Galaxy Clusters from the DESI Legacy Imaging Surveys. I. Cluster Detection

TL;DR

This paper presents a large catalog of over half a million galaxy clusters identified using a fast clustering algorithm on the DESI Legacy Imaging Surveys, enabling extensive statistical studies of galaxy evolution.

Contribution

The study introduces a new, efficient clustering method applied to DESI data, resulting in a comprehensive galaxy cluster catalog with calibrated mass estimates and low false detection rate.

Findings

Detected 540,432 galaxy clusters at z<1.

Median cluster mass is approximately 1.23×10^14 solar masses.

False detection rate is about 3.1%."

Abstract

Based on the photometric redshift catalog of Zou H. et al. (2019), we apply a fast clustering algorithm to identify 540,432 galaxy clusters at $z\lesssim1$ in the DESI legacy imaging surveys, which cover a sky area of about 20,000 deg$^2$. Monte-Carlo simulations indicate that the false detection rate of our detecting method is about 3.1\%. The total masses of galaxy clusters are derived using a calibrated richness--mass relation that are based on the observations of X-ray emission and Sunyaev \& Zel'dovich effect. The median redshift and mass of our detected clusters are about 0.53 and $1.23\times10^{14} M_\odot$, respectively. Comparing with previous clusters identified using the data of the Sloan Digital Sky Survey (SDSS), we can recognize most of them, especially those with high richness. Our catalog will be used for further statistical studies on galaxy clusters and environmental effects on the galaxy evolution, etc.