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arXiv 2109.09327astro-ph.SRastro-ph.GAastro-ph.IM
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用MUSE积分场摄谱仪对单个恒星进行可靠的恒星丰度测量

Reliable stellar abundances of individual stars with the MUSE integral-field spectrograph

Zixian Wang, Michael R. Hayden, Sanjib Sharma, Maosheng Xiang, Yuan-Sen Ting, Joss Bland-Hawthorn, Boquan Chen

备注：
20 pages, 17 figures, revised version, accepted by MNRAS
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摘要：

我们提出了一种新的方法来推导恒星标签的恒星观测MUSE领域利用数据驱动的机器学习方法。利用LAMOST和MUSE仪器的可比光谱特性（分辨率，波长覆盖范围），我们采用数据驱动的佩恩（DD-佩恩）模型用于LAMOST观测，并将其应用于MUSE领域的恒星观测。值得注意的是，尽管仪器的差异，根据27个LAMOST-MUSE共同恒星的交叉验证，我们能够确定恒星标签的精度优于75 K的$T_{\rm eff}$，0.15 dex的$\log g$，和0.1 dex的丰度[Fe/H]，[Mg/Fe]，[Si/Fe]，[Ti/Fe]，[C/Fe]，在3800< $T_{\rm eff}$ <7000 K，-1.5<[Fe/H]<0.5 dex的参数范围内，当前MUSE观测的[Ni/Fe]和[Cr/Fe]。自六年前首次投入使用以来，迄今为止，MUSE已被用于瞄准南部天空的13，000个领域，并且它在研究密集恒星领域（如球状星团或银河系凸起）的能力方面是独一无二的。我们的方法将使自动测定恒星参数的所有恒星在这些领域。此外，它还为其他光谱仪收集的数据的应用打开了大门，这些光谱仪具有类似于LAMOST的分辨率。通过即将推出的BlueMUSE和MAVIS，我们将获得更高精度的全新化学丰度范围，特别是关键的s过程元素，如[Y/Fe]和[Ba/Fe]，为恒星目标提供关键的年龄诊断。

英文摘要：

We present a novel approach to deriving stellar labels for stars observed in MUSE fields making use of data-driven machine learning methods. Taking advantage of the comparable spectral properties (resolution, wavelength coverage) of the LAMOST and MUSE instruments, we adopt the Data-Driven Payne (DD-Payne) model used on LAMOST observations and apply it to stars observed in MUSE fields. Remarkably, in spite of instrumental differences, according to the cross-validation of 27 LAMOST-MUSE common stars, we are able to determine stellar labels with precision better than 75K in $T_{\rm eff}$, 0.15 dex in $\log g$, and 0.1 dex in abundances of [Fe/H], [Mg/Fe], [Si/Fe], [Ti/Fe], [C/Fe], [Ni/Fe] and [Cr/Fe] for current MUSE observations over a parameter range of 3800<$T_{\rm eff}$<7000 K, -1.5<[Fe/H]<0.5 dex. To date, MUSE has been used to target 13,000 fields across the southern sky since it was first commissioned six years ago and it is unique in its ability to study dense star fields such as globular clusters or the Milky Way bulge. Our method will enable the automated determination of stellar parameters for all stars in these fields. Additionally, it opens the door for applications to data collected by other spectrographs having resolution similar to LAMOST. With the upcoming BlueMUSE and MAVIS, we will gain access to a whole new range of chemical abundances with higher precision, especially critical s-process elements such as [Y/Fe] and [Ba/Fe] that provide key age diagnostics for stellar targets.

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