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arXiv · 2510.10736

Selecting Clusters and Protoclusters via Stellar Mass Density: II. Application to HSC-SSP Observations

Abstract

We present a selection of candidates of clusters and protoclusters of galaxies identified in the photometric data of the HSC-SSP Wide Public Data Release 3 (PDR3), spanning the redshift range $\rm 0.1 \leq z \leq 2$. The selection method, detailed in Vicentin et al. (2025), involves detecting massive galaxies located in high-density regions of matter, identified as potential central dominant galaxies, i.e., (proto)BCGs. Probabilistic criteria based on proximity to the candidate central galaxy and the expected stellar mass of member galaxies are applied to identify likely members of each structure. We produced updated photometric redshift estimates using deep learning methods trained on a dataset combining spectroscopic redshifts from the HSC-SSP Wide PDR3, high-accuracy photometric redshifts from the COSMOS2020 catalog, and mid-infrared data from the unWISE catalog for matched sources. Our method achieves a predicted purity of $\sim 90\%$ in detecting (proto)clusters, with $\gtrsim 65\%$ correctly identifying the (proto)BCG. A total of 16,007 candidate (proto)clusters were identified over an effective area of $\rm \sim 850 \ deg^{2}$ within the HSC-SSP Wide footprint. Comparisons with other existing catalogs reveal a good level of consistency, while also highlighting that different methods yield complementary discoveries. We further compare richness and halo masses from our optical catalog with those from recent X-ray cluster catalogs (eROSITA and MCXC-II), finding a moderate positive correlation and a scatter of $\rm \sim 0.4$ dex. This catalog provides a valuable new set of targets for the Prime Focus Spectrograph (PFS) instrument.

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BibTeXRIS

Marcelo C. Vicentin, Laerte Sodré Jr., Michael A. Strauss, Erik V. R. de Lima, Pablo Araya-Araya. 2025-10-12. Selecting Clusters and Protoclusters via Stellar Mass Density: II. Application to HSC-SSP Observations. https://doi.org/10.3847/1538-4357%2Fadff72

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