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arXiv 2202.01809astro-ph.GAastro-ph.CO
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DESI PROObjective-Added Value Bright Galaxy Survey（PROVABGS）模拟挑战赛

The DESI PRObabilistic Value-Added Bright Galaxy Survey (PROVABGS) Mock Challenge

ChangHoon Hahn, K. J. Kwon, Rita Tojeiro, Malgorzata Siudek, Rebecca E. A. Canning, Mar Mezcua, Jeremy L. Tinker, David Brooks, Peter Doel, Kevin Fanning, Enriq… 展开作者

ChangHoon Hahn, K. J. Kwon, Rita Tojeiro, Malgorzata Siudek, Rebecca E. A. Canning, Mar Mezcua, Jeremy L. Tinker, David Brooks, Peter Doel, Kevin Fanning, Enrique Gaztañaga, Robert Kehoe, Martin Landriau, Aaron Meisner, John Moustakas, Claire Poppett, Gregory Tarle, Benjamin Weiner, Hu Zou

备注：
40 pages, 17 figures, submitted to ApJ, the PROVABGS SED modeling pipeline is publicly available at https://github.com/changhoonhahn/provabgs
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摘要：

PROOBESTAL增值明亮星系巡天（PROVABGS）目录将提供星系属性的测量，如恒星质量（$M_*$），恒星形成率（${\rm SFR}$），恒星金属度（$Z_{\rm MW}$）和恒星年龄（$t_{\rm age, MW}$），为DESI明亮星系巡天中超过1000万个星系。星系属性的完整后验分布将使用DESI光谱学和Legacy Surveys光度学的最新贝叶斯光谱能量分布（SED）建模来推断。在这项工作中，我们提出了SED模型，贝叶斯推理框架，和PROVABGS的方法。此外，我们适用于现实的合成DESI光谱和光度学，使用L-GALAXIES半解析模型构建的PROVABGS SED建模。我们比较推断的星系属性的模拟使用分层贝叶斯框架，以量化的准确性和精度的真实星系属性。总体而言，我们准确地推断出真实的$M_*$，${\rm SFR}$，$Z_{\rm MW}$，和$t_{\rm age, MW}$的模拟星系。然而，由SED模型引起的星系性质的先验对后验有显着的影响。他们强加了一个${\rm SFR}{>}10^{-1} M_\odot/{\rm yr}$下限${\rm SFR}$，${\sim}0.3$ dex偏差$\log Z_{\rm MW}$的星系与低光谱信噪比，和$t_{\rm age, MW} < 8\,{\rm Gyr}$上界恒星年龄。这项工作还表明，光谱和测光的联合分析显着提高了对星系性质的限制，单独测光，是必要的，以减轻先验的影响。通过这项工作中提出和验证的方法，PROVABGS将最大限度地利用从DESI观测中提取的信息，并提供一个概率增值星系目录，将当前的星系研究扩展到新的制度，并解锁尖端的概率分析。

英文摘要：

The PRObabilistic Value-Added Bright Galaxy Survey (PROVABGS) catalog will provide measurements of galaxy properties, such as stellar mass ($M_*$), star formation rate (${\rm SFR}$), stellar metallicity ($Z_{\rm MW}$), and stellar age ($t_{\rm age, MW}$), for >10 million galaxies of the DESI Bright Galaxy Survey. Full posterior distributions of the galaxy properties will be inferred using state-of-the-art Bayesian spectral energy distribution (SED) modeling of DESI spectroscopy and Legacy Surveys photometry. In this work, we present the SED model, Bayesian inference framework, and methodology of PROVABGS. Furthermore, we apply the PROVABGS SED modeling on realistic synthetic DESI spectra and photometry, constructed using the L-GALAXIES semi-analytic model. We compare the inferred galaxy properties to the true galaxy properties of the simulation using a hierarchical Bayesian framework to quantify accuracy and precision. Overall, we accurately infer the true $M_*$, ${\rm SFR}$, $Z_{\rm MW}$, and $t_{\rm age, MW}$ of the simulated galaxies. However, the priors on galaxy properties induced by the SED model have a significant impact on the posteriors. They impose a ${\rm SFR}{>}10^{-1} M_\odot/{\rm yr}$ lower bound on ${\rm SFR}$, a ${\sim}0.3$ dex bias on $\log Z_{\rm MW}$ for galaxies with low spectral signal-to-noise, and $t_{\rm age, MW} < 8\,{\rm Gyr}$ upper bound on stellar age. This work also demonstrates that a joint analysis of spectra and photometry significantly improves the constraints on galaxy properties over photometry alone and is necessary to mitigate the impact of the priors. With the methodology presented and validated in this work, PROVABGS will maximize information extracted from DESI observations and provide a probabilistic value-added galaxy catalog that will extend current galaxy studies to new regimes and unlock cutting-edge probabilistic analyses.

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