  Dark matter simulations require statistical techniques to properly identify
and classify their halos and structures. Nonparametric solutions provide
catalogs of these structures but lack the additional learning of a model-based
algorithm and might misclassify particles in merging situations. With mixture
models, we can simultaneously fit multiple density profiles to the halos that
are found in a dark matter simulation. In this work, we use the Einasto profile
(Einasto 1965, 1968, 1969) to model the halos found in a sample of the Bolshoi
simulation (Klypin et al. 2011), and we obtain their location, size, shape and
mass. Our code is implemented in the R statistical software environment and can
be accessed on https://github.com/LluisHGil/darkmix.
