The chemical composition of red giants in 47 Tucanae II. Magnesium isotopes and pollution scenarios

Abstract

Context. The phenomenon of multiple populations in globular clusters is still far from understood, with several proposed mechanisms to explain the observed behaviour. The study of elemental and isotopic abundance patterns are crucial for investigating the differences among candidate pollution mechanisms. Aims. We derive magnesium isotopic ratios for 13 stars in the globular cluster 47 Tucanae (NGC 104) to provide new, detailed information about the nucleosynthesis that has occurred within the cluster. For the first time, the impact of 3D model stellar atmospheres on the derived Mg isotopic ratios is investigated. Methods. Using both tailored 1D atmospheric models and 3D hydrodynamical models, we derive magnesium isotopic ratios from four features of MgH near 5135 Å in 13 giants near the tip of the red giant branch, using high signal-to-noise, high-resolution spectra. Results. We derive the magnesium isotopic ratios for all stars and find no significant offset of the isotopic distribution between the pristine and the polluted populations. Furthermore, we do not detect any statistically significant differences in the spread in the Mg isotopes in either population. No trends were found between the Mg isotopes and [Al/Fe]. The inclusion of 3D atmospheres has a significant impact on the derived ^(25)Mg/^(24)Mg ratio, increasing it by a factor of up to 2.5, compared to 1D. The ^(26)Mg/^(24)Mg ratio, on the other hand, essentially remains unchanged. Conclusions. We confirm the results seen from other globular clusters, where no strong variation in the isotopic ratios is observed between stellar populations, for observed ranges in [Al/Fe]. We see no evidence for any significant activation of the Mg-Al burning chain. The use of 3D atmospheres causes an increase of a factor of up to 2.5 in the fraction of 25Mg, resolving part of the discrepancy between the observed isotopic fraction and the predictions from pollution models.

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