LAMOST一维光谱提取算法的分析与比较
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1.中国科学院大学工程科学学院北京100049;2.中国科学院国家天文台光学天文重点实验室北京100101;3.中国科学院国家天文台空间天文与技术重点实验室北京100101;4.北京师范大学人工智能学院北京100875;

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国家自然科学基金项目(U1531242、11673036)资助


Analysis and Comparison of Spectral Extraction Algorithms in LAMOST
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1. School of Engineering Science, University of Chinese Academy of Sciences, Beijing 100049;2. Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101;3. Key Laboratory of Space Astronomy and Technology, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101;4. School of Artificial Intelligence, Beijing Normal University, Beijing 100875;

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    摘要:

    针对LAMOST (Large Sky Area Multi-Object Fiber Spectroscopic Telescope) 2维光谱图像数据, 对6种抽谱算法进行了分析与比较. 比较的算法包括孔径法、轮廓拟合法、直接反卷积方法、基于Tikhonov正则化的反卷积抽谱算法、基于自适应Landweber迭代的反卷积抽谱算法以及基于Richardson-Lucy迭代的反卷积抽谱算法. 通过实验对这些算法在信噪比和分辨率两个方面进行了比较, 发现基于Tikhonov正则化的反卷积抽谱算法、基于自适应Landweber迭代的反卷积抽谱算法以及基于Richardson-Lucy迭代的反卷积抽谱算法是6种算法中最为可靠的3种抽谱算法. 最后, 对今后的工作进行了展望.

    Abstract:

    In this paper, six spectral extraction algorithms are analyzed and compared in LAMOST (Large Sky Area Multi-Object Fiber Spectroscopic Telescope) two-dimensional spectral images. The compared algorithms include the aperture extracion method, profile-fitting method, direct deconvolution method, Tikhonov deconvolution method, deconvolution extraction based on adaptive Landweber iteration method, and deconvolution extraction based on Richardson-Lucy iteration method. The six algorithms are compared in the aspects of signal-to-noise ratio (SNR) and resolution. It can be found that the Tikhonov deconvolution method, deconvolution extraction based on adaptive Landweber iteration method, and deconvolution extraction based on Richardson-Lucy iteration method are the most reliable algorithms among them. Finally, the future work is proposed.

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李敏,李广伟,吕科,段福庆,哈斯铁尔·哈尔肯,赵永恒. LAMOST一维光谱提取算法的分析与比较[J].天文学报,2020,61(3):27. LI Min, LI Guang-wei, LV Ke, DUAN Fu-qing, HASITIEER Haerken, ZHAO Yong-heng. Analysis and Comparison of Spectral Extraction Algorithms in LAMOST[J]. Acta Astronomica Sinica,2020,61(3):27.

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  • 收稿日期:2019-11-21
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  • 在线发布日期: 2020-06-02
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