COWS: A filament finder for Hessian cosmic web identifiers
  The large scale galaxy and matter distribution is often described by means of
the cosmic web made up of voids, sheets, filaments and knots. Many different
recipes exist for identifying this cosmic web. Here we focus on a sub-class of
cosmic web identifiers, based on the analysis of the Hessian matrix, and
proposed a method, called COsmic Web Skeleton (COWS), of separating a set of
filaments cells into an ensemble of individual discreet filaments.
Specifically, a thinning algorithm is applied to velocity shear tensor based
cosmic web (V-web) to identify the spine of the filaments. This results in a
set of filaments with well defined end-point and length. It is confirmed that
these sit at local density ridges and align with the appropriate direction
defined by the underlying velocity field. The radial density profile of these
curved cylindrical filaments, as well as the distribution of their lengths is
also examined. The robustness of all results is checked against resolution and
the V-web threshold. The code for the COWS method has been made publicly
available.
