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arXiv 2304.04489astro-ph.CO
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CSST弱引力透镜准备I:预测非高斯协方差的影响及系统学控制要求

CSST WL preparation I: forecast the impact from non-Gaussian covariances and requirements on systematics-control

Ji Yao, Huanyuan Shan, Ran Li, Youhua Xu, Dongwei Fan, Dezi Liu, Pengjie Zhang, Yu Yu, Chengliang Wei, Bin Hu, Nan Li, Zuhui Fan, Haojie Xu, Wuzheng Guo

AI总结:

针对CSST巡天,预测非高斯协方差(以超样本协方差为主)显著降低统计信噪比,导致品质因子损失,并提出系统学控制要求(如固有排列、重子反馈等)以实现无偏宇宙学。

摘要:

精确估计统计误差和准确消除系统误差是第四代宇宙切变巡天面临的两大主要挑战。我们针对中国空间站望远镜(CSST),其巡天面积约17,500平方度,红移最高约4,探讨了这些误差的影响。我们考虑了由高斯协方差、连通非高斯协方差和超样本协方差贡献的统计误差。我们发现,以超样本协方差为主导的非高斯协方差,能够大幅降低CSST两点统计量的信噪比,导致物质聚集特性(σ8-Ωm平面)的品质因子损失约1/3,暗能量状态方程(w0-wa平面)的品质因子损失1/6。我们进一步对以下系统学缓解提出了要求:星系固有排列、重子反馈、剪切乘法偏差以及红移分布偏差,以实现无偏宇宙学。10^-2至10^-3水平的要求强调了相关研究的强烈需求,以支持未来的模型选择及相应的干扰参数先验。

英文摘要:

The precise estimation of the statistical errors and accurate removal of the systematical errors are the two major challenges for the stage IV cosmic shear surveys. We explore their impact for the China Space-Station Telescope (CSST) with survey area $\sim17,500°^2$ up to redshift $\sim4$. We consider statistical error contributed from Gaussian covariance, connected non-Gaussian covariance and super-sample covariance. We find the non-Gaussian covariances, which is dominated by the super-sample covariance, can largely reduce the signal-to-noise of the two-point statistics for CSST, leading to a $\sim1/3$ loss in the figure-of-merit for the matter clustering properties ($σ_8-Ω_m$ plane) and $1/6$ in the dark energy equation-of-state ($w_0-w_a$ plane). We further put requirements of systematics-mitigation on: intrinsic alignment of galaxies, baryonic feedback, shear multiplicative bias, and bias in the redshift distribution, for an unbiased cosmology. The $10^{-2}$ to $10^{-3}$ level requirements emphasize strong needs in related studies, to support future model selections and the associated priors for the nuisance parameters.

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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