BANYAN Σ: Bayesian Analysis for Nearby Young AssociatioNs Σ
Membership probability without photometric information
BANYAN Σ is a Bayesian analysis tool to determine the membership probability of stars or other astrophysical objects to nearby young associations. This algorithm is based on a comparison of Galactic position (XYZ) and space velocity (UVW), using a Bayesian classifier. The tool currently includes all 27 known and well-characterized young associations within 150 pc. When radial velocity and/or distance measurements are not available, Bayesian inference has the advantage of being able to marginalize over them and still compute membership probabilities. When this is the case, BANYAN Σ produces statistical predictions for these quantities, assuming membership to each young association.
The information entered on this web page is not stored on our server.
The details of this method are described in Gagné et al. (2018a; ApJ, 856, 23).
v1.1 02/02/2018 Fixed issues with the name resolver and now uses Simbad to collect data.
v1.2 06/11/2018 Added 2 new groups: Volans-Carina (VCA) and Argus (ARG).
Please cite Zuckerman et al. 2018 if you use Argus (https://arxiv.org/abs/1811.01508); and cite Gagné et al. (2018f; ApJ, 865, 136) if you use Volans-Carina
The results of this tool should be interpreted with caution.
1) A high membership probability in a young association does not guarantee that the star is a true member, or young. Instead it should be regarded as a star that deserves further follow-up: before it is considered as a bona fide member, it must be demonstrated that its full 6D kinematics match that of the young association, and that it displays independent signs of youth.
2) The Bayesian probabilities reported by BANYAN Σ are designed to generate recovery rates of : (1) 50%, (2) 68%, (3) 82%, and (4) 90% respectively when (1) only proper motion is used, (2) proper motion and radial velocity are used, (3) proper motion and distance are used, and (4) proper motion, radial velocity and distance are used.