NEXUS: Tracing the Cosmic Web Connection

TL;DR

The paper introduces the NEXUS algorithm and its extension NEXUS+ for multiscale, automatic identification of cosmic web structures like clusters, filaments, walls, and voids using various tracers, validated on N-body simulations.

Contribution

It presents a novel multiscale morphological analysis tool that effectively identifies cosmic web environments without size or shape bias, especially excelling with the NEXUS+ method.

Findings

NEXUS+ better detects filamentary and wall networks.

All methods identify prominent structures, but differ on tenuous features.

Density and tidal fields produce clumpier structures than velocity-based tracers.

Abstract

We introduce the NEXUS algorithm for the identification of Cosmic Web environments: clusters, filaments, walls and voids. This is a multiscale and automatic morphological analysis tool that identifies all the cosmic structures in a scale free way, without preference for a certain size or shape. We develop the NEXUS method to incorporate the density, tidal field, velocity divergence and velocity shear as tracers of the Cosmic Web. We also present the NEXUS+ procedure which, taking advantage of a novel filtering of the density in logarithmic space, is very successful at identifying the filament and wall environments in a robust and natural way. To asses the algorithms we apply them to an N-body simulation. We find that all methods correctly identify the most prominent filaments and walls, while there are differences in the detection of the more tenuous structures. In general, the structures traced by the density and tidal fields are clumpier and more rugged than those present in the velocity divergence and velocity shear fields. We find that the NEXUS+ method captures much better the filamentary and wall networks and is successful in detecting even the fainter structures. We also confirm the efficiency of our methods by examining the dark matter particle and halo distributions.