用改进的最小二乘反卷积法对光谱数据进行去噪
Denoising spectroscopic data by means of the improved Least-Squares Deconvolution method
摘要：
MOST，CoRoT和开普勒太空任务导致发现了大量有趣的，在某些情况下是独特的物体，其中包括脉动恒星，恒星托管系外行星，双星等。这些数据缺乏任何光谱信息，我们仍然需要地面光谱和/或多色光度跟踪，为一个可靠的解释。大多数观测到的恒星都很模糊，而且光谱数据需要很高的信噪比，这意味着需要使用大型望远镜，而大型望远镜的使用是有限的。在本文中，我们寻找一种替代方案，并旨在开发一种技术，允许去噪原来的低S/N光谱数据，使小望远镜观测微弱的目标成为可能和有效的。我们提出了一个推广的原始最小二乘反卷积（LSD）方法，通过实施多组分平均配置文件和线强度校正算法。该方法成功地测试了织女星和开普勒恒星，KIC 04749989的高分辨率光谱。对两颗脉动星20 Cvn和HD 189631的应用表明，该技术也适用于内禀变星：由LSD模型谱对这两颗天体进行的频率分析和模式识别结果与文献中的结果符合得很好。根据原始数据的信噪比和恒星的光谱特性，LSD模型光谱的信噪比增益通常在5到15倍之间。恢复的LSD模型光谱包含了原始光谱中存在的线轮廓变化的所有信息。该方法适用于高分辨率（>30 000）和低分辨率（<30 000）光谱，尽管可以从后者提取的信息受到分辨率本身的限制。
英文摘要：
The MOST, CoRoT, and Kepler space missions led to the discovery of a large number of intriguing, and in some cases unique, objects among which are pulsating stars, stars hosting exoplanets, binaries, etc. Although the space missions deliver photometric data of unprecedented quality, these data are lacking any spectral information and we are still in need of ground-based spectroscopic and/or multicolour photometric follow-up observations for a solid interpretation. Both faintness of most of the observed stars and the required high S/N of spectroscopic data imply the need of using large telescopes, access to which is limited. In this paper, we look for an alternative, and aim for the development of a technique allowing to denoise the originally low S/N spectroscopic data, making observations of faint targets with small telescopes possible and effective. We present a generalization of the original Least-Squares Deconvolution (LSD) method by implementing a multicomponent average profile and a line strengths correction algorithm. The method was successfully tested on the high resolution spectra of Vega and a Kepler star, KIC04749989. Application to the two pulsating stars, 20 Cvn and HD189631, showed that the technique is also applicable to intrinsically variable stars: the results of frequency analysis and mode identification from the LSD model spectra for both objects are in good agreement with the findings from literature. Depending on S/N of the original data and spectral characteristics of a star, the gain in S/N in the LSD model spectrum typically ranges from 5 to 15 times. The restored LSD model spectra contain all the information on line profile variations present in the original spectra. The method is applicable to both high- (>30 000) and low- (<30 000) resolution spectra, though the information that can be extracted from the latter is limited by the resolving power itself.
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