Abstract

Context. Ruprecht 147 (NGC 6774) is the closest old open cluster, with a distance of less than 300 pc and an age of about 2.5 Gyr. It is therefore well suited for testing stellar evolution models and for obtaining precise and detailed chemical abundance information. Aims. We combined photometric and astrometric information coming from literature and the Gaia mission with very high-resolution optical spectra of stars in different evolutionary stages to derive the cluster distance, age, and detailed chemical composition. Methods. We obtained spectra of six red giants using HARPS-N at the Telescopio Nazionale Galileo (TNG). We also used European Southern Observatory (ESO) archive spectra of 22 main sequence (MS) stars, observed with HARPS at the 3.6 m telescope. The very high resolution (115 000) and the large wavelength coverage (about 380–680 nm) of the twin instruments permitted us to derive atmospheric parameters, metallicity, and detailed chemical abundances of 23 species from all nucleosynthetic channels. We employed both equivalent widths and spectrum synthesis. We also re-derived the cluster distance and age using Gaia parallaxes, proper motions, and photometry in conjunction with the PARSEC stellar evolutionary models. Results. We fully analysed those stars with radial velocity and proper motion/parallax in agreement with the cluster mean values. We also discarded one binary not previously recognised, and six stars near the MS turn-off because of their high rotation velocity. Our final sample consists of 21 stars (six giants and 15 MS stars). We measured metallicity (the cluster average [Fe/H] is +0.08, rms = 0.07) and abundances of light, α, Fe-peak, and neutron-capture elements. The Li abundance follows the expectations, showing a tight relation between temperature and abundance on the MS, at variance with M 67, and we did not detect any Li-rich giant. Conclusions. We confirm that Rup 147 is the oldest nearby open cluster. This makes it very valuable to test detailed features of stellar evolutionary models.

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