• DOI:10.1093/mnras/staa2816
• Corpus ID: 219559274

Identifying galaxy groups at high redshift from incomplete spectroscopic data – I. The group finder and application to zCOSMOS

@article{Wang2020IdentifyingGG,
  title={Identifying galaxy groups at high redshift from incomplete spectroscopic data – I. The group finder and application to zCOSMOS},
  author={Kai Wang and H. J. Mo and Cheng Li and Jiacheng Meng and Yangyao Chen},
  journal={Monthly Notices of the Royal Astronomical Society},
  year={2020},
  volume={499},
  pages={89-105}
}

• Kai Wang, H. Mo, +2 authors Yangyao Chen
• Published 9 June 2020
• Physics
• Monthly Notices of the Royal Astronomical Society

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.