论文标题
凯克（Keck）的恒星特征与大炮一起雇用光谱
Stellar Characterization of Keck HIRES Spectra with The Cannon
论文作者
论文摘要
为了准确地解释外部行星的观察到的特性，有必要首先获得对宿主星特性的详细理解。但是，每星级分析恒星特性的物理模型在足够大的样本上可能会在计算上变得棘手。此外，这些模型受到可用光谱的波长覆盖范围的限制。 We combine previously derived spectral properties from the Spectroscopic Properties of Cool Stars (SPOCS) catalog (Brewer et al. 2016) with generative modeling using The Cannon to produce a model capable of deriving stellar parameters ($\log g$, $T_{\mathrm{eff}}$, and $v\sin i$) and 15 elemental abundances (C, N, O, Na, Mg，Al，Si，Ca，Ti，V，Cr，Mn，Fe，Ni和Y），用于使用Keck Obsvatory的高分辨率梯形梯形光谱仪（雇用）观察到的恒星光谱。我们证明了模型的高精度和精度，该模型仅需$ \ sim $ 3秒即可通过与SPOCS样本中的预先标记的光谱进行交叉验证来对每个恒星进行分类。我们训练有素的模型将连续范围的模板光谱作为其输入，可在https://github.com/malenarice/keckspec上公开获得。最后，我们使用在Keck 2004 2004年探测器升级之前获得的档案恒星光谱插入光谱并采用相同的建模方案来恢复477颗恒星的标签，这表明我们的插值模型可以成功预测具有（1）足够相似的系统和（2）与evavellength范围的不同光谱仪的恒星标签，这些模型与evavellength的范围相当（2）与peastres form copts post-toplaps coptsplage hanir coptsplage hanir coptsplage hanir forsyply coptsplage hanir for har incyplape。
To accurately interpret the observed properties of exoplanets, it is necessary to first obtain a detailed understanding of host star properties. However, physical models that analyze stellar properties on a per-star basis can become computationally intractable for sufficiently large samples. Furthermore, these models are limited by the wavelength coverage of available spectra. We combine previously derived spectral properties from the Spectroscopic Properties of Cool Stars (SPOCS) catalog (Brewer et al. 2016) with generative modeling using The Cannon to produce a model capable of deriving stellar parameters ($\log g$, $T_{\mathrm{eff}}$, and $v\sin i$) and 15 elemental abundances (C, N, O, Na, Mg, Al, Si, Ca, Ti, V, Cr, Mn, Fe, Ni, and Y) for stellar spectra observed with Keck Observatory's High Resolution Echelle Spectrometer (HIRES). We demonstrate the high accuracy and precision of our model, which takes just $\sim$3 seconds to classify each star, through cross-validation with pre-labeled spectra from the SPOCS sample. Our trained model, which takes continuum-normalized template spectra as its inputs, is publicly available at https://github.com/malenarice/keckspec. Finally, we interpolate our spectra and employ the same modeling scheme to recover labels for 477 stars using archival stellar spectra obtained prior to Keck's 2004 detector upgrade, demonstrating that our interpolated model can successfully predict stellar labels for different spectrographs that have (1) sufficiently similar systematics and (2) a wavelength range that substantially overlaps with that of the post-2004 HIRES spectra.
