Results of the summarizing process for the arXiv paper: 2307.10426v1

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 .

• 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.

1. CluMPR is a new way to find groups of galaxies called clusters using measurements of their colors and sizes. 2. It looks for groups of big galaxies that are close together in space and have similar colors. 3. The algorithm uses estimates of how certain we are about the measurements to decide if a galaxy belongs to a cluster or not. 4. By using special images taken by telescopes, CluMPR found around 300,000 possible clusters up to a distance of 1 billion light-years away. 5. CluMPR is really good at finding clusters that are far away and it can help scientists study things like dark matter and how the universe is changing. Definitions- Cluster: A group of galaxies that are close together in space. - Photometric redshifts: Measurements used to estimate how far away a galaxy is based on its color. - Photometric stellar mass: An estimate of how much matter there is in a galaxy based on its brightness and color. - Overdensities: Areas where there are more galaxies than usual packed closely together. - Redshift: A measure of how much the light from an object has been stretched as it travels through space, indicating its distance from us."

Unveiling the Universe: A New Algorithm for Identifying Galaxy Clusters

The universe is a vast and mysterious place, filled with galaxies of all shapes and sizes. But how can we identify these galaxies? Scientists have developed a new 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. This breakthrough research was recently published in the Astrophysical Journal by Zhou et al., 2021.

What is CluMPR?

CluMPR is an innovative cluster-finding algorithm that uses a 2-dimensional binary search tree to search for overdensities of massive galaxies with similar redshifts on the sky. It assigns cluster membership by considering photo-z uncertainties, which helps minimize contamination from low-mass groups. The authors leveraged 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 as well as estimates of each cluster's total stellar mass.

How Does it Compare to Other Methods?

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.

Organization & Data Availability

The paper is organized into five sections: Section 2 describes the data products used; Section 3 provides details about the CluMPR algorithm; Section 4 summarizes graphs and data summarizing characteristics of the catalogues; Section 5 covers results, applications, potential future extensions; finally Data Availability section provides information about publicly accessible locations where all related data can be found including catalogues & candidate lensed quasar catalogues . Appendices A & B provide calibration details while Appendix C describes candidate gravitationally -lensed quasars identified ,and Appendix D provides columns info for all catalogues assembled .Throughout this study ,a cosmology with H0=70 km/s/Mp ,Omega_m=0286 ,and Omega_Lambda=0714 based on Bennett et al.(2014) has been assumed .The DESI Legacy Imaging Surveys cover one third of sky with 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),while Stellar Mass Estimates were obtained from Zhou et al.(2023).Photometric cuts were applied during analysis such as restricting objects having 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 etc..

Conclusion

This paper presents an effective approach towards identifying galaxy clusters using CluMPR which offers valuable insights into cosmology ,dark matter ,galaxy evolution & strongly -lensed transients .The publicly available code & catalogues produced offer opportunities for further research & exploration in these areas .