Identifying Mergers Using Quantitative Morphologies in Zoom Simulations
  of High-Redshift Galaxies
  Non-parametric morphology measures are a powerful tool for identifying galaxy
mergers at low redshifts. We employ cosmological zoom simulations using Gizmo
with the Mufasa feedback scheme, post-processed using 3D dust radiative
transfer into mock observations, to study whether common morphological measures
Gini G, M20, concentration C, and asymmetry A are effective at identifying
major galaxy mergers at z ~ 2 - 4, i.e. "Cosmic Noon". Our zoom suite covers
galaxies with 10^8.6 < M_* < 10^11 M_sun at z ~ 2, and broadly reproduces key
global galaxy observations. Our primary result is that these morphological
measures are unable to robustly pick out galaxies currently undergoing mergers
during Cosmic Noon, typically performing no better than a random guess. This
improves only marginally if we consider whether galaxies have undergone a
merger within the last Gyr. When also considering minor mergers, galaxies
display no trend of moving towards the merger regime with increasing merger
ratio. From z = 4 -> 2, galaxies move from the non-merger towards the merger
regime in all statistics, but this is primarily an effect of mass: Above a
given noise level, higher mass galaxies display a more complex outer morphology
induced by their clustered environment. We conclude that during Cosmic Noon,
these morphological statistics are of limited value in identifying galaxy
mergers.
