SDSS-IV MaStar: Data-driven Parameter Derivation for the MaStar Stellar Library
SDSS-IV MaStar: Data-driven Parameter Derivation for the MaStar Stellar Library
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DOI：
10.3847/1538-3881/ac3ca7
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发表时间：
2021-12
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通讯作者：
J. Imig;J. Holtzman;R. Yan;D. Lazarz;Yanping Chen;L. Hill;D. Thomas;C. Maraston;M. Prescott;G. Stringfellow;D. Bizyaev;R. Beaton;N. Drory
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作者：
J. Imig;J. Holtzman;R. Yan;D. Lazarz;Yanping Chen;L. Hill;D. Thomas;C. Maraston;M. Prescott;G. Stringfellow;D. Bizyaev;R. Beaton;N. Drory
阿帕奇点天文台(MANGA)恒星图书馆(MaStar)的绘制附近星系图是一大批高质量的经验恒星光谱，旨在涵盖所有光谱类型，非常适合用于漫画调查中观察到的星系的恒星群分析。该资料库包含24,130颗独特恒星的59,266个光谱，光谱分辨率为R∼1800，覆盖的波长范围为3,622-10,354？在这项工作中，我们推导了库中每个光谱的五个物理参数：有效温度(Tef)、表面重力(Logg)、金属丰度([Fe/H])、微湍流速度(log(VMicro))和α元素丰度([α/Fe])。这些参数是通过使用神经网络模型的灵活的数据驱动算法得出的。我们使用在阿帕奇点星系演化实验(APOEE)中也观察到的1675个MaStar目标的子集来训练神经网络，采用独立推导的远地点恒星参数和化学丰度管道参数作为这个参考集。对于远地点训练集(7000≤T≤30000 K)不能很好代表参数空间的区域，我们补充了理论模型光谱。我们给出了我们得到的参数，并对不确定性进行了分析，并与文献中的其他分析进行了比较。
The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) Stellar Library (MaStar) is a large collection of high-quality empirical stellar spectra designed to cover all spectral types and ideal for use in the stellar population analysis of galaxies observed in the MaNGA survey. The library contains 59,266 spectra of 24,130 unique stars with spectral resolution R ∼ 1800 and covering a wavelength range of 3622–10,354 Å. In this work, we derive five physical parameters for each spectrum in the library: effective temperature (T eff), surface gravity ( logg ), metallicity ([Fe/H]), microturbulent velocity ( log(vmicro) ), and alpha-element abundance ([α/Fe]). These parameters are derived with a flexible data-driven algorithm that uses a neural network model. We train a neural network using the subset of 1675 MaStar targets that have also been observed in the Apache Point Observatory Galactic Evolution Experiment (APOGEE), adopting the independently-derived APOGEE Stellar Parameter and Chemical Abundance Pipeline parameters for this reference set. For the regions of parameter space not well represented by the APOGEE training set (7000 ≤ T ≤ 30,000 K), we supplement with theoretical model spectra. We present our derived parameters along with an analysis of the uncertainties and comparisons to other analyses from the literature.