J/MNRAS/476/3233ivo://CDS.VizieR/J/MNRAS/476/3233doi:10.26093/cds/vizier.74763233CDSHon M.Stello D.Yu J.2025-05-22T20:15:30Z2023-10-04T08:14:43ZCDS support team

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

cds-question@unistra.frgiant-starsvisible-astronomyasteroseismologyDeep learning in the form of 1D convolutional neural networks have previously been shown to be capable of efficiently classifying the evolutionary state of oscillating red giants into red giant branch stars and helium-core burning stars by recognizing visual features in their asteroseismic frequency spectra. We elaborate further on the deep learning method by developing an improved convolutional neural network classifier. To make our method useful for current and future space missions such as K2, TESS, and PLATO, we train classifiers that are able to classify the evolutionary states of lower frequency resolution spectra expected from these missions. Additionally, we provide new classifications for 8633 Kepler red giants, out of which 426 have previously not been classified using asteroseismology. This brings the total to 14983 Kepler red giants classified with our new neural network. We also verify that our classifiers are remarkably robust to suboptimal data, including low signal-to-noise and incorrect training truth labels.2018MNRAS.476.3233Hhttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/MNRAS/476/3233CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toV/133 : Kepler Input Catalog (Kepler Mission Team, 2009)J/MNRAS/469/4578 : Deep learning classification in asteroseismologyhttps://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/MNRAS/476/3233https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/MNRAS/476/3233http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/MNRAS/476/3233https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/MNRAS/476/3233https://vizier.iucaa.in/viz-bin/votable?-source=J/MNRAS/476/3233http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/MNRAS/476/3233GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/MNRAS/476/3233/table3 (Population class predictions for 14983 Kepler red giants)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/MNRAS/476/3233/table3?https://vizier.iucaa.in/viz-bin/conesearch/J/MNRAS/476/3233/table3?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/MNRAS/476/3233/table3?GETtext/xml+votable180.050000true291.0558836.55995190.0055555555555555564/922-923 933-935 944-946 5/3645-3647 3683 3704 3706 3729-3731 3760 3788-3789 3792-3793 6/14559 14567 14573 14575 14577-14579 14730-14731 14738 14744 14746-14747 14749-14751 14792 14794-14795 14822 14828 14830-14831 14914-14915 15044-15045 15057 15059-15062 15160-15161 15176-15178 15200 15202 15232-15233https://cdsarc.cds.unistra.fr/viz-bin/moc/J/MNRAS/476/3233?format=asciiOpticaldefaultJ/MNRAS/476/3233/table3Population class predictions for 14983 Kepler red giantsSimbadSimbad column added by the CDSmeta.ref.urlcharrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintKICKIC numbermeta.id;meta.mainintPop[0/1] Population (1)meta.codeintProb? Probability (2)stat.probabilityfloatnullablee_Prob? Uncertainty on probabilitystat.errorfloatnullabledeltanuMean large frequency separation of modes with the same degree and consecutive order, {DELTA}nu (Yu et al., in prep.)em.freq;src.vardoublenumaxFrequency of maximum oscillation power (Yu et al., in prep.)em.freq;src.vardoubleepsilon? Location of the l=0 mode (3)stat.fit.paramfloatnullableFlagsFlags (4)meta.code.errorchar_RAPositions from KIC (Cat. V/133) catalog (right ascension part)degpos.eq.ra;meta.mainindexed_DEPositions from KIC (Cat. V/133) catalog (declination part)degpos.eq.dec;meta.mainindexed