A reliable cluster detection technique using photometric redshifts: introducing the 2TecX algorithm

TL;DR

The paper introduces 2TecX, a new high-redshift galaxy cluster detection algorithm that uses full photometric redshift probability functions and cross-checks two different methods to improve reliability and reduce false detections.

Contribution

It presents a novel cluster detection technique combining Voronoi Tesselations and Friends-Of-Friends methods with full probability functions, enhancing detection accuracy at high redshift.

Findings

Reduces spurious detections through cross-checking techniques.

Effectively isolates high-redshift clusters with high efficiency.

Defines completeness and mass limits as functions of redshift.

Abstract

We present a new cluster detection algorithm designed for finding high-redshift clusters using optical/infrared imaging data. The algorithm has two main characteristics. First, it utilises each galaxy's full redshift probability function, instead of an estimate of the photometric redshift based on the peak of the probability function and an associated Gaussian error. Second, it identifies cluster candidates through cross-checking the results of two substantially different selection techniques (the name 2TecX representing the cross-check of the two techniques). These are adaptations of the Voronoi Tesselations and Friends-Of-Friends methods. Monte-Carlo simulations of mock catalogues show that cross-checking the cluster candidates found by the two techniques significantly reduces the detection of spurious sources. Furthermore, we examine the selection effects and relative strengths and weaknesses of either method. The simulations also allow us to fine-tune the algorithm's parameters, and define completeness and mass limit as a function of redshift. We demonstrate that the algorithm isolates high-redshift clusters at a high level of efficiency and low contamination.