POINT-AGAPE调查：比较微透镜事件的自动识别与M31
The POINT-AGAPE Survey: Comparing Automated Searches of Microlensing Events toward M31
摘要：
使用自动化超像素调查在M31中搜索微透镜引起了许多困难，这些困难在更传统的技术中不存在。在这里，我们专注于这个问题，即微透镜候选人的名单是敏感的选择标准或“削减”强加和一些主观性是参与这一点。削弱切割将产生一个更长的微透镜候选者列表，但有更大比例的虚假事件;加强切割将产生一个更短的列表，但可能会排除一些真正的事件。我们说明了这一点，通过比较三个分析相同的数据集，从3年的观察运行INT在拉帕尔马。其中两项分析的结果已经报道：Belokurov等人（2005）根据其切割强度获得了3至22个候选者，而Calchi Novati等人（2005）获得了6个候选者。第三个分析是首次提出的，报告了10个微透镜候选者，其中7个是新的。只有两个候选人是共同的所有三个分析。为了理解为什么这些分析会产生不同的候选人名单，比较了三个小组使用的削减。
英文摘要：
Searching for microlensing in M31 using automated superpixel surveys raises a number of difficulties which are not present in more conventional techniques. Here we focus on the problem that the list of microlensing candidates is sensitive to the selection criteria or "cuts" imposed and some subjectivity is involved in this. Weakening the cuts will generate a longer list of microlensing candidates but with a greater fraction of spurious ones; strengthening the cuts will produce a shorter list but may exclude some genuine events. We illustrate this by comparing three analyses of the same data-set obtained from a 3-year observing run on the INT in La Palma. The results of two of these analyses have been already reported: Belokurov et al. (2005) obtained between 3 and 22 candidates, depending on the strength of their cuts, while Calchi Novati et al. (2005) obtained 6 candidates. The third analysis is presented here for the first time and reports 10 microlensing candidates, 7 of which are new. Only two of the candidates are common to all three analyses. In order to understand why these analyses produce different candidate lists, a comparison is made of the cuts used by the three groups...
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。
