Optimizing high-redshift galaxy surveys for environmental information

ABSTRACT We investigate the performance of group finding algorithms that reconstruct galaxy groups from positional information tracer galaxies are observed in redshift surveys carried out with multiplexed spectrographs. use mock light-cones produced by L-Galaxies semi-analytic model evolution which underlying reality is known. particularly focus on at high redshift, and how this affected choices mass (largely equivalent to their co-moving number density) (assumed random) sampling rate these tracers. first however compare two different approaches as applied low conclude broadly comparable. For simplicity we adopt just one these, ‘Friends-of-Friends’ (FoF) basis for our study redshift. introduce 12 science metrics designed quantify group-finder relevant a wide range investigations catalogue. These examine quality recovered catalogue, median halo masses richness structures, scatter dark matter successful classifies singletons, centrals, satellites. analyse vary limiting stellar random galaxies, allowing quantification various trade-offs between possible survey designs. Finally, look impact same design parameters relative ‘costs’ observation time using an example potential MOONRISE MOONS instrument.