论文标题
从不完整的光谱数据中识别高红移的星系组：I。组查找器和ZCOSMOS应用
Identifying galaxy groups at high redshift from incomplete spectroscopic data: I. The group finder and application to zCOSMOS
论文作者
论文摘要
从星系的红移调查中识别星系基团在将星系与潜在的暗物质分布连接起来起着重要作用。当前和未来的高$ z $光谱调查通常在红移采样中不完整，这既给在高$ z $宇宙中识别群体都带来机会和挑战。我们开发了一个基于不完整的红移样品与光度数据结合的组发现器，并使用机器学习方法将光晕质量分配给已识别的组。使用现实的模拟目录进行测试表明，具有Halo Masses $ \ rm M_H \ gtrsim 10^{12} M _ {\ odot}/H $的$ \ gtrsim 90 \％$ $ $ \ rm m_h \ gtrsim 10^{12} {\ odot}/h $已成功识别，并且污染物的部分比$ 10 \％$。在所有质量上，光环质量估计的标准偏差小于0.25 DEX。我们将我们的小组查找器应用于Zcosmos-Bright，并描述获得的组目录的基本属性。
Identifying galaxy groups from redshift surveys of galaxies plays an important role in connecting galaxies with the underlying dark matter distribution. Current and future high-$z$ spectroscopic surveys, usually incomplete in redshift sampling, present both opportunities and challenges to identifying groups in the high-$z$ Universe. We develop a group finder that is based on incomplete redshift samples combined with photometric data, using a machine learning method to assign halo masses to identified groups. Test using realistic mock catalogs shows that $\gtrsim 90\%$ of true groups with halo masses $\rm M_h \gtrsim 10^{12} M_{\odot}/h$ are successfully identified, and that the fraction of contaminants is smaller than $10\%$. The standard deviation in the halo mass estimation is smaller than 0.25 dex at all masses. We apply our group finder to zCOSMOS-bright and describe basic properties of the group catalog obtained.
