Hot subdwarf candidates from LAMOST DR7 Virtual Observatory Resource

Authors
  1. Tan L.
  2. Mei Y.
  3. Liu Z.
  4. Luo Y.
  5. Deng H.
  6. Wang F.
  7. Deng L.
  8. Liu C.
  9. Published by
    CDS
Abstract

Hot subdwarf stars are a particular type of star that is crucial for studying binary evolution and atmospheric diffusion processes. In recent years, identifying hot subdwarfs by machine-learning methods has become a hot topic, but there are still limitations in automation and accuracy. In this paper, we proposed a robust identification method based on a convolutional neural network. We first constructed the data set using the spectral data of LAMOST DR7-V1. We then constructed a hybrid recognition model including an eight-class classification model and a binary classification model. The model achieved an accuracy of 96.17% on the testing set. To further validate the accuracy of the model, we selected 835 hot subdwarfs that were not involved in the training process from the identified LAMOST catalog (2428, including repeated observations) as the validation set. An accuracy of 96.05% was achieved. On this basis, we used the model to filter and classify all 10,640,255 spectra of LAMOST DR7-V1, and obtained a catalog of 2393 hot subdwarf candidates, of which 2067 have been confirmed. We found 25 new hot subdwarfs among the remaining candidates by manual validation. The overall accuracy of the model is 87.42%. Overall, the model presented in this study can effectively identify specific spectra with robust results and high accuracy, and can be further applied to the classification of large-scale spectra and the search for specific targets.

Keywords
  1. Subdwarf stars
  2. Optical astronomy
  3. Spectroscopy
Bibliographic source Bibcode
2022ApJS..259....5T
See also HTML
https://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJS/259/5
IVOA Identifier IVOID
ivo://CDS.VizieR/J/ApJS/259/5
Document Object Identifer DOI
doi:10.26093/cds/vizier.22590005

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History

2022-09-09T08:59:34Z
Resource record created
2022-09-09T08:59:34Z
Created
2023-11-13T08:06:41Z
Updated

Contact

Name
CDS support team
Postal Address
CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France
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cds-question@unistra.fr