论文标题
Kids-1000目录:红移分布及其校准
KiDS-1000 catalogue: Redshift distributions and their calibration
论文作者
论文摘要
我们提出了从$ \ sim1000 $ deg $^2 $(KIDS-1000)的区域中的第四个数据发布中选择的星系的红移发行估算。这些红移分布代表了使用儿童1000数据的弱重力透镜测量值的关键成分之一。主要估计值是基于深度光谱参考目录,这些目录在自组织的帮助(SOM)的帮助下重新加权,以非常类似于儿童1000来源,分为光度法红移范围内的五个断层扫描红移箱$ 0.1 <z____________ \ sathrm {b} \ le1.2 $。选择源以使它们仅占据九维幅度空间的体积,该空间也被参考样品(“金”选择)覆盖。从模拟目录中估计,从该校准确定的平均红移中的剩余偏见为$ \ lyssim0.01 $,对于所有五个垃圾箱,不确定性为$ \ sim 0.01 $。对Kids-1000红移分布的这种主要SOM估计,采用独立的聚类红移方法进行了补充。在验证了同一模拟目录上的聚类-y $ z $并仔细评估系统错误之后,我们发现SOM红移分布没有明显的偏差,相对于群集 - $ z $测量。簇$ z $重新校准的SOM红移分布代表了红移分布的替代校准,在$ \ sim 0.01-0.02 $的平均红移中仅略大不确定性,可用于儿童1000宇宙学弱弱透镜分析。由于这包括SOM不确定性,因此群集 - $ Z $在Kids-1000数据上具有完全竞争力。
We present redshift distribution estimates of galaxies selected from the fourth data release of the Kilo-Degree Survey over an area of $\sim1000$ deg$^2$ (KiDS-1000). These redshift distributions represent one of the crucial ingredients for weak gravitational lensing measurements with the KiDS-1000 data. The primary estimate is based on deep spectroscopic reference catalogues that are re-weighted with the help of a self-organising map (SOM) to closely resemble the KiDS-1000 sources, split into five tomographic redshift bins in the photometric redshift range $0.1<z_\mathrm{B}\le1.2$. Sources are selected such that they only occupy that volume of nine-dimensional magnitude-space that is also covered by the reference samples (`gold' selection). Residual biases in the mean redshifts determined from this calibration are estimated from mock catalogues to be $\lesssim0.01$ for all five bins with uncertainties of $\sim 0.01$. This primary SOM estimate of the KiDS-1000 redshift distributions is complemented with an independent clustering redshift approach. After validation of the clustering-$z$ on the same mock catalogues and a careful assessment of systematic errors, we find no significant bias of the SOM redshift distributions with respect to the clustering-$z$ measurements. The SOM redshift distributions re-calibrated by the clustering-$z$ represent an alternative calibration of the redshift distributions with only slightly larger uncertainties in the mean redshifts of $\sim 0.01-0.02$ to be used in KiDS-1000 cosmological weak lensing analyses. As this includes the SOM uncertainty, clustering-$z$ are shown to be fully competitive on KiDS-1000 data.