Affiliation:
1. CAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences , Beijing 100101 , People’s Republic of China
2. School of Astronomy and Space Science, University of Chinese Academy of Sciences , Beijing 100049 , People’s Republic of China
Abstract
ABSTRACT
Sky subtraction is a crucial step in the data reduction process for LAMOST, including dark, bright, and grey nights. During the pilot survey, on bright nights, atmospheric scattering of moonlight can introduce gradients in the sky background. In observations during bright moonlit nights, the sky component is significant, and sometimes, variations in colour can be observed in the sky spectra. This phenomenon is not universally present during observations on bright moonlit nights. Taking this into consideration, this paper proposes a weighted trend-surface method to reconstruct the sky component within the science target fibre, aiming to achieve the subtraction of the sky component. We constructed a sky model using a trend surface, utilizing data from all sky fibre spectra on the same spectrograph to predict the sky component for each fibre spectrum. Subsequently, the reconstructed sky spectrum data were compared with the actually observed sky spectrum data and the ‘super sky’ from LAMOST’s pipeline. The results indicate that our method is closer to the observed real sky spectrum than the ‘super sky’, showing smaller residuals and variance, with an average closer to zero. This method serves as a viable solution, particularly when dealing with colour variations observed during bright moonlit nights.
Funder
National Natural Science Foundation of China
National Development and Reform Commission
Publisher
Oxford University Press (OUP)
Subject
Space and Planetary Science,Astronomy and Astrophysics