arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 0910.2617astro-ph.IM
收藏

COSMOS场的钱德拉巡天:震源探测和photometry

The Chandra survey of the COSMOS field II: source detection and photometry

S. Puccetti, C. Vignali, N. Cappelluti, F. Fiore, G. Zamorani, T. L. Aldcroft, M. Elvis, R. Gilli, T. Miyaji, H. Brunner, M. Brusa, F. Civano, A. Comastri, F. D… 展开作者

S. Puccetti, C. Vignali, N. Cappelluti, F. Fiore, G. Zamorani, T. L. Aldcroft, M. Elvis, R. Gilli, T. Miyaji, H. Brunner, M. Brusa, F. Civano, A. Comastri, F. Damiani, A. Fruscione, A. Finoguenov, A. M. Koekemoer, V. Mainieri

摘要:

钱德拉宇宙巡天(C-COSMOS)是一个大型的1.8毫秒钱德拉计划,覆盖了宇宙场的中心连续~0.92 deg^2。C-COSMOS是一个复杂的镶嵌的结果,每个位置都有多达六个重叠点(四个重叠点位于中心约0.45度^2的大部分区域,具有最佳曝光,两个重叠点位于周围的大部分区域,覆盖了额外的约0.47度^2)。因此,C-COSMOS数据的充分利用需要专注于三个主要问题的专门和准确的分析:1)当PSF在同一源的不同观测值之间发生强烈变化时(从~1 arcsec到~10 arcsec半功率半径),最大化灵敏度; 2)解析闭合对;以及3)获得最佳源定位和计数率。我们在这里提出我们的处理四个关键分析项目:源检测,定位,光度测定,和调查灵敏度。我们的最后程序包括两个步骤的程序:(1)小波检测算法,找到源的候选者,(2)极大似然点扩散函数拟合算法,以评估源计数率和每个源候选者是背景的波动的概率。我们讨论了这个过程的主要特点,这是不同的检测算法和测光工具之间的详细比较的结果,广泛和专用的模拟校准。

英文摘要:

The Chandra COSMOS Survey (C-COSMOS) is a large, 1.8 Ms, Chandra program, that covers the central contiguous ~0.92 deg^2 of the COSMOS field. C-COSMOS is the result of a complex tiling, with every position being observed in up to six overlapping pointings (four overlapping pointings in most of the central ~0.45 deg^2 area with the best exposure, and two overlapping pointings in most of the surrounding area, covering an additional ~0.47 deg^2). Therefore, the full exploitation of the C-COSMOS data requires a dedicated and accurate analysis focused on three main issues: 1) maximizing the sensitivity when the PSF changes strongly among different observations of the same source (from ~1 arcsec up to ~10 arcsec half power radius); 2) resolving close pairs; and 3) obtaining the best source localization and count rate. We present here our treatment of four key analysis items: source detection, localization, photometry, and survey sensitivity. Our final procedure consists of a two step procedure: (1) a wavelet detection algorithm, to find source candidates, (2) a maximum likelihood Point Spread Function fitting algorithm to evaluate the source count rates and the probability that each source candidate is a fluctuation of the background. We discuss the main characteristics of this procedure, that was the result of detailed comparisons between different detection algorithms and photometry tools, calibrated with extensive and dedicated simulations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑