利用50个VLT场的孔径质量统计寻找星系团
Searching for galaxy clusters using the aperture mass statistics in 50 VLT fields
摘要：
应用孔径质量（地图）统计提供了一个弱透镜的方法来检测集群大小的暗物质晕。我们提出了一个新的孔径滤波器功能，并最大限度地提高了有效性的地图统计检测集群大小的晕使用分析模型。然后，我们使用弱透镜模拟目录产生的光线追踪通过N体模拟，分析图像处理的效果上的预期数密度的晕。使用地图统计，孔径半径通常为几个弧分，因此孔径经常部分位于数据场之外，从而降低了晕轮检测的信噪比。我们研究这些边界效应分析和使用模拟目录。我们发现，预期的数密度的晕减少了两个因素，如果一个字段的大小是可比的孔径的直径。最后，我们报告的结果，一个弱透镜集群搜索应用地图统计50随机选择的字段，在VLT与FORS 1观察。总共50个VLT字段覆盖0.64平方度的面积。I波段图像是在良好的视宁度条件下拍摄的（平均视宁度为0.6弧秒）。这导致了用于弱透镜分析的星系的高数量密度（26个/平方角分）。在五个VLT领域，我们检测到一个显着的地图信号，这与光分布的过密度相一致。因此，这些检测是剪切选择集群的优秀候选者。
英文摘要：
Application of the aperture mass (Map-) statistics provides a weak lensing method for the detection of cluster-sized dark matter halos. We present a new aperture filter function and maximise the effectiveness of the Map-statistics to detect cluster-sized halos using analytical models. We then use weak lensing mock catalogues generated from ray-tracing through N-body simulations, to analyse the effect of image treatment on the expected number density of halos. Using the Map-statistics, the aperture radius is typically several arcminutes, hence the aperture often lies partly outside a data field, consequently the signal-to-noise ratio of a halo detection decreases. We study these border effects analytically and by using mock catalogues. We find that the expected number density of halos decreases by a factor of two if the size of a field is comparable to the diameter of the aperture used. We finally report on the results of a weak lensing cluster search applying the Map-statistics to 50 randomly selected fields which were observed with FORS1 at the VLT. Altogether the 50 VLT fields cover an area of 0.64 square degrees. The I-band images were taken under excellent seeing conditions (average seeing 0.6 arcsec.) which results in a high number density of galaxies used for the weak lensing analysis (26/sq.arcmin). In five of the VLT fields, we detect a significant Map-signal which coincides with an overdensity of the light distribution. These detections are thus excellent candidates for shear-selected clusters.
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