Building Halo Merger Trees from the Q Continuum Simulation
  Cosmological N-body simulations rank among the most computationally intensive
efforts today. A key challenge is the analysis of structure, substructure, and
the merger history for many billions of compact particle clusters, called
halos. Effectively representing the merging history of halos is essential for
many galaxy formation models used to generate synthetic sky catalogs, an
important application of modern cosmological simulations. Generating realistic
mock catalogs requires computing the halo formation history from simulations
with large volumes and billions of halos over many time steps, taking hundreds
of terabytes of analysis data. We present fast parallel algorithms for
producing halo merger trees and tracking halo substructure from a single-level,
density-based clustering algorithm. Merger trees are created from analyzing the
halo-particle membership function in adjacent snapshots, and substructure is
identified by tracking the "cores" of merging halos -- sets of particles near
the halo center. Core tracking is performed after creating merger trees and
uses the relationships found during tree construction to associate
substructures with hosts. The algorithms are implemented with MPI and evaluated
on a Cray XK7 supercomputer using up to 16,384 processes on data from HACC, a
modern cosmological simulation framework. We present results for creating
merger trees from 101 analysis snapshots taken from the Q Continuum, a large
volume, high mass resolution, cosmological simulation evolving half a trillion
particles.
