# The CluMPR Galaxy Cluster-Finding Algorithm and DESI Legacy Survey Galaxy Cluster Catalogue

**Authors:** M. J. Yantovski-Barth, Jeffrey A. Newman, Biprateep Dey, Brett H. Andrews, Michael Eracleous, Jesse Golden-Marx, Rongpu Zhou  
**arXiv:** [2307.10426](https://arxiv.org/abs/2307.10426)  
**Date:** 2023-07-19  
**Summary page:** https://www.summarizepaper.com/en/paper/2307.10426v1/

## Key points

- CluMPR is a new cluster-finding algorithm that uses photometric redshifts and photometric stellar mass measurements to identify galaxy clusters.
- The algorithm utilizes a 2-dimensional binary search tree to search for overdensities of massive galaxies with similar redshifts on the sky.
- Cluster membership is assigned by considering photo-z uncertainties.
- The algorithm leverages the deep DESI Legacy Surveys grzW1W2 imaging data to create a catalogue of approximately 300,000 galaxy cluster candidates up to a redshift of z = 1.
- CluMPR is particularly effective at identifying clusters at high redshifts ranging from z = 0.75 to 1 while minimizing contamination from low-mass groups.
- It is ideal for identifying strongly lensed high-redshift supernovae and quasars, which can be used for studying cosmology, dark matter, and stellar astrophysics.
- The paper is organized into sections describing the data products used, the CluMPR algorithm, summary graphs and data summarizing the characteristics of the galaxy cluster catalogue, results and applications, and potential future extensions of this work.
- Appendices provide details regarding calibration of the algorithm and information about catalogues assembled in this work.
- A cosmology with specific parameters is assumed throughout the paper based on Bennett et al.(2014).
- The publicly available code and catalogues produced in this work offer opportunities for further research in cosmology, dark matter, galaxy evolution, and strongly-lensed transients.

## Summary

This paper presents a new cluster-finding algorithm called CluMPR (Clusters from Masses and Photometric Redshifts) that utilizes photometric redshifts (photo-z's) and photometric stellar mass measurements to identify galaxy clusters. The algorithm uses a 2-dimensional binary search tree to search for overdensities of massive galaxies with similar redshifts on the sky and assigns cluster membership by considering photo-z uncertainties. The authors leverage the deep DESI Legacy Surveys grzW1W2 imaging data over one-third of the sky to create a catalogue of approximately 300,000 galaxy cluster candidates up to a redshift of z = 1. This catalogue includes information on member galaxies and estimates of each cluster's total stellar mass. Compared to other methods, CluMPR is particularly effective at identifying clusters at high redshifts ranging from z = 0.75 to 1, while minimizing contamination from low-mass groups. This makes it ideal for identifying strongly lensed high-redshift supernovae and quasars, which serve as powerful probes for studying cosmology, dark matter, and stellar astrophysics. The paper is organized as follows: Section 2 describes the data products used to generate the galaxy cluster catalogue, including multi-band images obtained from the DESI Legacy Imaging Surveys. Section 3 provides a detailed description of the CluMPR algorithm and explains the process of calibrating galaxy cluster parameters and assigning member galaxies. In Section 4, summary graphs and data summarizing the characteristics of the CluMPR galaxy cluster catalogue are presented. The results, applications, and potential future extensions of this work are summarized in Section 5. The Data Availability section provides information about publicly accessible locations where all data and code related to this paper can be found, including the cluster catalogues and candidate lensed quasar catalogues. Appendices A and B provide details regarding the calibration of the algorithm, while Appendix C describes a set of candidate gravitationally-lensed quasars that have been identified. Appendix D provides information about the columns of all catalogues assembled in this work. Throughout the paper, a cosmology with 𝐻0 = 70 𝑘𝑚/𝑠/𝑀 𝑝𝑐 , Ω𝑚 = 0.286 ,and Ω𝜆 = 0.714 is assumed based on Bennett et al.(2014). The DESI Legacy Imaging Surveys data used in this study covers over one third of the sky and includes multi band images in three optical bands (g ,r ,z )and two infrared bands from WISE (W1 ,W2 ).Photometric redshifts were obtained from Zhou et al. (2021),and stellar mass estimates were obtained from Zhou et al. (2023).The analysis applies several photometric cuts to select galaxies for analysis ,ensuring good measurements of photometric redshifts and stellar masses with minimal contamination from stars .These cuts include restricting objects to have a z magnitude < 21(since photo -z's are only reliable for z band magnitude < 21 ),specific Gaia photometric mean magnitudes or astrometric excess noise values to remove stars ,and excluding point spread function objects by setting TYPE != PSF . Overall ,this paper presents a comprehensive approach to identifying galaxy clusters using CluMPR and provides valuable insights into cosmology ,dark matter ,galaxy evolution ,and strongly -lensed transients .The publicly available code and catalogues produced in this work offer opportunities for further research and exploration in these areas .