论文标题
弱透镜层析成像红移分布推断超级智能卡鲁斯·斯巴鲁战略计划三年形状目录
Weak Lensing Tomographic Redshift Distribution Inference for the Hyper Suprime-Cam Subaru Strategic Program three-year shape catalogue
论文作者
论文摘要
我们提供了后验样品红移分布，用于超级智能Subaru战略计划弱镜头三年（HSC Y3）分析。使用星系的光度法和空间互相关，我们对样品红移分布进行了组合的贝叶斯分层推断。空间互相关是使用发光红色星系（LRG）的子样本得出的，其准确的红移信息可提供，最多可提供$ z <1.2 $的光度红移。我们使用在光谱和多播放光度数据上校准的两种经验技术的组合得出了基于光度法的约束，该技术涵盖了剪切目录的空间子集。有限的空间覆盖范围会导致我们在推理中包含的宇宙差异错误预算。我们的互相关分析对LRG的光度红移误差进行了建模，以纠正系统的偏见和统计不确定性。我们证明了使用空间互相关得出的样品红移分布之间的一致性，相结合分析的后验。基于此评估，我们建议保守的先验，以用于三年宇宙学弱透镜分析中使用的层析形成箱的样品红移分布。
We present posterior sample redshift distributions for the Hyper Suprime-Cam Subaru Strategic Program Weak Lensing three-year (HSC Y3) analysis. Using the galaxies' photometry and spatial cross-correlations, we conduct a combined Bayesian Hierarchical Inference of the sample redshift distributions. The spatial cross-correlations are derived using a subsample of Luminous Red Galaxies (LRGs) with accurate redshift information available up to a photometric redshift of $z < 1.2$. We derive the photometry-based constraints using a combination of two empirical techniques calibrated on spectroscopic- and multiband photometric data that covers a spatial subset of the shear catalog. The limited spatial coverage induces a cosmic variance error budget that we include in the inference. Our cross-correlation analysis models the photometric redshift error of the LRGs to correct for systematic biases and statistical uncertainties. We demonstrate consistency between the sample redshift distributions derived using the spatial cross-correlations, the photometry, and the posterior of the combined analysis. Based on this assessment, we recommend conservative priors for sample redshift distributions of tomographic bins used in the three-year cosmological Weak Lensing analyses.
