Optimizing high redshift galaxy surveys for environmental information

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