Discovery of 2716 hot emission-line stars from LAMOST DR5

We present a catalog of 3339 hot emission-line stars (ELSs) identified from 451 695 O, B and A type spectra, provided by LAMOST Data Release 5 (DR5). We developed an automated Python routine that identified 5437 spectra having a peak between 6561 and 6568 Å. False detections and bad spectra were rem...

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Bibliographic Details
Published in:Research in astronomy and astrophysics 2021-12, Vol.21 (11), p.288-179
Main Authors: Shridharan, Baskaran, Mathew, Blesson, Nidhi, Sabu, Anusha, Ravikumar, Arun, Roy, Kartha, Sreeja S., Kumar, Yerra Bharat
Format: Article
Language:English
Subjects:
astronomical databases: catalogs
B stars
Emission analysis
Emission spectra
Line spectra
methods: data analysis
Spectral emissivity
Stars
stars: early-type
techniques: photometric
Wavelengths
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Summary:We present a catalog of 3339 hot emission-line stars (ELSs) identified from 451 695 O, B and A type spectra, provided by LAMOST Data Release 5 (DR5). We developed an automated Python routine that identified 5437 spectra having a peak between 6561 and 6568 Å. False detections and bad spectra were removed, leaving 4138 good emission-line spectra of 3339 unique ELSs. We re-estimated the spectral types of 3307 spectra as the LAMOST Stellar Parameter Pipeline (LASP) did not provide accurate spectral types for these emission-line spectra. As Herbig Ae/Be stars exhibit higher excess in near-infrared and mid-infrared wavelengths than classical Ae/Be stars, we relied on 2MASS and WISE photometry to distinguish them. Finally, we report 1089 classical Be, 233 classical Ae and 56 Herbig Ae/Be stars identified from LAMOST DR5. In addition, 928 B[em]/A[em] stars and 240 CAe/CBe potential candidates are identified. From our sample of 3339 hot ELSs, 2716 ELSs identified in this work do not have any record in the SIMBAD database and they can be considered as new detections. Identification of such a large homogeneous set of emission-line spectra will help the community study the emission phenomenon in detail without worrying about the inherent biases when compiling from various sources.
ISSN:1674-4527
DOI:10.1088/1674-4527/21/11/288