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arXiv 1307.7626astro-ph.GA
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仙女座卫星系统的PAndAS视图- I。利用空间和色星等信息对矮星系的贝叶斯搜索

The PAndAS view of the Andromeda satellite system - I. A Bayesian search for dwarf galaxies using spatial and color-magnitude information

Nicolas F. Martin, Rodrigo A. Ibata, Alan W. McConnachie, A. Dougal Mackey, Annette M. N. Ferguson, Michael J. Irwin, Geraint F. Lewis, Mark A. Fardal

摘要:

我们提出了一个通用的算法来搜索矮星系的光度表,并将其应用到泛仙女座考古调查(PAndAS)。该算法是在贝叶斯框架下开发的,与大多数矮星系搜索代码相反,它利用了源的空间和颜色星等信息,采用概率方法。占显着的污染从银河系前景和仙女座星系的结构恒星晕,我们恢复所有已知的矮星系在PAndAS足迹具有很高的意义,即使是最不发光的。一些仙女座球状星团也被恢复,并在一个案例中被发现。我们发布了一个由该算法产生的143个最重要的检测的列表。39个最重要的孤立探测的综合性质表明,至少有一些这样的痕迹真正的矮星系,太暗,无法单独检测。社区必须进行后续观测,以确定哪些是仙女座卫星系统的真正成员。这里提出的搜索技术将用于在即将到来的贡献,以确定矮星系的PAdAS完整性限制。虽然在这里调谐到搜索矮星系的PAndAS数据,该算法可以很容易地适应于搜索任何局部的过密度,其属性可以可靠地建模在任何目录的参数空间。

英文摘要:

We present a generic algorithm to search for dwarf galaxies in photometric catalogs and apply it to the Pan-Andromeda Archaeological Survey (PAndAS). The algorithm is developed in a Bayesian framework and, contrary to most dwarf-galaxy-search codes, makes use of both the spatial and color-magnitude information of sources in a probabilistic approach. Accounting for the significant contamination from the Milky Way foreground and from the structured stellar halo of the Andromeda galaxy, we recover all known dwarf galaxies in the PAndAS footprint with high significance, even for the least luminous ones. Some Andromeda globular clusters are also recovered and, in one case, discovered. We publish a list of the 143 most significant detections yielded by the algorithm. The combined properties of the 39 most significant isolated detections show hints that at least some of these trace genuine dwarf galaxies, too faint to be individually detected. Follow-up observations by the community are mandatory to establish which are real members of the Andromeda satellite system. The search technique presented here will be used in an upcoming contribution to determine the PAndAS completeness limits for dwarf galaxies. Although here tuned to the search of dwarf galaxies in the PAndAS data, the algorithm can easily be adapted to the search for any localised overdensity whose properties can be modeled reliably in the parameter space of any catalog.

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。

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