利用LAMOST光谱和Kepler星震学数据搜寻α超丰的年轻恒星

项目背景: α超丰的年轻恒星是丰度大于0.13 dex 但年龄小于6Gyr的恒星。这类恒星的发现挑战了传统的恒星演化理论，对其深入研究有助于我们深入理解恒星形成和演化过程，为银河系的演化理论提供观测限制。目前该类恒星样本极少，限制了对其深入研究，有必要利用LAMOST数据系统开展这类恒星的搜寻证认工作。.研究内容：(1) LAMOST恒星的α丰度估计方法研究；(2) 基于星震学数据的红巨星年龄的估计方法研究；(3) α超丰的年轻恒星的搜寻与证认。.项目特色：(1) 首次使用LAMOST光谱结合Kepler星震学数据系统搜寻α超丰的年轻恒星，将使样本数量提高一个量级；(2) 使用全新的算法估计红巨星的年龄和质量；(3) 全面系统的研究LAMOST光谱的α丰度估计方法。.项目基础：已完成LAMOST恒星的α丰度估计。

Context: The young α-rich stars are the stars whose ages are younger than 6 Gyr but the α abundance are larger than 0.13 dex. The recent discovery of α-rich young stars has challenged the standard theory of stellar evolution. The born place, chemical enrichment process and the distribution of these stars are not well understood. The study of these stars provides new insight into the stellar mixing and evolution. However, they are only handful of stars known so far. Thus, it is necessary to embark a systematic survey to search for such stars and we found LAMOST database with millions of giant stars spectra would be an appropriate database to initiate our study..Contents: (1) Develop new methods of estimating the stellar α abundance; (2) Develop new methods of estimating the ages and mass of red giants; (3) Search for and identify the α-rich young stars..Merits: (1) This is the first project to search for the α-rich young stars with the LAMOST spectra and Kepler asteroseismic data, which could increase the number of α rich young stars by one order; (2) The new algorithms of estimating the ages of red giants will be used; (3) The new methods of estimating the α abundance of stars from LAMOST spectra will be provided..Foundation: Have tested our Extreme Learning Method to a subsample of LAMOST spectra to derive alpha abundances and they are in good agreement with the literature values.