Here, you will find additional figures and tables for the Gagné et al. (2014) paper. I have put each of them on Figshare as well so that they get their own DOI if you wish to refer to a particular table or figure set. However, we kindly ask that you always at least refer Gagné et al. (2014) when using any of this material.
After the success of the BANYAN I web tool, we have decided to build another web tool for BANYAN II. It implements various modifications that were brought to our Bayesian classifier analysis, including rotated ellipsoids for the spatial and kinematic models of moving groups, the use of a Besançon Galaxy model for the old and young field population model, the use of prior probabilities different than unity to represent the expected population of a star for each hypothesis (taking account of the galactic latitude and the size of proper motion). As was the case with the BANYAN I web tool, no photometric treatment is available in the BANYAN II web tool.
We have collected a list of 158 young or unusually red object in the literature that were not already bona fide members to a known moving group or association. The list is restricted to objects with spectral types later than M5. It is available in 5 formats : iWork Numbers (v3 2013 or 2009) for MAC OS X, Microsoft Excel, CSV and PDF.
This table contains all known bona fide members to moving groups considered in Malo et al. (2013) and Gagné et al. (2014), as well as relevant photometric and kinematic information.
This table is an electronic version of Table 4 in Gagné et al. (2014).
This table is an electronic version of Table 5 in Gagné et al. (2014).
This table is a merged electronic version of Tables 1 and 2 in Gagné et al. (2014) in the EPS, PDF, Numbers v3, Numbers 2009 and XLSX formats.
This contains all tables in Gagné et al. (2014) in the latex TeX format.
These figures contain a map of the position and proper motion of bona fide members in nearby, young moving groups. Each star’s proper motion vector is prolongated into a great circle on the celestial sphere, to show that they converge in two points (the apex and anti-apex), which are often close to the Solar’s apex and anti-apex. Thanks to Adric Riedel for help in the construction of these figures, and see some similar figures that he made.
These figures compare the proper motion of each candidate member to nearby, young moving groups in Gagné et al. (2014) to figures described in Section 3.1.
These figures compare the position of each candidate member (red) of nearby, young moving groups in Gagné et al. (2014) to the color-magnitude sequences in Figure 3 (left) in the same reference, as well as new candidate members in Gagné et al. (in prep.) (black dots, purple dots for those whose youth is confirmed). See also Joe Filippazzo’s BDNYC post on the photometric properties of young stars. The statistical distance predictions from BANYAN II were used when a parallax measurement was unavailable. An empty circle means that the magnitude has been corrected for binarity, and an upside-down triangle means that a parallax measurement was used.
These figures compare the position of each candidate member to nearby, young moving groups in Gagné et al. (2014) to Figure 3 (right) in the same reference. The statistical distance predictions from BANYAN II were used when a parallax measurement was unavailable.
These figures show the 3-dimensional XYZ and UVW positions of bona fide member to nearby, young moving groups, as well as their ellipsoidal spatial models in Gagné et al. (2014). They are similar to Figure 2 in the same work (only shown for TW Hydrae therein).
These figures show the expected 3-dimensional XYZ and UVW positions of candidate members to nearby, young moving groups in Gagné et al. (2014), compared to figures similar to those in Section 3.5. The statistical distance and radial velocity predictions from BANYAN II were used when such measurements were unavailable.
These figures show the 2-dimensional posterior probability density functions as a function of radial velocity and distance for all candidate members presented in Gagné et al. (2014). They are similar to Figure 10 in the same reference.
These packages contain all figures in Gagné et al. (2014) in either the EPS or PDF formats.
These IDL save files contain the RV and distance probability density functions for the spatial and kinematic models of nearby, young moving groups as defined in Gagné et al. 2014. They can be used to generate Fig.1 in this reference (see Figshare description for more information).
This idl savefile contains the parameters of all spatial and Kinematic models of nearby, young associations of Gagné et al. 2014. You can acess them with the following command in IDL : IDL> restore, ‘mg_parameters_Gagne2014.sav’, /verbose & help, params_all, /str.
These two IDL routines can be used to transform Euler angles to a rotation matrix, and vice-versa.
This IDL routine uses the krEllipsoidFit algorithm (from Ronn Kling and Jerry Lefever) to fit a 3D ellipsoid to a set of cartesian coordinates. The krEllipsoidFit IDL routine was not written by our team but rather by Ronn Kling, so please give him credit and cite his web page (www.rlkling.com) when using this package (there is no paper to be cited), in addition to the reference to the BANYAN II paper.
This IDL routine can be used to rotate XYZUVW coordinates and their measurement errors in a new frame of reference, using either a rotation matrix or Euler angles.
These IDL routines can be used to transform ra, dec, distance and the error on distance for any number of stars to XYZ coordinates and their errors, as well as ra, dec, distance, proper motion and radial velocity to UVW coordinates and their errors. This package includes a modification on the glactc.pro astrolib routine that is significantly faster with large sets of objects.
This IDL routine can be used to transform the Bayesian probability of a candidate member to its field contamination probability (calculated from the Monte Carlo simulation presented in Section 5 of Gagné et al., 2014). The proper motion, sky position as well as radial velocity (if available) and distance (if available) must be input in order to compute the χ-factors that are used to adjust the expected field and NYA populations for a given object. Because of this, this routine can correctly make predictions for e.g. objects with very small proper motions, or objects in the Galactic plane.
This IDL routine uses the 2MASS and WISE J, H, Ks, W1 and W2 apparent magnitudes and the distance of a given object, along with an estimated age range, to determine its most probable mass range using AMES-COND isochrones (Baraffe et al. (2003) in combination with CIFIST2011 BT-SETTL atmosphere models (Allard et al. 2013, Rajpurohit et al. 2013) in a likelihood analysis. Errors on the distance and photometry, when input, are propagated to the estimated mass range. This routine was used to estimate the masses of candidate members in Table 3 of Gagné et al. (2014). Please cite Gagné et al. 2014, Baraffe et al. 2003, Allard et al. 2013 and Rajpurohit et al. 2013 (see links on Figshare page) if you use this procedure.
This IDL routine uses an optimal variance-weighted mean to combine measurements of the same physical quantity with individual errors. It corrects for over-dispersion to account for possible underestimations of individual measurements, as well as an intrinsically varying physical quantity. The routine does not correct for under-dispersion to avoid strange behaviours in cases where individual measurements are very close one to another. This IDL routines uses the method described here, and was used to combine radial velocity, proper motion and distance measurements in Gagné et al. (2014).