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We report the first systematic study to identify and characterize a sample of classical Ae stars in the Galaxy. The spectra of these stars were retrieved from the A-star catalog using the Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST) survey. We identified the emission-line stars in this catalog from which 159 are confirmed as classical Ae stars. This increases the sample of known classical Ae stars by about nine times from the previously identified 21 stars. The evolutionary phase of classical Ae stars in this study is confirmed from the relatively small mid- and far-infrared excess and from their location in the optical color-magnitude diagram. We estimated the spectral type using MILES spectral templates and identified Classical Ae stars beyond A3, for the first time. The prominent emission lines in the spectra within the wavelength range 3700 -- 9000 {AA} are identified and compared with the features present in classical Be stars. The H{alpha} emission strength of the stars in our sample show a steady decrease from late-B type to Ae stars, suggesting that the disc size may be dependent on the spectral type. Interestingly, we noticed emission lines of Fe{sc ii}, O{sc i} and Paschen series in the spectrum of some classical Ae stars. These lines are supposed to fade out by late B-type and should not be present in Ae stars. Further studies, including spectra with better resolution, is needed to correlate these results with the rotation rates of classical Ae stars.
Combing Gaia DR2 with LAMOST DR5, we spectroscopically identified 924 hot subdwarf stars, among which 32 stars exhibit strong double-lined composite spectra. We measured the effective temperature $T_{rm eff}$, surface gravity $log,g$, helium abundanc
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
Our study aims to recognize M-type stars which are classified as UNKNOWN due to bad quality in Large sky Area Multi-Object fibre Spectroscopic Telescope (LAMOST) DR5 V1. A binary nonlinear hashing algorithm based on Multi-Layer Pseudo Inverse Learnin
We present the determination of stellar parameters and individual elemental abundances for 6 million stars from $sim$8 million low-resolution ($Rsim1800$) spectra from LAMOST DR5. This is based on a modeling approach that we dub $The$ $Data$--$Driven
We report on searching for Classical B-type emission-line (CBe) stars from the first data release (DR1) of the Large Sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST; also named the Guoshoujing Telescope). A total of 192 (12 known CBes) ob