pop-cosmos:从 COSMOS 数据中全面了解星系群体

Justin Alsing, Stephen Thorp, Sinan Deger, Hiranya V. Peiris, Boris Leistedt, Daniel Mortlock, Joel Leja
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引用次数: 0

摘要

我们提出了 pop-cosmos:一个描述星系种群特征的综合模型,它是根据宇宙演化巡天(COSMOS)的 140,938 个(r < 25 个选定的)星系,用从紫外线到红外线的 26 个波段的光度测量进行校准的。我们为 COSMOS 数据构建了一个详细的前向模型,其中包括:一个描述星系特征及其演化联合分布的种群模型(由一个灵活的基于分数的扩散模型进行参数化);一个将星系的内在属性与其光度测量联系起来的最先进的恒星种群合成模型;以及一个用于观测、校准和选择过程的数据模型。通过最小化合成数据和真实数据之间的最佳传输距离,我们能够联合拟合种群模型和数据模型,从而得出考虑到参数退化、光度噪声和校准以及选择的稳健校准种群级推断。我们介绍了我们的模型对宇宙学和星系演化的一些关键预测,包括质量函数和红移分布;质量-金属性-红移和基本金属性关系;恒星形成序列;尘埃衰减与恒星质量、恒星形成率和衰减律指数之间的关系;以及气体电离与恒星形成之间的关系。我们的模型包含了星系演化的全面图景,可以忠实地预测宽红移(z < 4)和波长范围内的星系颜色。
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pop-cosmos: A Comprehensive Picture of the Galaxy Population from COSMOS Data
We present pop-cosmos: a comprehensive model characterizing the galaxy population, calibrated to 140,938 (r < 25 selected) galaxies from the Cosmic Evolution Survey (COSMOS) with photometry in 26 bands from the ultraviolet to the infrared. We construct a detailed forward model for the COSMOS data, comprising: a population model describing the joint distribution of galaxy characteristics and its evolution (parameterized by a flexible score-based diffusion model); a state-of-the-art stellar population synthesis model connecting galaxies’ intrinsic properties to their photometry; and a data model for the observation, calibration, and selection processes. By minimizing the optimal transport distance between synthetic and real data, we are able to jointly fit the population and data models, leading to robustly calibrated population-level inferences that account for parameter degeneracies, photometric noise and calibration, and selection. We present a number of key predictions from our model of interest for cosmology and galaxy evolution, including the mass function and redshift distribution; the mass–metallicity-redshift and fundamental metallicity relations; the star-forming sequence; the relation between dust attenuation and stellar mass, star formation rate, and attenuation-law index; and the relation between gas-ionization and star formation. Our model encodes a comprehensive picture of galaxy evolution that faithfully predicts galaxy colors across a broad redshift (z < 4) and wavelength range.
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