Mock galaxy shape catalogues in the Subaru Hyper Suprime-Cam Survey
Mock galaxy shape catalogues in the Subaru Hyper Suprime-Cam Survey
复制标题
Subaru Hyper Suprime-Cam Survey 中的模拟星系形状目录
DOI：
10.1093/mnras/stz791
复制
发表时间：
2019
影响因子：
4.8
通讯作者：
Hironao Miyatake
中科院分区：
文献类型：
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作者：
Masato Shirasaki;Takashi Hamana;Masahiro Takada;Ryuichi Takahashi;Hironao Miyatake
我们使用全天光线追踪弱透镜模拟为 Subaru Hyper Suprime-Cam (HSC) 调查第一年剪切目录生成 2268 个模拟目录。我们的模拟目录考虑了真实数据中的各种影响：勘测足迹、源星系的不均匀角分布、光度红移（photo-z）估计中的统计不确定性、透镜权重的变化以及星系形状测量中的统计噪声（包括内在形状和测量误差）。然后，我们利用模拟目录来评估宇宙切变两点相关性 ψ± 测量中预期的统计不确定性与 HSC 调查的断层摄影红移信息。我们适当考虑了调查足迹中源对的数量，为高斯样本方差开发了一个准分析公式。标准高斯公式显着高估或低估了模拟结果 50% 的水平。我们还表明，不同的照片目录或六个不相连的字段，而不是连续的几何形状，会导致协方差的变化。模拟目录使我们能够研究 χ± 的卡方分布。我们发现，所使用的数据向量的自由度分布比天真的预期的分布更宽。最后，我们提出了一种在模拟形状目录中包含非零乘性偏差的方法，并表明非零乘性偏差可以改变宇宙剪切分析中的有效形状噪声。我们的结果表明，估计似然函数的准确形式（以及协方差）对于根据精确测量进行稳健的宇宙学参数推断非常重要。
We use the full-sky ray-tracing weak lensing simulations to generate 2268 mock catalogues for the Subaru Hyper Suprime-Cam (HSC) survey first-year shear catalogue. Our mock catalogues take into account various effects as in the real data: the survey footprints, inhomogeneous angular distribution of source galaxies, statistical uncertainties in photometric redshift (photo-z) estimate, variations in the lensing weight, and the statistical noise in galaxy shape measurements including both intrinsic shapes and the measurement errors. We then utilize our mock catalogues to evaluate statistical uncertainties expected in measurements of cosmic shear two-point correlations ξ±with tomographic redshift information for the HSC survey. We develop a quasi-analytical formula for the Gaussian sample variance properly taking into account the number of source pairs in the survey footprints. The standard Gaussian formula significantly overestimates or underestimates the mock results by 50 per cent level. We also show that different photo-zcatalogues or the six disconnected fields, rather than a consecutive geometry, cause variations in the covariance by. The mock catalogues enable us to study the chi-square distribution for ξ±. We find the wider distribution than that naively expected for the distribution with the degrees of freedom of data vector used. Finally, we propose a method to include non-zero multiplicative bias in mock shape catalogue and show that the non-zero multiplicative bias can change the effective shape noise in cosmic shear analyses. Our results suggest an importance of estimating an accurate form of the likelihood function (and therefore the covariance) for robust cosmological parameter inference from the precise measurements.