Weak lensing with sizes, magnitudes and shapes
Weak lensing with sizes, magnitudes and shapes
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DOI：
10.1093/mnras/stv1249
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发表时间：
2014-10
影响因子：
4.8
通讯作者：
Justin Alsing;D. Kirk;A. Heavens;A. Jaffe
中科院分区：
文献类型：
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作者：
Justin Alsing;D. Kirk;A. Heavens;A. Jaffe
弱透镜效应可以通过对遥远星系图像的一些影响来观察到;它们的形状被剪切，它们的大小和大小被放大，它们在天空中的位置被透镜场改变。星系的形状探测剪切场，而星系的大小、星等和数密度探测会聚场。两者都包含宇宙学信息。在本文中，我们关注的是作为宇宙收敛的探测器的单个星系的大小和星等的放大，并解决三个关键问题：给定的大小，星等和红移，我们如何估计收敛场？对于一个典型的透镜观测来说，大小和量级的内在分布是什么？这种分布的形状如何决定我们推断收敛的能力？对于观测到的大小-星等分布，除了宇宙剪切，我们还能从放大中提取多少额外的信息？我们开发了一个贝叶斯方法推断的收敛ELD从测量的大小，幅度和红移，并证明收敛的推断需要详细的知识的联合分布的内在大小和幅度。我们建立了一个简单的参数化模型的sizemagnitude分布和估计CFHTLenS星系的分布。根据测量的分布，我们表明收敛估计的典型离散度为0：8，而剪切的离散度为0：38。我们讨论了放大的物理系统学的可能性（类似于剪切的内在排列），并计算了暗能量品质因数（FoM）的预期增益，从结合放大与剪切的差异
Weak lensing can be observed through a number of eects on the images of distant galaxies; their shapes are sheared, their sizes and uxes (magnitudes) are magnied and their positions on the sky are modied by the lensing eld. Galaxy shapes probe the shear eld whilst size, magnitude and number density probe the convergence eld. Both contain cosmological information. In this paper we are concerned with the magnication of the size and magnitude of individual galaxies as a probe of cosmic convergence and address three key questions: given a size, magnitude and redshift, how do we estimate the convergence eld? What is the intrinsic distribution of sizes and magnitudes for a typical lensing survey and how does the shape of this distribution determine our ability to infer convergence? For the observed size-magnitude distribution, how much additional information might we expect to extract from magnication in addition to cosmic shear? We develop a Bayesian approach for inferring the convergence eld from a measured size, magnitude and redshift and demonstrate that the inference on convergence requires detailed knowledge of the joint distribution of intrinsic sizes and magnitudes. We build a simple parameterised model for the sizemagnitude distribution and estimate this distribution for CFHTLenS galaxies. In light of the measured distribution, we show that the typical dispersion on convergence estimation is 0:8, compared to 0:38 for shear. We discuss the possibility of physical systematics for magnication (similar to intrinsic alignments for shear) and compute the expected gains in the Dark Energy Figure-of-Merit (FoM) from combining magnication with shear for dierent