2021
DOI: 10.1093/mnras/staa3401
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Discovery of new mercury–manganese stars, including a fast rotator

Abstract: The origin of mercury–manganese (HgMn) stars is still poorly understood and the statistical analysis of an extensive sample of well characterized objects would be very valuable. Nevertheless, the compilation of a clean and reliable list of all known HgMn stars, and complete characterization of those objects, is still a pending issue. We report the identification of 13 new HgMn stars from our own spectroscopic observations and from publicly available spectral libraries. In addition, we perform a thorough litera… Show more

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Cited by 7 publications
(8 citation statements)
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“…Our results challenge the hypothesis of a sharp rotational cutoff of the HgMn phenomenon, but should be verified by confirmation of the HgMn nature of each of these rapid rotators based on high-resolution spectroscopic observations and detailed abundance analysis. This confirmation has already been obtained for HD 169027 by Woolf & Lambert (1999) and for HD 93549 and HD 145842 by González et al (2021).…”
Section: Discussionsupporting
confidence: 79%
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“…Our results challenge the hypothesis of a sharp rotational cutoff of the HgMn phenomenon, but should be verified by confirmation of the HgMn nature of each of these rapid rotators based on high-resolution spectroscopic observations and detailed abundance analysis. This confirmation has already been obtained for HD 169027 by Woolf & Lambert (1999) and for HD 93549 and HD 145842 by González et al (2021).…”
Section: Discussionsupporting
confidence: 79%
“…The 3 stars with 2-5 mmag g-mode oscillations (HD 29589, HD 93549, HD 171301) are particularly interesting for follow up studies and detailed asteroseismic analyses. All three objects have been studied with high-resolution spectra (Hubrig et al 2011;González et al 2021;Adelman, Gulliver & Gucella 2017) and their HgMn classification is indisputable. Two other well-studied HgMn stars, HD 172728 (Adelman, Gulliver & Rayle 2001) and HD 173524 , have the longest TESS data sets (12 and 10 TESS sectors respectively).…”
Section: Discussionmentioning
confidence: 99%
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