Kinematic Ages of the Tucana–Horologium, Columba, and Carina Associations
Authors/Creators
- 1. Université de Montreal
- 2. Planétarium de Montréal, Espace pour la vie
- 3. Trottier Institute for Research on Exoplanets
- 4. Université de Montréal
- 5. Planétarium de Montréal, Espace pour la Vie
Description
Nearby young associations are ideal laboratories to study the early evolution of cool stars. The traceback method can constrain the age of an association from astrometric and kinematic data alone, circumventing the need for stellar evolution models. Previous traceback age estimates have, however, often been incompatible with other age-dating methods. We applied the Kinematic Age for Nearby Young Associations (kanya) traceback analysis tool on core samples, free of contaminants such as unresolved multiple systems, of carefully vetted members of the Tucana–Horologium (THA), Columba (COL), and Carina (CAR) associations, using data from Gaia Data Release 3 (DR3) data products and other kinematic surveys included in the Montreal Open Clusters and Associations (MOCA) Database, in order to test whether the traceback method can be used successfully on 40–50 Myr-old associations. Several systematic biases, including gravitational redshift, convective blueshift, and the bias on traceback ages due to random measurement errors, were accounted for. We found that the mean length of all branches between members and the trace of the spatial covariance matrix are the most robust and generalizable association size metrics among those that were tested. We obtained reliable constraints on the traceback ages: $44.8_{-7.0}^{+2.1}$ Myr for THA, and $28.4_{-2.9}^{+1.8}$ Myr for COL and CAR. These results are compatible with previous age estimates for THA, COL, and CAR computed with the isochrones and lithium depletion boundary (LDB) methods.
Files
Poster.pdf
Files
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Additional details
Related works
- Is source of
- Journal article: 10.3847/1538-4357/ae1d79 (DOI)
Software
- Repository URL
- https://github.com/dominicouture/kanya
- Programming language
- Python