用Prospector从宽波段测光法导出物理性质：模型的描述和在局部宇宙中使用129个Galerkin对其准确性的证明
Deriving Physical Properties from Broadband Photometry with Prospector: Description of the Model and a Demonstration of its Accuracy Using 129 Galaxies in the Local Universe
摘要：
星系的宽带测光测量复杂的恒星星族、气体和尘埃的未解决的混合。解释这些数据对模型来说是一个挑战：许多研究表明，从模拟星系光度学中得出的属性是不确定的，其不确定性为两倍或更多，但现在回答该领域的关键问题需要更高的精度。在这里，我们提出了一个新的模型框架，专门为这些复杂性。我们的模型，勘探者- $α$，包括尘埃衰减和再辐射，一个灵活的衰减曲线，星云发射，恒星金属丰度，和一个6分量的非参数恒星形成历史。参数空间的灵活性和范围，加上Prospector推理框架内的MCMC采样，旨在提供无偏参数和现实的误差线。我们用孔径匹配的光谱法评估模型的准确性，这是从拟合中排除的。我们比较光谱特征预测仅从适合的宽带测光观察到的光谱特征。我们的模型预测H $α$光度与分散的$\sim$ 0.18德克斯和偏移的$\sim$ 0.1德克斯在广泛的形态类型和恒星质量。这种一致性是值得注意的，因为H $α$光度依赖于精确的恒星形成速率、尘埃衰减和恒星金属丰度。该模型还准确地预测尘埃敏感的巴耳末递减，光谱恒星金属丰度，PAH质量分数，以及年龄和金属敏感的功能D $_{\mathrm{n}}$ 4000和H $δ$。虽然该模型通过了所有这些测试，我们警告说，我们还没有评估其性能在更高的红移或恢复恒星质量的准确性。
英文摘要：
Broadband photometry of galaxies measures an unresolved mix of complex stellar populations, gas, and dust. Interpreting these data is a challenge for models: many studies have shown that properties derived from modeling galaxy photometry are uncertain by a factor of two or more, and yet answering key questions in the field now requires higher accuracy than this. Here, we present a new model framework specifically designed for these complexities. Our model, Prospector-$α$, includes dust attenuation and re-radiation, a flexible attenuation curve, nebular emission, stellar metallicity, and a 6-component nonparametric star formation history. The flexibility and range of the parameter space, coupled with MCMC sampling within the Prospector inference framework, is designed to provide unbiased parameters and realistic error bars. We assess the accuracy of the model with aperture-matched optical spectroscopy, which was excluded from the fits. We compare spectral features predicted solely from fits to the broadband photometry to the observed spectral features. Our model predicts H$α$ luminosities with a scatter of $\sim$0.18 dex and an offset of $\sim$0.1 dex across a wide range of morphological types and stellar masses. This agreement is remarkable, as the H$α$ luminosity is dependent on accurate star formation rates, dust attenuation, and stellar metallicities. The model also accurately predicts dust-sensitive Balmer decrements, spectroscopic stellar metallicities, PAH mass fractions, and the age- and metallicity-sensitive features D$_{\mathrm{n}}$4000 and H$δ$. Although the model passes all these tests, we caution that we have not yet assessed its performance at higher redshift or the accuracy of recovered stellar masses.
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