The CluMPR Galaxy Cluster-Finding Algorithm and DESI Legacy Survey Galaxy Cluster Catalogue
M. J. Yantovski-Barth, Jeffrey A. Newman, Biprateep Dey, Brett H., Andrews, Michael Eracleous, Jesse Golden-Marx, Rongpu Zhou

TL;DR
This paper introduces CluMPR, a new galaxy cluster-finding algorithm utilizing photometric redshifts and stellar mass data, applied to the DESI Legacy Survey to create a large catalog of high-redshift clusters for cosmology and astrophysics research.
Contribution
The paper presents CluMPR, a novel cluster detection method that improves high-redshift cluster identification using probabilistic membership and mass measurements, applied to a large survey.
Findings
Created a catalog of ~300,000 galaxy cluster candidates up to z=1.
CluMPR effectively identifies high-redshift clusters with minimal contamination.
Discovered candidate strongly-lensed quasars, including known systems.
Abstract
Galaxy clusters enable unique opportunities to study cosmology, dark matter, galaxy evolution, and strongly-lensed transients. We here present a new cluster-finding algorithm, CluMPR (Clusters from Masses and Photometric Redshifts), that exploits photometric redshifts (photo-z's) as well as photometric stellar mass measurements. CluMPR uses a 2-dimensional binary search tree to search for overdensities of massive galaxies with similar redshifts on the sky and then probabilistically assigns cluster membership by accounting for photo-z uncertainties. We leverage the deep DESI Legacy Survey grzW1W2 imaging over one-third of the sky to create a catalogue of ~ 300,000 galaxy cluster candidates out to z = 1, including tabulations of member galaxies and estimates of each cluster's total stellar mass. Compared to other methods, CluMPR is particularly effective at identifying clusters at the…
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Taxonomy
TopicsAstronomy and Astrophysical Research · Galaxies: Formation, Evolution, Phenomena · Stellar, planetary, and galactic studies
