A kinematic classification of the cosmic web

TL;DR

This paper introduces a new velocity shear tensor-based algorithm for classifying the cosmic web, enabling higher resolution analysis of cosmic structures down to less than 0.1h^{-1} Mpc.

Contribution

The paper presents a novel classification method based on velocity shear tensors, extending previous tidal tensor approaches and achieving finer structural resolution.

Findings

Velocity-based web resolves structures below 0.1h^{-1} Mpc

Void regions are extended and under-dense

Filaments and knots dominate over-dense regions

Abstract

A new approach for the classification of the cosmic web is presented. In extension of the previous work of Hahn et al. (2007) and Forero-Romero et al. (2009) the new algorithm is based on the analysis of the velocity shear tensor rather than the gravitational tidal tensor. The procedure consists of the construction of the the shear tensor at each (grid) point in space and the evaluation of its three eigenvectors. A given point is classified to be either a void, sheet, filament or a knot according to the number of eigenvalues above a certain threshold, 0, 1, 2, or 3 respectively. The threshold is treated as a free parameter that defines the web. The algorithm has been applied to a dark matter only, high resolution simulation of a box of side-length 64$h^{-1}$Mpc and N = $1024^3$ particles with the framework of the WMAP5/LCDM model. The resulting velocity based cosmic web resolves structures down to <0.1$h^{-1}$Mpc scales, as opposed to the ~1$h^{-1}$Mpc scale of the tidal based web. The under-dense regions are made of extended voids bisected by planar sheets, whose density is also below the mean. The over-dense regions are vastly dominated by the linear filaments and knots. The resolution achieved by the velocity based cosmic web provides a platform for studying the formation of halos and galaxies within the framework of the cosmic web.