标题： 卡农2：用于详细化学丰度分析的驱动数据的恒星光谱模型 显示英文标题

标题： The Cannon 2: A data-driven model of stellar spectra for detailed chemical abundance analyses

摘要： 我们已经证明，数据驱动模型对于从光谱中推断恒星的物理属性（标签；Teff, logg, [M/H]）是有效的，即使信噪比很低。 在这里，我们探讨当标签空间的维度很大时（Teff, logg 和 15 种丰度：C, N, O, Na, Mg, Al, Si, S, K, Ca, Ti, V, Mn, Fe, Ni）并且模型对丰度和参数变化的响应是非线性的情况下，是否可能实现这一点。 我们采用压缩感知的思想，在保持模型自由度的同时限制整体模型复杂性。 该模型使用一组 12,681 颗红巨星的高信噪比光谱观测数据以及来自 APOGEE 调查的恒星参数和丰度进行训练。 我们发现可以成功训练并使用一个包含 17 个恒星标签的模型。 验证显示，该模型在推断所有 17 个标签方面表现良好（典型丰度精度为 0.04 dex），即使我们通过丢弃约 50% 的观测时间来降低信噪比。 模型依赖关系是有意义的：相对于丰度的光谱导数与已知的原子线相关，并且我们识别出之前未知的原子线所属的元素。 我们恢复了球状星团恒星丰度标签中的（反）相关性，这与文献一致。 然而我们发现球状星团丰度的内在扩散比之前报告的小 3--4 倍。 我们为 87,563 颗红巨星提供了 17 个标签及其相关误差，并提供了开源代码，以便将这项工作扩展到其他光谱调查。 显示英文摘要

摘要： We have shown that data-driven models are effective for inferring physical attributes of stars (labels; Teff, logg, [M/H]) from spectra, even when the signal-to-noise ratio is low. Here we explore whether this is possible when the dimensionality of the label space is large (Teff, logg, and 15 abundances: C, N, O, Na, Mg, Al, Si, S, K, Ca, Ti, V, Mn, Fe, Ni) and the model is non-linear in its response to abundance and parameter changes. We adopt ideas from compressed sensing to limit overall model complexity while retaining model freedom. The model is trained with a set of 12,681 red-giant stars with high signal-to-noise spectroscopic observations and stellar parameters and abundances taken from the APOGEE Survey. We find that we can successfully train and use a model with 17 stellar labels. Validation shows that the model does a good job of inferring all 17 labels (typical abundance precision is 0.04 dex), even when we degrade the signal-to-noise by discarding ~50% of the observing time. The model dependencies make sense: the spectral derivatives with respect to abundances correlate with known atomic lines, and we identify elements belonging to atomic lines that were previously unknown. We recover (anti-)correlations in abundance labels for globular cluster stars, consistent with the literature. However we find the intrinsic spread in globular cluster abundances is 3--4 times smaller than previously reported. We deliver 17 labels with associated errors for 87,563 red giant stars, as well as open-source code to extend this work to other spectroscopic surveys.