Kilo-Degree Survey第四次数据发布中的红序星系聚类研究
Clustering of red-sequence galaxies in the fourth data release ofthe Kilo-Degree Survey
AI总结：
本研究利用KiDS第四次数据发布构建亮红序星系样本，通过红序模板筛选、测光权重校正等方法，测量角两点相关函数并约束大尺度偏置，验证了样本偏置的一致性及与被动演化模型的吻合性。
摘要：
我们提出了一个亮红序星系样本，用于研究Kilo-Degree Survey（千度巡天，简称KiDS）第四次数据发布中的大尺度结构。入选星系由红序模板定义，该模板是一种以红移为条件的、数据驱动的星等-颜色关系模型。本研究中，红序模板利用KiDS-VIKING的宽带光学+近红外测光数据以及重叠的光谱数据集构建。筛选过程包括估算红序红移、评估样本纯度，以及估算红移区间的基础红移分布。完成筛选后，我们通过为星系分配测光权重，降低了巡天特性对观测到的星系数密度的影响。我们测量了四个红移区间内红星系的角两点相关函数，并在假设固定ΛCDM宇宙学模型的前提下，约束了红序样本的大尺度偏置。我们发现两个光度阈值样本（致密样本与亮样本）的线性偏置具有一致性，且我们的约束结果与被动演化模型吻合良好。
英文摘要：
We present a sample of luminous red-sequence galaxies to study the large-scale structure in the fourth data release of the Kilo-Degree Survey. The selected galaxies are defined by a red-sequence template, in the form of a data-driven model of the colour-magnitude relation conditioned on redshift. In this work, the red-sequence template is built using the broad-band optical+near infrared photometry of KiDS-VIKING and the overlapping spectroscopic data sets. The selection process involves estimating the red-sequence redshifts, assessing the purity of the sample, and estimating the underlying redshift distributions of redshift bins. After performing the selection, we mitigate the impact of survey properties on the observed number density of galaxies by assigning photometric weights to the galaxies. We measure the angular two-point correlation function of the red galaxies in four redshift bins, and constrain the large scale bias of our red-sequence sample assuming a fixed $Λ$CDM cosmology. We find consistent linear biases for two luminosity-threshold samples (dense and luminous). We find that our constraints are well characterized by the passive evolution model.
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