COWS: a filament finder for Hessian cosmic web identifiers. Issue 1 (30th May 2022) - Pfeifer, Simon; Libeskind, Noam I; Hoffman, Yehuda; Hellwing, Wojciech A; Bilicki, Maciej; Naidoo, Krishna
ABSTRACT: 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.