论文标题

带有星系簇的宇宙学弱镜头:统计限制和实验设计

Cosmology with galaxy cluster weak lensing: statistical limits and experimental design

论文作者

Wu, Hao-Yi, Weinberg, David H., Salcedo, Andrés N., Wibking, Benjamin D.

论文摘要

在当前和下一代弱透镜调查中,我们可以预测对物质聚类sigma_8(z)的幅度的约束。我们主张一种类似于星系 - 果胶镜头的方法,其中每个红移箱中的可观察力是平均数量计数,而簇簇的平均弱透镜曲线在质量代理阈值之上。主要的天体物理滋扰参数是阈值附近的质量代理和真实质量之间的对数散射。对于类似于黑暗能源调查(DES)的调查,罗马空间望远镜高纬度调查(HLS)和鲁宾天文台的遗产调查(LSST),我们预测Sigma_8的0.26%,0.24%和0.10%的Sigma_8的总计准确性分别比质量 - OBSEVERABLE STAPTAR ESTERTE STARTE AN 0.01更好。在DES或HLS的情况下,对于0.05的散射,对于LSST的0.016,这些约束将在0.05的散射中降低约20%。一个月的一个月观察计划,其针对约2500个大型群集的罗马空间望远镜可以单独对Sigma_8(Z = 0.7)的限制达到0.5%,或与HLS结合使用约0.33%。实现簇的约束功能需要准确了解质量观察的关系和严格控制系统学的能力。我们为我们的数值结果提供了分析近似,可以轻松地对其他调查假设或其他群集质量估计方法进行缩放。

We forecast constraints on the amplitude of matter clustering sigma_8(z) achievable with the combination of cluster weak lensing and number counts, in current and next-generation weak lensing surveys. We advocate an approach, analogous to galaxy-galaxy lensing, in which the observables in each redshift bin are the mean number counts and the mean weak lensing profile of clusters above a mass proxy threshold. The primary astrophysical nuisance parameter is the logarithmic scatter between the mass proxy and true mass near the threshold. For surveys similar to the Dark Energy Survey (DES), the Roman Space Telescope High Latitude Survey (HLS), and the Rubin Observatory Legacy Survey of Space and Time (LSST), we forecast aggregate precision on sigma_8 of 0.26%, 0.24%, and 0.10%, respectively, if the mass-observable scatter has an external prior better than 0.01. These constraints would be degraded by about 20% for a 0.05 prior on scatter in the case of DES or HLS and for a 0.016 prior for LSST. A one-month observing program with Roman Space Telescope targeting approximately 2500 massive clusters could achieve a 0.5% constraint on sigma_8(z=0.7) on its own, or a ~0.33% constraint in combination with the HLS. Realizing the constraining power of clusters requires accurate knowledge of the mass-observable relation and stringent control of systematics. We provide analytic approximations to our numerical results that allow easy scaling to other survey assumptions or other methods of cluster mass estimation.

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