Sky subtraction of LAMOST at bright night

Author:

Han Bochong12,Song Yihan12,Zhao Yongheng12

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

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3