Peaks above the Maxwellian Sea: A New Approach to Finding Substructure
  in N-Body Haloes
  We describe a new algorithm for finding substructures within dark matter
haloes from N-body simulations. The algorithm relies upon the fact that
dynamically distinct substructures in a halo will have a {\em local} velocity
distribution that differs significantly from the mean, i.e. smooth background
halo. We characterize the large-scale mean field using a coarsely grained
cell-based approach, while a kernel smoothing process is used to determined the
local velocity distribution. Comparing the ratio of these two estimates allows
us to identify particles which are strongly cluster in velocity space relative
to the background and thus resident in substructure. From this population of
outliers, groups are identified using a Friends-of-Friends-like approach. False
positives are rejected using Poisson noise arguments. This approach does not
require a search of the full phase-space structure of a halo, a non-trivial
task, and is thus computationally advantageous. We apply our algorithm to
several test cases and show that it identifies not only subhaloes, bound
overdensities in phase-space, but can recover tidal streams with a high purity.
Our method can even find streams which do not appear significantly overdense in
either physical or phase-space.
