Identification of Cosmological Filaments

PEREYRA, LUIS; SGRÓ, MARIO AGUSTIN; MERCHÁN. MANUEL; STASYSZYN, FEDERICO; PAZ, DANTE

Córdoba

Workshop; Friends of Friends; 2019

In this work, we identify and analyse the properties of filaments assuming that they are structures that connect neighbouring critical points those maxima of the density field defined by dark matter halos of masses in the range of cluster of galaxies. To extract filaments we develop a simple identification algorithmbased on two standard tools, the Minimal Spanning Tree (MST) and the Friends of Friends (FoF) algorithm. By focusing our analysis on the densest dark matter filaments, we found that the radial density profile, at scales around $1, h^{-1} mathrm{Mpc}$, approximately follow a power-law function with index -2. Furthermore, the large infall velocities from the low-density environment approach perpendicular to the filaments and diverge from a saddle point in the filament towards the clusters at the filament ends.We find that the location of this saddle point on the filament spine depends on the masses of the clusters at the filament ends.Following theoretical prescriptions, we estimate the linear density from the transverse velocity dispersion, finding a good correspondence with the measured mass per unit of length of our filaments.These two results can be applied to observational samples of filaments linking two physical properties as the saddle point location and the mass per unit length with two measurements obtained from observations as cluster masses and the velocity dispersion of galaxies.