2018/02/19 by B-Q Chen, B. -Q. Chen, X. -W. Liu +13 · 23 citations
Engineering · Physics and Astronomy · #Astronomical Observations and Instrumentation #Astronomy #Astrophysics #Astrophysics and Star Formation Studies #Computer science #Function (biology) #LAMOST #Machine learning #Milky Way #Physics #Selection (genetic algorithm) #Spectral line #Stars #Stellar, planetary, and galactic studies #astro-ph.GA #astro-ph.SR
paper · pdf · doi:10.1093/mnras/sty454
published in Monthly Notices of the Royal Astronomical Society 476(3), 3278-3289 (Oxford University Press) · 13 pages, 12 figures, accepted for publication in MNRAS
arxiv created 2018/02/19 · openalex publication_date 2018/02/21 · openalex created_date 2018/03/06 · arxiv updated 2018/03/14 · openalex updated_date 2026/08/05
We present a detailed analysis of the selection function of the LAMOST Spectroscopic Survey of the Galactic Anti-centre (LSS-GAC). LSS-GAC was designed to obtain low-resolution optical spectra for a sample of more than 3 million stars in the Galactic anti-centre. The second release of value-added catalogues of the LSS-GAC (LSS-GAC DR2) contains stellar parameters, including radial velocity, atmospheric parameters, elemental abundances, and absolute magnitudes deduced from 1.8 million spectra of 1.4 million unique stars targeted by the LSS-GAC between 2011 and 2014. For many studies using this data base, such as those investigating the chemodynamical structure of the Milky Way, a detailed understanding of the selection function of the survey is indispensable. In this paper, we describe how the selection function of the LSS-GAC can be evaluated to sufficient detail and provide selection function corrections for all spectroscopic measurements with reliable parameters released in LSS-GAC DR2. The results, to be released as new entries in the LSS-GAC value-added catalogues, can be used to correct the selection effects of the catalogue for scientific studies of various purposes.