Determining Stellar Elemental Abundances from DESI Spectra with the Data-driven Payne

Meng Zhang, Maosheng Xiang, Yuan-Sen Ting, Jiahui Wang, Haining Li, Hu Zou, Jundan Nie, Lanya Mou, Tianmin Wu, Yaqian Wu and Jifeng Liu
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Abstract

Stellar abundances for a large number of stars provide key information for the study of Galactic formation history. Large spectroscopic surveys such as the Dark Energy Spectroscopic Instrument (DESI) and LAMOST take median-to-low-resolution (R ≲ 5000) spectra in the full optical wavelength range for millions of stars. However, the line-blending effect in these spectra causes great challenges for elemental abundance determination. Here we employ DD-Payne, a data-driven method regularized by differential spectra from stellar physical models, to the DESI early data release spectra for stellar abundance determination. Our implementation delivers 15 labels, including effective temperature Teff, surface gravity , microturbulence velocity vmic, and the abundances for 12 individual elements, namely C, N, O, Mg, Al, Si, Ca, Ti, Cr, Mn, Fe, and Ni. Given a spectral signal-to-noise ratio of 100 per pixel, the internal precisions of the label estimates are about 20 K for Teff, 0.05 dex for , and 0.05 dex for most elemental abundances. These results agree with the theoretical limits from the Crámer–Rao bound calculation within a factor of 2. The majority of the accreted halo stars contributed by the Gaia–Enceladus–Sausage are discernible from the disk and in situ halo populations in the resultant [Mg/Fe]–[Fe/H] and [Al/Fe]–[Fe/H] abundance spaces. We also provide distance and orbital parameters for the sample stars, which spread over a distance out to ∼100 kpc. The DESI sample has a significantly higher fraction of distant (or metal-poor) stars than the other existing spectroscopic surveys, making it a powerful data set for studying the Galactic outskirts. The catalog is publicly available.
利用数据驱动佩恩从 DESI 光谱确定恒星元素丰度
大量恒星的丰度为研究银河系的形成历史提供了关键信息。暗能量光谱仪(DESI)和 LAMOST 等大型光谱巡天在全光学波长范围内拍摄了数百万颗恒星的中低分辨率(R ≲ 5000)光谱。然而,这些光谱中的线混合效应给元素丰度测定带来了巨大挑战。在这里,我们采用 DD-Payne(一种由恒星物理模型差分光谱正则化的数据驱动方法)对 DESI 早期发布的数据光谱进行恒星丰度测定。我们的实施提供了 15 个标签,包括有效温度 Teff、表面引力、微扰动速度 vmic 以及 12 种元素的丰度,即 C、N、O、Mg、Al、Si、Ca、Ti、Cr、Mn、Fe 和 Ni。在每个像素的光谱信噪比为 100 的情况下,标签估计值的内部精确度分别为:Teff 约为 20 K,Ⅳ为 0.05 dex,大多数元素丰度为 0.05 dex。这些结果与克拉默-拉奥约束计算的理论限值相吻合,误差不超过 2 倍。在所得到的[Mg/Fe]-[Fe/H]和[Al/Fe]-[Fe/H]丰度空间中,Gaia-Enceladus-Sausage 所贡献的大部分吸积晕星都可以从星盘和原地晕群中分辨出来。我们还提供了样本恒星的距离和轨道参数,这些恒星的距离最远可达 ∼ 100 kpc。与其他现有的光谱巡天相比,DESI样本中遥远(或贫金属)恒星的比例要高得多,这使它成为研究银河系外围的强大数据集。该星表是公开的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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