  We conducted an analysis on dark matter halo properties following major and
minor mergers to advance our understanding of halo evolution. In this work, we
analyzed ~80,000 dark matter halos from the Bolshoi-Planck cosmological
simulation and studied halo evolution during relaxation after major mergers,
those in which the merging mass ratio m/M > 0.3. We then applied a Gaussian
filter to the property evolutions and characterized peak distributions,
frequencies, and variabilities for several halo properties, including
centering, spin, shape (prolateness), scale radius, and virial ratio. However,
there were also halos that experienced relaxation without the presence of major
mergers. We hypothesized that this was due to minor mergers unrecorded by the
simulation analysis. By using property peaks to create a novel merger detection
algorithm, we attempted to find minor mergers and match them to the unaccounted
relaxed halos. Not only did we find evidence that minor mergers were the
causes, but we also found similarities between major and minor merger effects,
showing the significance of minor mergers for future studies. Through our dark
matter merger statistics, we expect our work to ultimately serve as vital
parameters towards better understanding galaxy formation and evolution.
