Galaxy Groups at Low and High Redshift with RESOLVE and LADUMA

The group environment plays a key role in galaxy evolution through common processes such as merging and stripping. The physical interpretation and utility of group metrics across redshift depend on the method of group finding and the quality of the survey data. Here, we construct volume-limited group catalogs using ancillary data sets cross-matched in the field of the LADUMA (Looking At the Distant Universe with the MeerKAT Array) survey, a MeerKAT large program that will provide unprecedented sensitivity to neutral hydrogen emission out to z > 1. To make best use of a mixture of photometric and spectroscopic redshifts, we implement a probabilistic friends-of-friends algorithm with full cosmological corrections to identify groups at high redshift. We apply these methods and simulate high-z data quality issues by degrading spectroscopic redshifts, flux sensitivity, and catalog completeness in the highly complete, volume-limited z ~ 0 RESOLVE (REsolved Spectroscopy of a Local VolumE) survey. We compare the typical sizes of groups across redshifts, with attention to cosmic variance. Finally, in preparation for a comparable analysis at high redshift, we quantify the integrated gas content in RESOLVE groups, examining how their gas inventory changes with group membership refinement and/or subgroup identification. This research has been supported by National Science Foundation grant AST-1814486.