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arXiv 2406.17849astro-ph.COastro-ph.GA
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利用星系团的飞溅半径约束宇宙学参数

Constraining cosmological parameters using the splashback radius of galaxy clusters

Roan Haggar, Yuba Amoura, Charlie T. Mpetha, James E. Taylor, Kris Walker, Chris Power

AI总结:

本研究利用宇宙学模拟发现星系团飞溅半径随$Ω_{\ m{M}}$和$σ_{8}$变化,能打破$S_{8}$参数测量导致的简并,从而通过弱引力透镜分析收紧低红移宇宙学参数约束。

摘要:

诸如 $Ω_{\ m{M}}$ 和 $σ_{8}$ 等宇宙学参数可以通过多种方法间接测量,包括星系团丰度和宇宙剪切。这些测量约束了复合参数 $S_{8}$,导致 $Ω_{\ m{M}}$ 和 $σ_{8}$ 之间产生简并。然而,由于星系团的一些结构性质依赖于其吸积历史,它们也与宇宙学参数相关。在本工作中,我们关注飞溅半径,这是一个可观测的星系团特征,代表了星系团与周围宇宙之间的边界。使用一系列具有不同 $Ω_{\ m{M}}$ 和 $σ_{8}$ 值的宇宙学模拟,我们表明在具有较小 $Ω_{\ m{M}}$ 值或较大 $σ_{8}$ 值的宇宙学中,星系团质量晕周围的飞溅半径位置更大。这种变化打破了由 $S_{8}$ 参数测量带来的 $Ω_{\ m{M}}$ 和 $σ_{8}$ 之间的简并。我们还表明这种变化原则上在观测中是可测量的。由于飞溅半径可以通过已用于估计 $S_{8}$ 的相同弱引力透镜分析来确定,这种新方法可以利用现有数据或诸如 Euclid 和 LSST 等即将到来的数据,收紧对宇宙学参数的低红移约束。

英文摘要:

Cosmological parameters such as $Ω_{\rm{M}}$ and $σ_{8}$ can be measured indirectly using various methods, including galaxy cluster abundance and cosmic shear. These measurements constrain the composite parameter $S_{8}$, leading to degeneracy between $Ω_{\rm{M}}$ and $σ_{8}$. However, some structural properties of galaxy clusters also correlate with cosmological parameters, due to their dependence on a cluster's accretion history. In this work, we focus on the splashback radius, an observable cluster feature that represents a boundary between a cluster and the surrounding Universe. Using a suite of cosmological simulations with a range of values for $Ω_{\rm{M}}$ and $σ_{8}$, we show that the position of the splashback radius around cluster-mass halos is greater in cosmologies with smaller values of $Ω_{\rm{M}}$ or larger values of $σ_{8}$. This variation breaks the degeneracy between $Ω_{\rm{M}}$ and $σ_{8}$ that comes from measurements of the $S_{8}$ parameter. We also show that this variation is, in principle, measurable in observations. As the splashback radius can be determined from the same weak lensing analysis already used to estimate $S_{8}$, this new approach can tighten low-redshift constraints on cosmological parameters, either using existing data, or using upcoming data such as that from Euclid and LSST.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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