Automated detection of filaments in the large scale structure of the universe
Roberto E. Gonzalez (1), Nelson E. Padilla (1) ((1) Universidad, Catolica de Chile)

TL;DR
This paper introduces a novel method for detecting large-scale filaments in the universe's structure using cosmological simulation data, focusing on dark matter haloes and their spatial relationships.
Contribution
The method uniquely combines skeleton-like backbone construction with binding energy criteria, demonstrating robustness without requiring detailed dynamical information.
Findings
High-quality filaments constitute about 33% of detected filaments.
Filament lengths mostly below 50 h^{-1} Mpc, with some extending up to 150 h^{-1} Mpc.
Node connectivity increases with node mass, from about 1.87 to 2.49 filaments per node.
Abstract
We present a new method to identify large scale filaments and apply it to a cosmological simulation. Using positions of haloes above a given mass as node tracers, we look for filaments between them using the positions and masses of all the remaining dark-matter haloes. In order to detect a filament, the first step consists in the construction of a backbone linking two nodes, which is given by a skeleton-like path connecting the highest local dark matter (DM) density traced by non-node haloes. The filament quality is defined by a density and gap parameters characterising its skeleton, and filament members are selected by their binding energy in the plane perpendicular to the filament. This membership condition is associated to characteristic orbital times; however if one assumes a fixed orbital timescale for all the filaments, the resulting filament properties show only marginal changes,…
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