Identifying galaxy groups at high redshift from incomplete spectroscopic data – I. The group finder and application to zCOSMOS
Kai Wang, H. J. Mo, Cheng Li, Jiacheng Meng, Yangyao Chen
Abstract
ABSTRACT 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 catalogues shows that $\gtrsim \! 90{{\ \rm per\ cent}}$ of true groups with halo masses $\rm {\it M}_h \gtrsim 10^{12} M_{\odot }\,h^{-1}$ are successfully identified, and that the fraction of contaminants is smaller than $10{{\ \rm per\ cent}}$. 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 catalogue obtained.