Sr and Ba abundances: Comparing machine-learning with star-by-star analyses. High-resolution re-analysis of suspected LAMOST barium stars

2021 
Context. A new large sample of 895 s-process-rich candidates out of 454 180 giant stars surveyed by LAMOST at a low spectral resolution (R ~ 1800) has been reported by Norfolk et al. (2019, MNRAS, 490, 2219; hereafter N19).Aims. This study is aimed at confirming the s-process enrichment at the higher resolution (R ~ 86 000) offered by the HERMES-Mercator spectrograph for the 15 brightest targets of the N19 sample, which consists of 13 Sr-only stars and two Ba-only stars (designating stars with only the Sr or only Ba lines strengthened).Methods. Abundances were derived for elements Li, C (including the 12 C/13 C isotopic ratio), N, O, Na, Mg, Fe, Rb, Sr, Y, Zr, Nb, Ba, La, and Ce, using the TURBOSPECTRUM radiative transfer LTE code with MARCS model atmospheres. Binarity has been tested by comparing the Gaia DR2 radial velocity (epoch 2015.5) with the HERMES velocity obtained 1600–1800 days (about 4.5 yr) later.Results. Among the 15 programme stars, 4 show no s-process overabundances ([X/Fe] ∕Fe ] Blending effects and saturated lines have to be considered very carefully when using machine-learning techniques, especially when applied to low-resolution spectra. Among the Sr-only stars from the previous study sample, about 60% (8/13) of them can be expected to be true mild barium stars and about 8% to be strong barium stars; this fraction is likely close to 100% for the N19 Ba-only stars (2/2). Therefore, we recommend to limit the sample to N19 Ba-only stars when one needs an unpolluted sample of mass-transfer (i.e., extrinsic) objects.
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