Exploring the Morphology of RAVE Stellar Spectra

G. Matijevic*, T. Zwitter, O. Bienayme, J. Bland-Hawthorn, C. Boeche, K. C. Freeman, B. K. Gibson, G. Gilmore, E. K. Grebel, A. Helmi, U. Munari, J. Navarro, Q. A. Parker, W. Reid, G. Seabroke, A. Siebert, A. Siviero, M. Steinmetz, F. G. Watson, M. WilliamsR. F. G. Wyse

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

The RAdial Velocity Experiment (RAVE) is a medium-resolution (R similar to 7500) spectroscopic survey of the Milky Way that has already obtained over half a million stellar spectra. They present a randomly selected magnitude-limited sample, so it is important to use a reliable and automated classification scheme that identifies normal single stars and discovers different types of peculiar stars. To this end, we present a morphological classification of similar to 350,000 RAVE survey stellar spectra using locally linear embedding, a dimensionality reduction method that enables representing the complex spectral morphology in a low-dimensional projected space while still preserving the properties of the local neighborhoods of spectra. We find that the majority of all spectra in the database (similar to 90%-95%) belong to normal single stars, but there is also a significant population of several types of peculiars. Among them, the most populated groups are those of various types of spectroscopic binary and chromospherically active stars. Both of them include several thousands of spectra. Particularly the latter group offers significant further investigation opportunities since activity of stars is a known proxy of stellar ages. Applying the same classification procedure to the sample of normal single stars alone shows that the shape of the projected manifold in two-dimensional space correlates with stellar temperature, surface gravity, and metallicity.

Original languageEnglish
Article number14
Number of pages14
JournalAstrophysical journal supplement series
Volume200
Issue number2
DOIs
Publication statusPublished - Jun-2012

Keywords

  • methods: numerical
  • stars: peculiar
  • techniques: spectroscopic
  • EVALUATING GAIA PERFORMANCES
  • PRINCIPAL COMPONENT ANALYSIS
  • VELOCITY EXPERIMENT RAVE
  • DIGITAL SKY SURVEY
  • 1ST DATA RELEASE
  • AUTOMATED CLASSIFICATION
  • ECLIPSING BINARIES
  • NEURAL-NETWORKS
  • HIGH-RESOLUTION
  • PECULIAR STARS

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