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Magnetic chemically peculiar (mCP) stars are important to astrophysics because their complex atmospheres lend themselves perfectly to the investigation of the interplay between such diverse phenomena as atomic diffusion, magnetic fields, and stellar rotation. The present work is aimed at identifying new mCP stars using spectra collected by the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). Suitable candidates were selected by searching LAMOST DR4 spectra for the presence of the characteristic 5200A flux depression. Spectral classification was carried out with a modified version of the MKCLASS code and the accuracy of the classifications was estimated by comparison with results from manual classification and the literature. Using parallax data and photometry from Gaia DR2, we investigated the space distribution of our sample stars and their properties in the colour-magnitude diagram. Our final sample consists of 1002 mCP stars, most of which are new discoveries (only 59 previously known). Traditional mCP star peculiarities have been identified in all but 36 stars, highlighting the efficiency of the codes peculiarity identification capabilities. The derived temperature and peculiarity types are in agreement with manually derived classifications and the literature. Our sample stars are between 100 Myr and 1 Gyr old, with the majority having masses between 2M(Sun) and 3M(Sun). Our results could be considered as strong evidence for an inhomogeneous age distribution among low-mass (M < 3M(Sun)) mCP stars. We identified several astrophysically interesting objects: two mCP stars have distances and kinematical properties in agreement with halo stars; an eclipsing binary system hosting an mCP star component; and an SB2 system likely comprising of an mCP star and a supergiant component.
The present work presents our efforts at identifying new mercury-manganese (HgMn/CP3) stars using spectra obtained with the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). Suitable candidates were searched for among pre-selected e
In this work, we present a catalog of 2651 carbon stars from the fourth Data Release (DR4) of the Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST). Using an efficient machine-learning algorithm, we find out these stars from more than
In this paper we present a new catalogue of Chemically Peculiar (CP) stars obtained by compiling publications in which abundances of metals are provided. Our catalogue includes 428 stars for which the data were obtained through spectroscopic observat
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The number of known variable stars has increased by several magnitudes over the last decade, and automated classification routines are becoming increasingly important to cope with this development. Here we show that the upside-down CBH variables, whi