Crawling the Cosmic Network: Exploring the Morphology of Structure in the Galaxy Distribution

TL;DR

This paper introduces a Hessian-based method to classify large-scale cosmic structures like walls, filaments, and clumps in galaxy distributions, validated on simulations and SDSS data, revealing scale-dependent morphology and evolution.

Contribution

It presents a novel Hessian matrix approach for characterizing the morphology of large-scale structures in galaxy surveys and simulations.

Findings

Structures are filament-dominated at 10-20 h^{-1} Mpc scales.

Clump-dominated at 5 h^{-1} Mpc scales.

Walls are present but not dominant below ~25 h^{-1} Mpc.

Abstract

Although coherent large-scale structures such as filaments and walls are apparent to the eye in galaxy redshift surveys, they have so far proven difficult to characterize with computer algorithms. This paper presents a procedure that uses the eigenvalues and eigenvectors of the Hessian matrix of the galaxy density field to characterize the morphology of large-scale structure. By analysing the smoothed density field and its Hessian matrix, we can determine the types of structure - walls, filaments, or clumps - that dominate the large-scale distribution of galaxies as a function of scale. We have run the algorithm on mock galaxy distributions in a LCDM cosmological N-body simulation and the observed galaxy distributions in the Sloan Digital Sky Survey. The morphology of structure is similar between the two catalogues, both being filament-dominated on 10-20 h^{-1} Mpc smoothing scales and clump-dominated on 5 h^{-1} Mpc scales. There is evidence for walls in both distributions, but walls are not the dominant structures on scales smaller than ~25 h^{-1} Mpc. Analysis of the simulation suggests that, on a given comoving smoothing scale, structures evolve with time from walls to filaments to clumps, where those found on smaller smoothing scales are further in this progression at a given time.