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Sr and Ba abundance determinations: comparing machine-learning with star-by-star analyses -- High-resolution re-analysis of suspected LAMOST barium stars

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arxiv 2107.08401 v1 pith:VQ5HPOQH submitted 2021-07-18 astro-ph.SR

Sr and Ba abundance determinations: comparing machine-learning with star-by-star analyses -- High-resolution re-analysis of suspected LAMOST barium stars

classification astro-ph.SR
keywords starsbariummildoverabundancespreviouss-processstrongba-only
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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A new large sample of 895 s-process-rich candidates out of 454180 giant stars surveyed by LAMOST at low spectral resolution (R ~ 1800) has been reported by Norfolk et al. (2019; hereafter N19). We aim at confirming the s-process enrichment at the higher resolution (R ~ 86000) offered by the HERMES-Mercator spectrograph, for the 15 brightest targets of the previous study sample which consists in 13 Sr-only stars and two Ba-only stars. Abundances were derived for elements Li, C, N, O, Na, Mg, Fe, Rb, Sr, Y, Zr, Nb, Ba, La, and Ce. Binarity has been tested by comparing the Gaia DR2 radial velocity with the HERMES velocity obtained 1600 - 1800 days later. Among the 15 programme stars, four show no s-process overabundances ([X/Fe] < 0.2 dex), eight show mild s-process overabundances (at least three heavy elements with 0.2 < [X/Fe] < 0.8), and three have strong overabundances (at least three heavy elements with [X/Fe] > 0.8). Among the 13 stars classified as Sr-only by the previous investigation, four have no s-process overabundances, eight are mild barium stars, and one is a strong barium star. The two Ba-only stars turn out to be both strong barium stars and are actually dwarf barium stars. They also show clear evidence for being binaries. Among the no-s stars, there are two binaries out of four, whereas only one out of the eight mild barium stars show a clear signature of radial-velocity variations. Blending effects and saturated lines have to be considered very carefully when using machine-learning techniques, especially on low-resolution spectra. Among the Sr-only stars from the previous study sample, one may expect about 60% (8/13) of them to be true mild barium stars and about 8% to be strong barium stars, and this fraction is likely close to 100% for the previous study Ba-only stars (2/2).

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