Stars with discrepant v sin i as derived from Ca II 3933 and Mg II 4481 Å lines. I. Composite-spectrum ... View Full Text


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Article Info

DATE

2011-07

AUTHORS

J. Zverko, J. Žižňovský, I. Iliev, I. Barzova, I. Stateva, I. I. Romanyuk, D. O. Kudryavtsev, E. A. Semenko

ABSTRACT

Axial rotation of a star plays an important role in its evolution, physical conditions in its atmosphere and the shape of its spectrum. Methods of determining of v sin i are based on comparison of the observed profiles of spectral lines with the theoretical ones. Their accuracy depends on the type and quality of spectrograms, as well as on the algorithms used. A frequently used method is a simple comparison of one line, e.g. the Ca ii at 3933 Å or Mg ii at 4481 Å. This, however, may result in a false value of v sin i in case when low-dispersion spectra are used. We investigate the spectra of stars with a significant discrepancy of their rotational velocities introduced in various sources, and analyze the corresponding spectral region from the point of view of possible admixed features, which may mask the true line profiles. We use CCD spectra of the stars having this discrepancy, to compare with theoretical spectra. We also studied photographic spectra, obtained during the 1970s and 1980s. In this work we studied the spectra of the binary HD 2913A, and identified the spectrum of its weaker component designated as “Ab”. We estimated the effective temperature, surface gravity and projected rotational velocity of the weaker component that classify it as an early F-type Main Sequence star. The discrepancy between the values of v sin i derived from the two lines of calcium and magnesium is explained as a consequence of superposition of the pair’s spectra. The cooler component contributes by a strong Ca ii-K line, and thus significantly broadens the observed line profile. More... »

PAGES

325

Identifiers

URI

http://scigraph.springernature.com/pub.10.1134/s1990341311030059

DOI

http://dx.doi.org/10.1134/s1990341311030059

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1015398576


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