论文标题
使用群集质量关系来限制宇宙学参数
Constraining Cosmological Parameters using the Cluster Mass-Richness Relation
论文作者
论文摘要
群集质量富度关系（MRR）是一种观察性高效且潜在强大的宇宙学工具，可使用簇丰度技术来限制宇宙的平均值密度和波动的振幅。我们使用Galwcat19得出MRR关系，GalwCAT19是我们从Sloan Digital Sky Survey-DR13 Spectroscopic数据集创建的公开可用的星系集群目录。 MRR在低富度末端显示尾巴。使用Illustris-TNG和Mini-uchuu宇宙学数值模拟，我们证明了这条尾巴是由系统的不确定性引起的。我们表明，通过明智的剪切，通过使用铰链函数来确定，可以确定MRR为线性的丰富度阈值，即群集质量尺度为logM_200 = alpha + beta logn_200。我们得出MRR并表明它与两组beta〜1的模拟一致。我们使用MRR来估计GalwCAT19目录中的群集质量，然后我们将其用于在Omega_m和Sigma_8上设置约束。利用全成员MRR，我们获得了Omega_m = 0.31（+0.04-0.03）和Sigma_8 = 0.82（+0.05-0.04）的约束，并利用红色会员MRR，我们获得了OmeGa_M = 0.31（+0.04-0.03）和Sigma__8 = 0.81（+0.04-0.03）和0.81（+0.81（+0.81）。我们对Omega_M和Sigma_8的限制与Planck 2018结果非常有竞争力。
The cluster mass-richness relation (MRR) is an observationally efficient and potentially powerful cosmological tool for constraining the mean matter density of the universe and the amplitude of fluctuations using the cluster abundance technique. We derive the MRR relation using GalWCat19, a publicly available galaxy cluster catalog we created from the Sloan Digital Sky Survey-DR13 spectroscopic dataset. The MRR shows a tail at the low-richness end. Using the Illustris-TNG and mini-Uchuu cosmological numerical simulations, we demonstrate that this tail is caused by systematical uncertainties. We show that, by means of a judicious cut, identified by the use of the Hinge function, it is possible to determine a richness threshold above which the MRR is linear i.e., where cluster mass scales with richness as logM_200 = alpha + beta logN_200. We derive the MRR and show it is consistent with both sets of simulations with a slope of beta ~ 1. We use our MRR to estimate cluster masses from the GalWCat19 catalog which we then use to set constraints on omega_m and sigma_8. Utilizing the all-member MRR, we obtain constraints of omega_m = 0.31 (+0.04-0.03) and sigma_8 = 0.82 (+0.05-0.04), and utilizing the red-member MRR, we obtain omega_m = 0.31 (+0.04-0.03) and sigma_8 = 0.81 (+0.05-0.04). Our constraints on omega_m and sigma_8 are consistent and very competitive with the Planck 2018 results.
