SPT clusters with DES and HST weak lensing. I. Cluster lensing and Bayesian population modeling of multiwavelength cluster datasets

Bocquet, S., Grandis, S., Bleem, L. E., Klein, M., Mohr, J. J., Aguena, M., Alarcon, A., Allam, S., Allen, S. W., Alves, O., Amon, A., Ansarinejad, B., Bacon, D., Bayliss, M., Bechtol, K., Becker, M. R., Benson, B. A., Bernstein, G. M., Brodwin, M., Brooks, D., Campos, A., Canning, R. E. A., Carlstrom, J. E., Carnero Rosell, A., Carrasco Kind, M., Carretero, J., Cawthon, R., Chang, C., Chen, R., Choi, A., Cordero, J., Costanzi, M., da Costa, L. N., Pereira, M. E. S., Davis, C., DeRose, J., Desai, S., de Haan, T., De Vicente, J., Diehl, H. T., Dodelson, S., Doel, P., Doux, C., Drlica-Wagner, A., Eckert, K., Elvin-Poole, J., Everett, S., Ferrero, I., Ferté, A., Flores, A. M., Frieman, J., García-Bellido, J., Gatti, M., Giannini, G., Gladders, M. D., Gruen, D., Gruendl, R. A., Harrison, I. ORCID: https://orcid.org/0000-0002-4437-0770, Hartley, W. G., Herner, K., Hinton, S. R., Hollowood, D. L., Holzapfel, W. L., Honscheid, K., Huang, N., Huff, E. M., James, D. J., Jarvis, M., Khullar, G., Kim, K., Kraft, R., Kuehn, K., Kuropatkin, N., Kéruzoré, F., Lee, S., Leget, P.-F., MacCrann, N., Mahler, G., Mantz, A., Marshall, J. L., McCullough, J., McDonald, M., Mena-Fernández, J., Miquel, R., Myles, J., Navarro-Alsina, A., Ogando, R. L. C., Palmese, A., Pandey, S., Pieres, A., Plazas Malagón, A. A., Prat, J., Raveri, M., Reichardt, C. L., Roberson, J., Rollins, R. P., Romer, A. K., Romero, C., Roodman, A., Ross, A. J., Rykoff, E. S., Salvati, L., Sánchez, C., Sanchez, E., Sanchez Cid, D., Saro, A., Schrabback, T., Schubnell, M., Secco, L. F., Sevilla-Noarbe, I., Sharon, K., Sheldon, E., Shin, T., Smith, M., Somboonpanyakul, T., Stalder, B., Stark, A. A., Strazzullo, V., Suchyta, E., Swanson, M. E. C., Tarle, G., To, C., Troxel, M. A., Tutusaus, I., Varga, T. N., von der Linden, A., Weaverdyck, N., Weller, J., Wiseman, P., Yanny, B., Yin, B., Young, M., Zhang, Y. and Zuntz, J. 2024. SPT clusters with DES and HST weak lensing. I. Cluster lensing and Bayesian population modeling of multiwavelength cluster datasets. Physical Review D (particles, fields, gravitation, and cosmology) 110 (8) , 083509. 10.1103/physrevd.110.083509

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Abstract

We present a Bayesian population modeling method to analyze the abundance of galaxy clusters identified by the South Pole Telescope (SPT) with a simultaneous mass calibration using weak gravitational lensing data from the Dark Energy Survey (DES) and the Hubble Space Telescope (HST). We discuss and validate the modeling choices with a particular focus on a robust, weak-lensing-based mass calibration using DES data. For the DES Year 3 data, we report a systematic uncertainty in weak-lensing mass calibration that increases from 1% at

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	Schools > Physics and Astronomy
Additional Information:	License information from Publisher: LICENSE 1: URL: https://link.aps.org/licenses/aps-default-license, Start Date: 2024-10-03
Publisher:	American Physical Society
ISSN:	2470-0010
Date of First Compliant Deposit:	9 December 2024
Date of Acceptance:	23 May 2024
Last Modified:	09 Dec 2024 10:45
URI:	https://orca.cardiff.ac.uk/id/eprint/173064

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