A New Multi-Scale Structure Finding Algorithm to Identify Cosmological Structure

TL;DR

This paper presents a novel multi-scale algorithm for identifying and classifying large-scale cosmological structures such as clusters, filaments, and voids, aligning well with observational data.

Contribution

The paper introduces a self-consistent, multi-scale structure finding algorithm that accurately classifies cosmological structures and reproduces key observational results.

Findings

Reproduces baryon fraction of ICM

Matches average temperatures and densities of structures

Effectively classifies clusters, filaments, and voids

Abstract

We introduce a new self-consistent structure finding algorithm that parses large scale cosmological structure into clusters, filaments and voids. This structure finding algorithm probes the cosmological structure at multiple scales and clas- sifies the appropriate regions with the most probable structure type and size. We show that it reproduces key observational results, including the baryon fraction of ICM, and average temperatures and densities for the different structures.