arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2007.12200astro-ph.GAastro-ph.CO
收藏

一种自校准的基于Halo的星系群探测器:算法与测试

A Self-Calibrating Halo-Based Galaxy Group Finder: Algorithm and Tests

Jeremy L. Tinker

摘要:

我们描述了一个扩展的晕为基础的星系群发现算法。我们增加了自由的算法,以更准确地确定哪些星系的中心,哪些是卫星,并提供无偏估计的晕质量。我们着重于确定恒星形成和静止星系的星系晕关系。在组查找算法中增加的自由度是使用依赖颜色的星系聚类的观测以及光谱中心星系L_sat的堆叠样本周围的深度成像数据中的总卫星光度的测量进行自校准的。我们在一系列模拟上测试这种方法,这些模拟改变了星系晕的连接,包括一个从UniverseMachine结果构建的模拟。我们的自校准算法显示出显着的改进,在以前的方法估计的颜色依赖的卫星星系的比例。它将中心星系log M_halo的误差减小了一倍以上,减小到<~0.2 dex。通过L_sat数据,它可以量化恒星形成和静止星系的光度-晕质量关系的差异,即使是只有一个光谱成员的星系群。而以前的算法不能约束在固定的M_halo的L_gal的散射,自校准技术可以提供一个强大的下限,这种散射。

英文摘要:

We describe an extension of the halo-based galaxy group-finding algorithm. We add freedom to the algorithm in order to more accurately determine which galaxies are central and which are satellites, and to provide unbiased estimates of halo masses. We focus on determination of the galaxy-halo relations for star-forming and quiescent galaxies. The added freedom in the group-finding algorithm is self-calibrated using observations of color-dependent galaxy clustering, as well as measurements of the total satellite luminosity in deep imaging data around stacked samples of spectroscopic central galaxies, L_sat. We test this approach on a series of mocks that vary the galaxy-halo connection, including one mock constructed from UniverseMachine results. Our self-calibrated algorithm shows marked improvement over previous methods in estimating the color-dependent satellite fraction of galaxies. It reduces the error in log M_halo for central galaxies by over a factor of two, to <~0.2 dex. Through the L_sat data, it can quantify differences in the luminosity-to-halo mass relations for star-forming and quiescent galaxies, even for groups with only one spectroscopic member. Whereas previous algorithms cannot constrain the scatter in L_gal at fixed M_halo, the self-calibration technique can provide a robust lower limit to this scatter.

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。

↑