefloate_TeffError of TeffKstat.error;phys.temperature.effectivefloatloggLogarithm of surface gravitylog(cm.s**-2)phys.gravityfloate_loggError of logGlog(cm.s**-2)stat.errorfloatAvVisual extinctionmagphys.absorptionfloate_AvError of Avmagstat.errorfloatveilrVeiling at 7500{AA}phys.absorptionfloate_veilrError of veilrstat.errorfloatLibrary[Settl Dusty] Phoenix library originmeta.notecharSpTypeSpectral typesrc.spTypechare_SpType[] Left-hand side error of SpTypestat.error;src.spTypefloatE_SpType[] Right-hand side error of SpTypestat.error;stat.maxfloatLbolJ? Logarithm of stellar luminosity based on J-band photometry from HAWK-I or Vista (1)solLumphys.luminosity;em.IR.JfloatnullableMass? Stellar mass based on PARSEC models (2)solMassphys.massfloatnullableAge? Stellar age based on PARSEC models (2)Myrtime.agefloatnullableFileNameName of the pdf spectrum file in subdirectory spmeta.id;meta.filechar