基于LASSO算法的恒星α元素丰度估计方法研究  

Stellar Alpha Element Abundance Estimation Using LASSO Algorithm

作　　者：卜育德[1] 潘景昌[2] 王春雨[3] 陈修梅[4] BU Yu-de PAN Jing-chang WANG Chun-yu CHEN Xiu-mei(School of Mathematics and Statistics, Shandong University, Weihai, Weihai 264209, China School of Information Engineering, Shandong University, Weihai, Weihai 264209, China School of Statistics, Renmin University of China, Beijing 100872, China School of Information Engineering, Shandong Youth University of Political Science, Ji＇nan 250103, China)

机构地区：[1]山东大学(威海)数学与统计学院,山东威海264209 [2]山东大学(威海)信息工程学院,山东威海264209 [3]中国人民大学统计学院,北京100872 [4]山东青年政治学院信息工程学院,山东济南250103

出　　处：《光谱学与光谱分析》2017年第1期278-282,共5页Spectroscopy and Spectral Analysis

基　　金：国家自然科学基金项目(U1431102;11603012);山东省青年基金项目(ZR2015AQ011);山东大学(威海)青年学者未来计划资助

摘　　要：主要研究了一种新的基于LASSO算法的恒星α元素丰度估计方法。海量恒星的α元素(O,Mg,Si,Ca和Ti)丰度信息将有助于我们了解银河系的演化进程。但目前从中低分辨率光谱中确定α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,LASSO算法对ELODIE光谱的α丰度的估计精度为0.003(0.078)dex。为验证光谱分辨率变化对LASSO算法结果的影响,我们首先用ELODIE光谱通过高斯卷积得到了分辨率为42 000,21 000,10 500,4 200和2 100的光谱,然后使用LASSO算法估计α元素丰度,精度分别为0.003 3(0.078)dex,-0.05(0.059)dex,-0.007(0.060)dex,0.008 0(0.069)dex和-0.004 5(0.067)dex。上述结果证明LASSO算法对分辨率变化不敏感。为验证LASSO算法对信噪比变化的鲁棒性,使用ELODIE光谱分别构造了信噪比为30,25,20,15和5的光谱。LASSO算法在上述数据集上的精度分别为-0.002(0.076)dex,-0.09(0.073)dex,0.003 6(0.075)dex,0.007 6(0.078)dex和-0.009(0.08)dex,因而LASSO算法对信噪比变化不敏感。因此,LASSO算法适用于低分辨率低信噪比的LAMOST和SDSS光谱。LASSO算法在SDSS光谱上的估计精度为0.003 7(0.097)dex,而在球状星团和疏散星团成员星上的结果显示LASSO算法给出的丰度与文献给出α丰度值误差在1σ以内。因此,LASSO算法能够用于估计恒星的α元素丰度。In this paper,a new method based on LASSO algorithm is studied for the estimation of stellar alpha element abundance.The information of alpha elements（O,Mg,Ca,Si,and Ti）of massive stars will help us to better understand the evolution of the galaxy.Presently the main method of determining the alpha element abundances from the low resolution spectra is the template matching method.However,it is difficult for us to optimize the algorithm parameters and the algorithm is sensitive to the noise.Thus,it is necessary to study the new method to determine the abundance.The experimental results show that the accuracy of LASSO algorithm on ELODIE spectra is 0.003（0.078）dex.To explore the impact of the spectral resolution variation,we use ELODIE spectra to generate the spectral data sets with following resolutions：42 000,21 000,10 500,4 200 and 2 100 by using the Gaussian convolution.The results of the LASSO algorithm on these data sets are 0.003 3（0.078）dex,-0.05（0.059）dex,-0.007（0.069）dex and-0.004 5（0.067）dex,respectively.These results show that the LASSO algorithm is not sensitive to the change of the resolution.In order to verify the robustness of LASSO algorithm against the change of SNRs,we use ELODIE to generate the spectral data sets with following SNRs：30,25,20,15 and 5.The results of LASSO algorithm on the above data sets are：-0.002（0.076）dex,-0.090（0.073）dex,0.003 6（0.075）dex,0.007 6（0.078）dex and-0.009（0.080）dex,respectively.Thus,LASSO algorithm is not sensitive to the change of SNR.Therefore,the LASSO algorithm is suitable for low resolution and low SNR spectra such as LAMOST and SDSS spectra.The accuracy of Lasso algorithm on the SDSS spectra is 0.003 7（0.097）dex,and the results of LASSO on globular and open clusters show good agreement with literature values（within 1σ）.Therefore,the LASSO algorithm can be used to estimate the alpha element abundances of stars.

关 键 词：LASSO α元素丰度 线性回归 特征提取 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置]