Evidence of extra mixing in field giants as traced by the lithium and carbon isotope ratio

Abstract

Context. Although not predicted by standard stellar evolution, the surface abundance of light elements, such as lithium (Li), carbon, and nitrogen, changes during the red giant branch (RGB) as a result of extra mixing. This is usually associated with thermohaline mixing acting after the RGB bump. Peculiar Li-enriched RGB stars might also be related to either enhanced mixing or pollution from external sources. Aims. We measure the Li abundance and carbon isotopic ratio 12C=13C in a sample of 166 field red giants with 0:3 _ [Fe=H] _ 0:2, targeted by the EXPRESS radial velocity program to analyze the e_ects of extra mixing. Methods. We measured the abundances with spectral synthesis using high-quality spectra. Multiple-epoch observations needed for exoplanet detection were used to decrease the e_ects of telluric contamination in 12C=13C measurements. Results. Due to the prevalence of upper limits, the Li abundance pattern is complicated to interpret, but the comparison between RGB and core He-burning giants shows e_ects of mixing consistent with thermohaline. The most Li-enriched giant in the sample, classified as a RGB star close to the RGB bump, has low 12C=13C. Given that the 12C=13C should not be a_ected by planet engulfment, this does not seem to be the source of the high Li. There is a decreasing correlation between mass and 12C=13C in the RGB and an increasing correlation in the horizontal branch, which, once again, is consistent with thermohaline mixing. Our data also show a correlation between 12C=13C and [Fe/H]. There is no evident impact of binarity either on Li or on 12C=13C. Conclusions. Our sample shows behavior consistent with additional mixing acting after the RGB bump. The 12C=13C adds new clues which can be used to describe extra mixing, and it could well be the best tool to study mixing in giants. Additional measurements of 12C=13C in field stars would greatly improve our ability to compare data with models and understand mixing mechanisms.