AI 中文总结
研究针对银河系绘图仪中红巨星，利用预先计算的偏离系数网格生成NLTE光谱，训练神经网络模拟器拟合APOGEE光谱，得出铝、锰和钛有较强NLTE效应，提供了相关拟合结果目录及校正丰度。
AI 中文摘要
大多数光谱调查在恒星光谱建模时假设局部热力学平衡（LTE）。对于像SDSS-V的银河系绘图仪调查在其银河系起源计划中所针对的红巨星这样的发光恒星，这一假设开始失效。在这项工作中，我们从红外APOGEE光谱中给出了银河系绘图仪DR19中360,000颗红巨星的非局部热力学平衡（NLTE）丰度。我们使用预先计算的钠、镁、硅、铝、钙、钛、锰和镍的偏离系数网格生成NLTE光谱。为了大规模拟合APOGEE光谱，我们训练神经网络模拟器（NNEs）来合成LTE和NLTE H波段光谱。在验证NNEs准确后，我们用与训练数据参数范围相同的ASPCAP结果拟合APOGEE光谱。我们发现铝、锰和钛的NLTE效应约为0.1 dex，硅和镍的效应较小。我们提供了LTE和NLTE拟合结果的目录，以及使用多项式拟合校正的NLTE校正后的ASPCAP丰度。
英文摘要
The majority of spectroscopic surveys assume local thermodynamic equilibrium (LTE) during the modeling of stellar spectra. This assumption begins to break down for luminous stars, like the red giants targeted by SDSS-V's Milky Way Mapper Survey in its Galactic Genesis program. In this work, we present non-LTE (NLTE) abundances for 360,000 red giant stars in Milky Way Mapper DR19, from infrared APOGEE spectra. We generate NLTE spectra using precomputed departure coefficient grids for Na, Mg, Si, Al, Ca, Ti, Mn, and Ni. To fit APOGEE spectra at scale, we train neural network emulators (NNEs) to synthesize LTE and NLTE H-band spectra. After verifying that the NNEs are accurate, we fit the APOGEE spectra with ASPCAP results that fall within the same parameter range as the training data. We find strong NLTE effects on the order of 0.1\,dex for Al, Mn, and Ti, and smaller effects for Si and Ni. We provide a catalog of the results of our LTE and NLTE fits, as well as NLTE-corrected ASPCAP abundances using a polynomial fit correction.
Comments20 pages, 11 figures, 4 tables. To be submitted to Open Journal of Astrophysics
