sOPTICS: A Modified Density-Based Algorithm for Identifying Galaxy Groups/Clusters and Brightest Cluster Galaxies

TL;DR

This paper introduces sOPTICS, a modified density-based clustering algorithm that improves the identification of galaxy groups, clusters, and brightest cluster galaxies over traditional methods, demonstrating robustness and high accuracy in simulations and observational data.

Contribution

The paper proposes sOPTICS, a novel modification of the OPTICS algorithm that accounts for redshift space distortions, enhancing galaxy cluster detection accuracy.

Findings

sOPTICS outperforms FoF in identifying galaxy clusters and BCGs.

sOPTICS demonstrates robustness to outliers and hyperparameter variations.

High recovery rate of BCGs in large galaxy samples.

Abstract

A direct approach to studying the galaxy-halo connection is to analyze groups and clusters of galaxies that trace the underlying dark matter halos, emphasizing the importance of identifying galaxy clusters and their associated brightest cluster galaxies (BCGs). In this work, we test and propose a robust density-based clustering algorithm that outperforms the traditional Friends-of-Friends (FoF) algorithm in the currently available galaxy group/cluster catalogs. Our new approach is a modified version of the Ordering Points To Identify the Clustering Structure (OPTICS) algorithm, which accounts for line-of-sight positional uncertainties due to redshift space distortions by incorporating a scaling factor, and is thereby referred to as sOPTICS. When tested on both a galaxy group catalog based on semi-analytic galaxy formation simulations and observational data, our algorithm demonstrated robustness to outliers and relative insensitivity to hyperparameter choices. In total, we compared the results of eight clustering algorithms. The proposed density-based clustering method, sOPTICS, outperforms FoF in accurately identifying giant galaxy clusters and their associated BCGs in various environments with higher purity and recovery rate, also successfully recovering 115 BCGs out of 118 reliable BCGs from a large galaxy sample. Furthermore, when applied to an independent observational catalog without extensive re-tuning, sOPTICS maintains high recovery efficiency, confirming its flexibility and effectiveness for large-scale astronomical surveys.