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首页> 外文期刊>The Astrophysical journal >K2: A NEW METHOD FOR THE DETECTION OF GALAXY CLUSTERS BASED ON CANADA–FRANCE–HAWAII TELESCOPE LEGACY SURVEY MULTICOLOR IMAGES
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K2: A NEW METHOD FOR THE DETECTION OF GALAXY CLUSTERS BASED ON CANADA–FRANCE–HAWAII TELESCOPE LEGACY SURVEY MULTICOLOR IMAGES

机译:K2:基于加拿大-法国-夏威夷电视台遗留遗产调查多色图像的银河团检测新方法

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摘要

We have developed a new method, K2, optimized for the detection of galaxy clusters in multicolor images. Based on the Red Sequence approach, K2 detects clusters using simultaneous enhancements in both colors and position. The detection significance is robustly determined through extensive Monte Carlo simulations and through comparison with available cluster catalogs based on two different optical methods, and also on X-ray data. K2 also provides quantitative estimates of the candidate clusters' richness and photometric redshifts. Initially, K2 was applied to the two color (gri) 161 deg2 images of the Canada-France-Hawaii Telescope Legacy Survey Wide (CFHTLS-W) data. Our simulations show that the false detection rate for these data, at our selected threshold, is only ~1%, and that the cluster catalogs are ~80% complete up to a redshift of z = 0.6 for Fornax-like and richer clusters and to z ~ 0.3 for poorer clusters. Based on the g-, r-, and i-band photometric catalogs of the Terapix T05 release, 35 clusters/deg2 are detected, with 1-2 Fornax-like or richer clusters every 2 deg2. Catalogs containing data for 6144 galaxy clusters have been prepared, of which 239 are rich clusters. These clusters, especially the latter, are being searched for gravitational lenses—one of our chief motivations for cluster detection in CFHTLS. The K2 method can be easily extended to use additional color information and thus improve overall cluster detection to higher redshifts. The complete set of K2 cluster catalogs, along with the supplementary catalogs for the member galaxies, are available on request from the authors.
机译:我们已经开发了一种新方法K2,该方法针对多色图像中的星系团的检测进行了优化。基于红色序列方法,K2通过同时增强颜色和位置来检测聚类。通过广泛的蒙特卡洛模拟并与基于两种不同光学方法以及X射线数据的可用聚类目录进行比较,可以可靠地确定检测的重要性。 K2还提供了候选簇的丰富度和光度红移的定量估计。最初,将K2应用于加拿大-法国-夏威夷望远镜遗留测量范围(CFHTLS-W)数据的两个彩色(gri)161 deg2图像。我们的模拟显示,在我们选择的阈值下,这些数据的错误检测率仅为〜1%,并且对于类Fornax和更丰富的群集,群集目录的完成率达到〜80%达到了红移z = 0.6。较差的群集z〜0.3。根据Terapix T05版本的g,r和i波段光度学目录,检测到35个簇/度2,每2 deg2有1-2个类似于Fornax的或更丰富的簇。已准备好包含6144个星系团数据的目录,其中239个是富集团。正在寻找这些星团,尤其是后者,以寻找引力透镜,这是我们在CFHTLS中进行星团检测的主要动机之一。 K2方法可以轻松扩展为使用其他颜色信息,从而将总体群集检测提高到更高的红移。可根据作者的要求提供完整的K2星团目录集以及成员星系的补充目录。

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