Comparison of halo detection from noisy weak lensing convergence maps with Gaussian smoothing and MRLens treatment
Comparison of halo detection from noisy weak lensing convergence maps with Gaussian smoothing and MRLens treatment
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DOI：
10.1088/1674-4527/11/5/002
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发表时间：
2010-12
影响因子：
1.8
通讯作者：
Yang-XiuJiaoj;Huan-YuanShan;Zu-HuiFan
中科院分区：
文献类型：
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作者：
Yang-XiuJiaoj;Huan-YuanShan;Zu-HuiFan
在考虑源星系内禀椭圆率噪声的情况下，我们研究了弱透镜会聚映射中晕探测的效率和完备性。特别是，通过数值模拟，我们比较了高斯滤波器与所谓的MRLens处理的基础上修改的最大熵方法。对于没有透镜信号的纯噪声场，如果足够大数量的星系被包括在平滑窗口中，则高斯平滑导致在统计方面近似为高斯的残余噪声场。另一方面，MRLens治疗后的噪声场明显非高斯，导致表征噪声效应的复杂性。考虑到弱透镜聚类检测，尽管MRLens处理有效地删除了由噪声引起的假峰，但是由于其在其恢复过程中不能将具有相对低幅度的真实的信号与噪声区分开，因此其严重地去除了真实的峰。噪声水平越高，对真实的峰的去除效果越大。对于一个源密度为ng <$30 arcmin−2的观测，在探测阈值κ = 0.02的情况下，经过MRLens滤波后，在3 × 3 deg 2的区域内发现的峰值数量仅为50个，而在同一区域内M > 5 × 1013 M <$3且红移z <$2的晕的数量预计为530个。对于高斯平滑处理，检测的数量是10260，远大于MRLens。高斯平滑情况下的噪声统计的高斯性为该方法增加了进一步的优点，以规避弱透镜聚类检测中相对低效率的问题。因此，在旨在从弱透镜调查构建大聚类样本的研究中，高斯平滑方法的表现明显优于MRLens处理。
Taking into account the noise from intrinsic ellipticities of source galaxies, we study the efficiency and completeness of halo detections from weak lensing convergence maps. Particularly, with numerical simulations, we compare the Gaussian filter with the so called MRLens treatment based on the modification of the Maximum Entropy Method. For a pure noise field without lensing signals, a Gaussian smoothing results in a residual noise field that is approximately Gaussian in terms of statistics if a large enough number of galaxies are included in the smoothing window. On the other hand, the noise field after the MRLens treatment is significantly non-Gaussian, resulting in complications in characterizing the noise effects. Considering weak-lensing cluster detections, although the MRLens treatment effectively deletes false peaks arising from noise, it removes the real peaks heavily due to its inability to distinguish real signals with relatively low amplitudes from noise in its restoration process. The higher the noise level is, the larger the removal effects are for the real peaks. For a survey with a source density ng ∼ 30 arcmin−2, the number of peaks found in an area of 3 × 3 deg2 after MRLens filtering is only ∼ 50 for the detection threshold κ = 0.02, while the number of halos with M > 5 × 1013 M⊙ and with redshift z ⩽ 2 in the same area is expected to be ∼ 530. For the Gaussian smoothing treatment, the number of detections is ∼ 260, much larger than that of the MRLens. The Gaussianity of the noise statistics in the Gaussian smoothing case adds further advantages for this method to circumvent the problem of the relatively low efficiency in weak-lensing cluster detections. Therefore, in studies aiming to construct large cluster samples from weak-lensing surveys, the Gaussian smoothing method performs significantly better than the MRLens treatment.