BANYAN. XI. The BANYAN Sigma Multivariate Bayesian Algorithm to Identify Members of Young Associations with 150 pc

Affiliation auteurs!!!! Error affiliation !!!!
TitreBANYAN. XI. The BANYAN Sigma Multivariate Bayesian Algorithm to Identify Members of Young Associations with 150 pc
Type de publicationJournal Article
Year of Publication2018
AuteursGagne J, Mamajek EE, Malo L, Riedel A, Rodriguez D, Lafreniere D, Faherty JK, Roy-Loubier O, Pueyo L, Robin AC, Doyon R
JournalASTROPHYSICAL JOURNAL
Volume856
Pagination23
Date PublishedMAR 20
Type of ArticleArticle
ISSN0004-637X
Mots-clésbrown dwarfs, methods: data analysis, proper motions, stars: kinematics and dynamics, stars: low-mass
Résumé

BANYAN Sigma is a new Bayesian algorithm to identify members of young stellar associations within 150 pc of the Sun. It includes 27 young associations with ages in the range similar to 1-800 Myr, modeled with multivariate Gaussians in six-dimensional (6D) XYZUVW space. It is the first such multi-association classification tool to include the nearest sub-groups of the Sco-Cen OB star-forming region, the IC. 2602, IC. 2391, Pleiades and Platais. 8 clusters, and the rho Ophiuchi, Corona Australis, and Taurus star formation regions. A model of field stars is built from a mixture of multivariate Gaussians based on the Besancon Galactic model. The algorithm can derive membership probabilities for objects with only sky coordinates and proper motion, but can also include parallax and radial velocity measurements, as well as spectrophotometric distance constraints from sequences in color-magnitude or spectral type-magnitude diagrams. BANYAN Sigma S benefits from an analytical solution to the Bayesian marginalization integrals over unknown radial velocities and distances that makes it more accurate and significantly faster than its predecessor BANYAN. II. A contamination versus hit rate analysis is presented and demonstrates that BANYAN Sigma S achieves a better classification performance than other moving group tools available in the literature, especially in terms of cross-contamination between young associations. An updated list of bona fide members in the 27 young associations, augmented by the Gaia-DR1 release, as well as all parameters for the 6D multivariate Gaussian models for each association and the Galactic field neighborhood within 300 pc are presented. This new tool will make it possible to analyze large data sets such as the upcoming Gaia-DR2 to identify new young stars. IDL and Python versions of BANYAN Sigma S are made available with this publication, and a more limited online web tool is available at http://www.exoplanetes.umontreal.ca/banyan/banyansigma.php.

DOI10.3847/1538-4357/aaae09