Galaxy Clusters Selected via the Sunyaev-Zel'dovich Effect in 5 year data from the SPT-3G Main Survey
L. E. Bleem, M. Klein, K. Kornoelje, S. Bocquet, J. A. Sobrin, M. Aguena, E. Anderes, A. J. Anderson, F. Andrade-Oliveira, B. Ansarinejad, M. Archipley, L. Balkenhol, D. R. Barron, P. S. Barry, M. Bayliss, K. Benabed, A. N. Bender, B. A. Benson, F. Bianchini, F. R. Bouchet, D. Brooks, D. L. Burke, M. Calzadilla, R. Camilleri, E. Camphuis, M. G. Campitiello, J. E. Carlstrom, A. Carnero Rosell, J. Carretero, J. Carron, C. L. Chang, P. M. Chichura, A. Chokshi, T. -L. Chou, A. Coerver, M. Costanzi, T. M. Crawford, L. N. da Costa, C. Daley, T. M. Davis, T. de Haan, J. De Vicente, S. Desai, K. R. Dibert, H. T. Diehl, M. A. Dobbs, M. Doohan, D. Dutcher, S. Everett, G. Evrard, C. Feng, K. R. Ferguson, N. C. Ferree, K. Fichman, B. Flaugher, B. Floyd, K. Fosdick, A. Foster, S. Galli, A. E. Gambrel, A. K. Gao, J. García-Bellido, F. Ge, M. D. Gladders, S. Grandis, F. Guidi, S. Guns, G. Gutierrez, N. W. Halverson, S. R. Hinton, E. Hivon, G. P. Holder, D. L. Hollowood, W. L. Holzapfel, J. C. Hood, A. Hryciuk, N. Huang, T. Jhaveri, S. Kent, F. Kéruzoré, A. R. Khalife, G. Khullar, L. Knox, K. Kuehn, C. -L. Kuo, O. Lahav, K. Levy, Y. Li, A. E. Lowitz, C. Lu, G. P. Lynch, T. J. Maccarone, G. Mahler, A. S. Maniyar, J. L. Marshall, E. S. Martsen, M. McDonald, J. Mena-Fernández, F. Menanteau, M. Millea, R. Miquel, J. J. Mohr, J. Montgomery, J. Myles, Y. Nakato, T. Natoli, R. C. Nichol, V. Novosad, R. L. C. Ogando, Y. Omori, A. Ouellette, Z. Pan, K. A. Phadke, A. A. Plazas Malagón, A. W. Pollak, A. Porredon, K. Prabhu, J. Prat, W. Quan, S. Raghunathan, M. Rahimi, A. Rahlin, C. L. Reichardt, A. K. Romer, M. Rouble, J. E. Ruhl, E. Sanchez, D. Sanchez Cid, T. Schrabback, I. Sevilla-Noarbe, A. C. Silva Oliveira, A. Simpson, T. Somboonpanyakul, A. A. Stark, E. Suchyta, M. E. C. Swanson, C. Tandoi, C. To, C. Trendafilova, J. D. Vieira, A. G. Vieregg, V. Vikram, A. Vitrier, Y. Wan, N. Weaverdyck, J. Weller, N. Whitehorn, W. L. K. Wu, M. R. Young, J. A. Zebrowski, J. Zhan
astro-ph.CO, astro-ph.GA
Submitted: 2026-07-01
Comments: Cluster sample online available at https://pole.uchicago.edu/public/data/spt3g-clusters/
Code: https://github.com/gvernard/SLED_api
License: http://creativecommons.org/licenses/by/4.0/
The gist: We report a new galaxy cluster catalog, selected using the thermal Sunyaev-Zel'dovich (SZ) effect, from 5 years of observations of the SPT-3G Main field.
Terminology
Abstract
We report a new galaxy cluster catalog, selected using the thermal Sunyaev-Zel'dovich (SZ) effect, from 5 years of observations of the SPT-3G Main field. Drawn from arcminute-resolution data with white noise levels of 3.2, 2.5, and 8.9 mu K-arcmin at 95, 150, and 220 GHz, respectively, the sample consists of 8,892 cluster candidates detected above significance xi=4, with an expected purity of >82% (4,480 at xi 5 with purity >99%). Using optical and infrared data we have confirmed 7,190 candidates as clusters. The sample spans a mass range 7.9 times 10 13 M/h 70 < M 500c < 1.6 times 10 15 M/h 70 with a median mass of 1.65 times 10 14 M/h 70, and a redshift range of 0.037<z 2 with a median redshift of z med = 0.73; 1,780 clusters are at z>1 and 271 at z>1.5. Compared to previous SZ cluster samples from South Pole Telescope and Atacama Cosmology Telescope data, the SPT-3G sample is highly consistent in mass and redshift but is significantly deeper, with per-cluster detection signal-to-noise 2-4 times higher and a cluster density of 4.5 confirmed clusters/deg squared. We cross match with eRASS1 cluster and point source catalogs, finding 1,279 and 1,319 matches, respectively. The SPT and eROSITA cluster mass estimates are in relatively good agreement. We perform a series of validation checks using both internal data splits and comparisons to external samples. These tests show increasing correlated (dusty) emission with redshift, with a about17 times larger 220 GHz temperature increment for clusters at z about1.5 than z about0.25, but only weak evidence for correlated synchrotron emission. Finally, a number of clusters are flagged as candidate strong gravitational lenses.
Sources
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- Does Machine Learning Work? A Comparative Analysis of Strong Gravitational Lens Searches in the Dark Energy Survey
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- Image Marker
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