1998/09/28 by Santiago Torres, Enrique García-Berro, Enrique Garcia-Berro +1 · 1 citation
Physics and Astronomy · #Astronomy and Astrophysical Research #Scientific Research and Discoveries #Stellar, planetary, and galactic studies #astro-ph
paper · pdf · doi:10.1086/311721
15 pages, 3 postscript figures. Accepted for publication in ApJ Letters, uses aasms4.sty
arxiv created 1998/09/28 · openalex publication_date 1998/11/20 · arxiv updated 2009/12/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/31
The white dwarf luminosity function has proved to be an excellent tool for studying some properties of the Galactic disk, such as its age and the past history of the local star formation rate. The existence of an observational luminosity function for halo white dwarfs could provide valuable information about its age and the time that the star formation rate lasted, and it could also constrain the shape of the allowed initial mass functions. However, the main problem is the scarce number of white dwarfs already identified as halo stars. In this Letter, we show how an artificial intelligence algorithm can be used successfully to classify the population of spectroscopically identified white dwarfs, thus allowing us to identify several potential halo white dwarfs and to improve the significance of its luminosity function.