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Table · dataset · 2023

14983 Kepler red giants

Listed in IVOA Registry (Virtual Observatory)

Deep 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.

Description

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.

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We also verify that our classifiers are remarkably robust to suboptimal data, including low signal-to-noise and incorrect training truth labels.

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Stated by source
Optical
Provenance · 1 source records, 8 field assertions
SourceKeyLast seenRaw
IVOA Registry (Virtual Observatory)ivo://cds.vizier/j/mnras/476/323315 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · IVOA Registryconnector:ivoa_registry@1.0.0
concepts[field].local:field:astronomymapping · IVOA Registryconnector:ivoa_registry@1.0.0
concepts[modality].ivoa_waveband:opticalsource · IVOA Registryconnector:ivoa_registry@1.0.0
descriptionsource · IVOA Registryconnector:ivoa_registry@1.0.0rr.resource.res_description
license_textsource · IVOA Registryconnector:ivoa_registry@1.0.0
publication_datesource · IVOA Registryconnector:ivoa_registry@1.0.0
titlesource · IVOA Registryconnector:ivoa_registry@1.0.0rr.resource.res_title
updated_datesource · IVOA Registryconnector:ivoa_registry@1.0.0