Spectral Clustering for Optical Confirmation and Redshift Estimation of X-ray Selected Galaxy Cluster Candidates in the SDSS Stripe 82

TL;DR

This paper presents a spectral clustering algorithm to identify optical counterparts and estimate redshifts of X-ray selected galaxy clusters, successfully discovering new clusters and accurately estimating their redshifts in SDSS Stripe 82.

Contribution

The paper introduces a novel spectral clustering method for optical confirmation and redshift estimation of X-ray galaxy cluster candidates using SDSS data.

Findings

Accurately estimated photometric redshifts with a median error of 0.025.

Identified 12 new galaxy clusters in X-ray and optical data.

Confirmed 7 clusters with spectroscopic redshifts.

Abstract

We develop a galaxy cluster finding algorithm based on spectral clustering technique to identify optical counterparts and estimate optical redshifts for X-ray selected cluster candidates. As an application, we run our algorithm on a sample of X-ray cluster candidates selected from the third XMM-Newton serendipitous source catalog (3XMM-DR5) that are located in the Stripe 82 of the Sloan Digital Sky Survey (SDSS). Our method works on galaxies described in the color-magnitude feature space. We begin by examining 45 galaxy clusters with published spectroscopic redshifts in the range of 0.1 to 0.8 with a median of 0.36. As a result, we are able to identify their optical counterparts and estimate their photometric redshifts, which have a typical accuracy of 0.025 and agree with the published ones. Then, we investigate another 40 X-ray cluster candidates (from the same cluster survey) with no redshift information in the literature and found that 12 candidates are considered as galaxy clusters in the redshift range from 0.29 to 0.76 with a median of 0.57. These systems are newly discovered clusters in X-rays and optical data. Among them 7 clusters have spectroscopic redshifts for at least one member galaxy.