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Register a new userCarbon stars identified from LAMOST DR4 using Machine Learning
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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 seven million spectra. As a by-product, 17 carbon-enhanced metal-poor (CEMP) turnoff star candidates are also reported in this paper, and they are preliminarily identified by their atmospheric parameters. Except for 176 stars that could not be given spectral types, we classify the other 2475 carbon stars into five subtypes including 864 C-H, 226 C-R, 400 C-J, 266 C-N, and 719 barium stars based on a series of spectral features. Furthermore, we divide the C-J stars into three subtypes of CJ( H), C-J(R), C-J(N), and about 90% of them are cool N-type stars as expected from previous literature. Beside spectroscopic classification, we also match these carbon stars to multiple broadband photometries. Using ultraviolet photometry data, we find that 25 carbon stars have FUV detections and they are likely to be in binary systems with compact white dwarf companions.
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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 early-type spectra from LAMOST DR4 using a modified version of the MKCLASS code that probes several Hg II and Mn II features. The spectra of the resulting 332 candidates were visually inspected. Using parallax data and photometry from Gaia DR2, we investigated magnitudes, distances from the Sun, and the evolutionary status of our sample stars. We also searched for variable stars using diverse photometric survey sources. We present 99 bona fide CP3 stars, 19 good CP3 star candidates, and seven candidates. Our sample consists of mostly new discoveries and contains, on average, the faintest CP3 stars known (peak distribution 9.5 < G < 13.5 mag). All stars are contained within the narrow spectral temperature-type range from B6 to B9.5, in excellent agreement with the expectations and the derived mass estimates (2.4 < M(Sun) < 4 for most objects). Our sample stars are between 100 Myr and 500 Myr old and cover the whole age range from zero-age to terminal-age main sequence. They are almost homogeneously distributed at fractional ages on the main sequence < 80%, with an apparent accumulation of objects between fractional ages of 50% to 80%. We find a significant impact of binarity on the mass and age estimates. Eight photometric variables were discovered, most of which show monoperiodic variability in agreement with rotational modulation. Together with the recently published catalogue of APOGEE CP3 stars, our work significantly increases the sample size of known Galactic CP3 stars, paving the way for future in-depth statistical studies.
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.
In this work, we present the new catalog of carbon stars from the LAMOST DR2 catalog. In total, 894 carbon stars are identified from multiple line indices measured from the stellar spectra. Combining the CN bands in the red end with ctwo and other lines, we are able to identify the carbon stars. Moreover, we also classify the carbon stars into spectral sub-types of ch, CR, and cn. These sub-types approximately show distinct features in the multi-dimensional line indices, implying that in the future we can use them to identify carbon stars from larger spectroscopic datasets. Meanwhile, from the line indices space, while the cn stars are clearly separated from the others, we find no clear separation between CR and ch sub-types. The CR and ch stars seem to smoothly transition from one to another. This may hint that the CR and ch stars may not be different in their origins but look different in their spectra because of different metallicity. Due to the relatively low spectral resolution and lower signal-to-noise ratio, the ratio of $^{12}$C/$^{13}$C is not measured and thus the cj stars are not identified.
Stellar systems composed of single, double, triple or high-order systems are rightfully regarded as the fundamental building blocks of the Milky Way. Binary stars play an important role in formation and evolution of the Galaxy. Through comparing the radial velocity variations from multi-epoch observations, we analyze the binary fraction of dwarf stars observed with the LAMOST. Effects of different model assumptions such as orbital period distributions on the estimate of binary fractions, are investigated. The results based on log-normal distribution of orbital periods reproduce the previous complete analyses better than the power-law distribution. We find that the binary fraction increases with $T_{rm eff}$ and decreases with [Fe/H]. We first investigate the relation between $alpha$-elements and binary fraction in such a large sample as the LAMOST. The old stars with high [$alpha$/Fe] dominate higher binary fraction than young stars with low [$alpha$/Fe]. At the same mass, former forming stars possess a higher binary fraction than newly forming ones, which may be related with the evolution of the Galaxy.
LAMOST DR5 released more than 200,000 low resolution spectra of early-type stars with S/N>50. Searching for metallic-line (Am) stars in such a large database and study of their statistical properties are presented in this paper. Six machine learning algorithms were experimented with using known Am spectra, and both the empirical criteria method(Hou et al. 2015) and the MKCLASS package(Gray et al. 2016) were also investigated. Comparing their performance, the random forest (RF) algorithm won, not only because RF has high successful rate but also it can derives and ranks features. Then the RF was applied to the early type stars of DR5, and 15,269 Am candidates were picked out. Manual identification was conducted based on the spectral features derived from the RF algorithm and verified by experts. After manual identification, 9,372 Am stars and 1,131 Ap candidates were compiled into a catalog. Statistical studies were conducted including temperature distribution, space distribution, and infrared photometry. The spectral types of Am stars are mainly between F0 and A4 with a peak around A7, which is similar to previous works. With the Gaia distances, we calculated the vertical height Z from the Galactic plane for each Am star. The distribution of Z suggests that the incidence rate of Am stars shows a descending gradient with increasing jZj. On the other hand, Am stars do not show a noteworthy pattern in the infrared band. As wavelength gets longer, the infrared excess of Am stars decreases, until little or no excess in W1 and W2 bands.
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