Stellar spectral classification is a fundamental tool of modern astronomy, providing insight into physical characteristics such as effective temperature, surface gravity, and metallicity. Accurate and fast spectral typing is an integral need for large all-sky spectroscopic surveys like the Sloan Digital Sky Survey (SDSS) and the Large Sky Area Multi-Object Fiber Spectroscopic Telescope. Here, we present the next version of PyHammer, a stellar spectral classification software that uses optical spectral templates and spectral line index measurements. PyHammer v2.0 extends the classification power to include dwarf carbon stars, DA white dwarf stars, and also double-lined spectroscopic binaries (SB2). This release also includes a new empirical library of luminosity-normalized spectra that can be used to flux calibrate observed spectra or to create synthetic SB2 spectra. We have generated physically reasonable SB2 combinations as templates, adding the ability to spectrally type SB2s ...

中文翻译：

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使用光学恒星模板对单星和光谱双星进行分类

恒星光谱分类是现代天文学的基本工具，可深入了解物理特征，例如有效温度，表面重力和金属性。准确，快速的光谱分型是大型全天候光谱调查（如斯隆数字天空调查（SDSS）和大天空区域多目标光纤光谱望远镜）的整体需求。在这里，我们介绍PyHammer的下一个版本，这是一种使用光谱模板和光谱线指数测量的恒星光谱分类软件。PyHammer v2.0扩展了分类能力，包括矮碳星，DA白矮星以及双线光谱双星（SB2）。此版本还包括一个新的光度归一化光谱经验库，可用于对已观察光谱进行通量校准或创建合成SB2光谱。我们已经生成了物理上合理的SB2组合作为模板，从而增加了对SB2进行光谱分类的功能...