Ensemble age inversions for large spectroscopic surveys
Abstract
Context. Galactic astrophysics is now in the process of building a multidimensional map of the Galaxy. For such a map, stellar ages are an essential ingredient. Ages are measured only indirectly however, by comparing observational data with models. It is often difficult to provide a single age value for a given star, as several nonoverlapping solutions are possible.
Aims: We aim at recovering the underlying log(age) distribution from the measured log(age) probability density function for an arbitrary set of stars.
Methods: We build an age inversion method, namely we represent the measured log(age) probability density function as a weighted sum of probability density functions of monoage populations. Weights in that sum give the underlying log(age) distribution. Monoage populations are simulated so that the distribution of stars on the log g[Fe/H] plane is close to that of the observed sample.
Results: We tested the age inversion method on simulated data, demonstrating that it is capable of properly recovering the true log(age) distribution for a large (N > 10^{3}) sample of stars. The method was further applied to large public spectroscopic surveys. For RAVEon, LAMOST and APOGEE we also applied age inversion to monometallicity samples, successfully recovering agemetallicity trends present in higherprecision APOGEE data and chemical evolution models.
Conclusions: We conclude that applying an age inversion method as presented in this work is necessary to recover the underlying age distribution of a large (N > 10^{3}) set of stars. These age distributions can be used to explore agemetallicity relations, for instance.
 Publication:

Astronomy and Astrophysics
 Pub Date:
 September 2019
 DOI:
 10.1051/00046361/201935864
 arXiv:
 arXiv:1908.04548
 Bibcode:
 2019A&A...629A.127M
 Keywords:

 methods: statistical;
 stars: fundamental parameters;
 Galaxy: stellar content;
 Astrophysics  Astrophysics of Galaxies;
 Astrophysics  Solar and Stellar Astrophysics
 EPrint:
 15 pages, 15 figures