The Gaia-ESO Survey: Target selection of open cluster stars

Astronomy and Astrophysics(2022)

Cited 0|Views10
No score
Abstract
The Gaia-ESO Survey (GES) is a public, high-resolution spectroscopic survey with FLAMES@VLT. GES targeted in particular a large sample of open clusters (OCs) of all ages. The different kinds of OCs are useful to reach the main science goals, which are the study of the OC structure and dynamics, the use of OCs to constrain and improve stellar evolution models, and the definition of Galactic disc properties (e.g. metallicity distribution). GES is organised in 19 working groups (WGs). We describe here the work of three of them, WG4 in charge of the selection of the targets within each cluster), WG1 responsible for defining the most probable candidate members, and WG6 in charge of the preparation of the observations. As GES has been conducted before Gaia DR2, we could not make use of the Gaia astrometry to define cluster members. We made use of public and private photometry to select the stars to be observed with FLAMES. Candidate target selection was based on ground-based proper motions, radial velocities, and X-ray properties when appropriate, and it was mostly used to define the position of the clusters' evolutionary sequences in the colour-magnitude diagrams. Targets for GIRAFFE were selected near the sequences in an unbiased way. We used available information on membership only for the few UVES stars. We collected spectra for 62 confirmed OCs (a few more were taken from the ESO archive). Among them are very young clusters, where the main targets are pre-main sequence stars, clusters with very hot and massive stars currently on the main sequence, intermediate-age and old clusters where evolved stars are the main targets. The selection of targets was as inclusive and unbiased as possible and we observed a representative fraction of all possible targets, thus collecting the largest, most accurate, and most homogeneous spectroscopic data set on ever achieved. [abridged]
More
Translated text
Key words
cluster,stars,target selection
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined