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Atmospheric parameters of M4 stars

Short name: J/AJ/147/25
IVOA Identifier: ivo://CDS.VizieR/J/AJ/147/25
DOI (Digital Object Identifier): 10.26093/cds/vizier.51470025
Publisher: CDS[+][Pub. ID]
More Info: https://cdsarc.cds.unistra.fr/viz-bin/cat/J/AJ/147/25
VO Compliance: Level 2: This is a VO-compliant resource.
Status: active
Registered: 2016 Apr 18 09:18:28Z
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Description


We report new metallicities for stars of Galactic globular cluster M4 using the largest number of stars ever observed at high spectral resolution in any cluster. We analyzed 7250 spectra for 2771 cluster stars gathered with the Very Large Telescope (VLT) FLAMES+GIRAFFE spectrograph at VLT. These medium-resolution spectra cover a small wavelength range, and often have very low signal-to-noise ratios. We approached this data set by reconsidering the whole method of abundance analysis of large stellar samples from beginning to end. We developed a new algorithm that automatically determines the atmospheric parameters of a star. Nearly all of the data preparation steps for spectroscopic analyses are processed on the syntheses, not the observed spectra. For 322 red giant branch (RGB) stars with V<=14.7, we obtain a nearly constant metallicity, <[Fe/H]>=-1.07 ({sigma}=0.02). No difference in the metallicity at the level of 0.01 dex is observed between the two RGB sequences identified by Monelli et al. (2013MNRAS.431.2126M). For 1869 subgiant and main-sequence stars with V>14.7, we obtain <[Fe/H]>=-1.16 ({sigma}=0.09) after fixing the microturbulent velocity. These values are consistent with previous studies that have performed detailed analyses of brighter RGB stars at higher spectroscopic resolution and wavelength coverage. It is not clear if the small mean metallicity difference between brighter and fainter M4 members is real or is the result of the low signal-to-noise characteristics of the fainter stars. The strength of our approach is shown by recovering a metallicity close to a single value for more than 2000 stars, using a data set that is non-optimal for atmospheric analyses. This technique is particularly suitable for noisy data taken in difficult observing conditions.

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