Automated detection of filaments in the large scale structure of the
  universe
  We present a new method to identify large scale filaments and apply it to a
cosmological simulation. Using positions of haloes above a given mass as node
tracers, we look for filaments between them using the positions and masses of
all the remaining dark-matter haloes. In order to detect a filament, the first
step consists in the construction of a backbone linking two nodes, which is
given by a skeleton-like path connecting the highest local dark matter (DM)
density traced by non-node haloes. The filament quality is defined by a density
and gap parameters characterising its skeleton, and filament members are
selected by their binding energy in the plane perpendicular to the filament.
This membership condition is associated to characteristic orbital times;
however if one assumes a fixed orbital timescale for all the filaments, the
resulting filament properties show only marginal changes, indicating that the
use of dynamical information is not critical for the method. We test the method
in the simulation using massive haloes($M>10^{14}$h$^{-1}M_{\odot}$) as
filament nodes. The main properties of the resulting high-quality filaments
(which corresponds to $\simeq33%$ of the detected filaments) are, i) their
lengths cover a wide range of values of up to $150 $h$^{-1}$Mpc, but are mostly
concentrated below 50h$^{-1}$Mpc; ii) their distribution of thickness peaks at
$d=3.0$h$^{-1}$Mpc and increases slightly with the filament length; iii) their
nodes are connected on average to $1.87\pm0.18$ filaments for $\simeq
10^{14.1}M_{\odot}$ nodes; this number increases with the node mass to $\simeq
2.49\pm0.28$ filaments for $\simeq 10^{14.9}M_{\odot}$ nodes.
