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Optimal capture of non-Gaussianity in weak lensing surveys: power spectrum, bispectrum and halo counts

机译:弱透镜测量中非高斯性的最佳捕获:功率   光谱,双谱和晕圈计数

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摘要

We compare the efficiency of weak lensing-selected galaxy clusters counts andof the weak lensing bispectrum at capturing non-Gaussian features in the darkmatter distribution. We use the halo model to compute the weak lensing powerspectrum, the bispectrum and the expected number of detected clusters, andderive constraints on cosmological parameters for a large, low systematic weaklensing survey, by focusing on the $\Omega_m$-$\sigma_8$ plane and on the darkenergy equation of state. We separate the power spectrum into the resolved andthe unresolved parts of the data, the resolved part being defined as detectedclusters, and the unresolved part as the rest of the field. We consider fourkinds of clusters counts, taking into account different amount of information :signal-to-noise ratio peak counts; counts as a function of clusters' mass;counts as a function of clusters' redshift; and counts as a function ofclusters' mass and redshift. We show that when combined with the powerspectrum, those four kinds of counts provide similar constraints, thus allowingone to perform the most direct counts, signal-to-noise peaks counts, and getpercent level constraints on cosmological parameters. We show that the weaklensing bispectrum gives constraints comparable to those given by the powerspectrum and captures non-Gaussian features as well as clusters counts, itscombination with the power spectrum giving errors on cosmological parametersthat are similar to, if not marginally smaller than, those obtained whencombining the power spectrum with cluster counts. We finally note that in orderto reach its potential, the weak lensing bispectrum must be computed using alltriangle configurations, as equilateral triangles alone do not provide usefulinformation.
机译:我们在捕获暗物质分布中的非高斯特征时,比较了弱透镜选择星系团计数和弱透镜双谱的效率。我们通过关注$ \ Omega_m $-$ \ sigma_8 $平面,使用光晕模型来计算弱透镜屈光力谱,双谱和检测到的星团的预期数量,以及对大型,低系统弱透镜测量的宇宙学参数的派生约束以及关于状态的暗能量方程。我们将功率谱分为数据的已解析部分和未解析部分,已解析部分定义为检测到的簇,未解析部分定义为该字段的其余部分。考虑到不同的信息量,我们考虑了四种簇计数:信噪比峰值计数;根据簇的质量进行计数;根据簇的红移进行计数;并作为集群质量和红移的函数。我们显示,当与幂谱组合时,这四种计数提供相似的约束,从而使人们可以对宇宙学参数执行最直接的计数,信噪比峰值计数和水平百分比约束。我们证明了弱透镜双谱所给出的约束与功率谱所给予的约束相当,并且捕获了非高斯特征以及簇数,其与功率谱的组合给出了宇宙学参数的误差,该误差类似于(如果不是略小于)组合时获得的那些带有簇数的功率谱。我们最后注意到,为了发挥其潜力,必须使用全三角形配置来计算弱透镜双谱,因为仅等边三角形不能提供有用的信息。

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