主要研究了一种新的基于ELM算法的中低分辨光谱的恒星Mg元素丰度估计方法。 大科学工程郭守敬望远镜(LAMOST)为我们提供了海量的中低分辨率的光谱, 确定这些光谱的Mg元素丰度将有助于我们深入了解银河系的形成历史和演化过程。 目前从中低分辨率光谱中确定Mg元素丰度的方法主要是模板匹配法, 但该方法算法复杂, 优化参数较为困难且对噪声敏感, 因此有必要研究新的方法。 实验结果显示, ELM算法对MILES光谱的Mg丰度的估计的精度为0.009 9(0.15)dex, 而对信噪比大于50的LAMOST光谱的精度为0.002 7(0.11)dex。 通过与其他算法进行对比, 证实ELM算法是一种能精确估计中低分辨率光谱的Mg元素丰度的算法, 能够应用于LAMOST后期的光谱数据中。

In this paper, we mainly study a new method for estimating the Mg abundance of stars from the medium and low resolution spectra based on ELM algorithm. LAMOST provides us with a massive low-resolution spectrum, and determining the abundance of Mg elements in these spectra will help us understand the history and evolution of the Milky Way. At present, the traditional method of determining the abundance of Mg element from medium and low resolution spectra is the template matching method. However, this method is difficult to optimize parameters and is sensitive to noise. Therefore, it is necessary to study new methods to estimate the Mg abundance. The experiment show that ELM algorithm is agood alternative to traditional method. The accuracy of ELM algorithm on MILES spectra is 0.009 9 (0.15) dex, while on the LAMOST spectra with signal-to-noise ratios larger than 50 it is 0.002 7 (0.11) dex. A comparison of ELM with other four algorithms shows that ELM algorithm can accurately estimate the abundance of Mg elements from low resolution spectra and can be applied to the LAMOST spectra.