학술논문
SPT Clusters with DES and HST Weak Lensing. I. Cluster Lensing and Bayesian Population Modeling of Multi-Wavelength Cluster Datasets
Document Type
Working Paper
Author
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.; Rosell, A. Carnero; Kind, M. Carrasco; Carretero, J.; Cawthon, R.; Chang, C.; Chen, R.; Choi, A.; Cordero, J.; Costanzi, M.; da Costa, L. N.; Pereira, M. E. S.; Davis, C.; de Haan, T.; DeRose, J.; Desai, S.; 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.; 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.; Kéruzoré, F.; Khullar, G.; Kim, K.; Kraft, R.; Kuehn, K.; Kuropatkin, N.; 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.; Malagón, A. A. Plazas; 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.; Cid, D. Sanchez; 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.; Zuntz, J.
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Subject
Language
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 $z=0.25$ to 10\% at $z=0.95$, to which we add 2\% in quadrature to account for uncertainties in the impact of baryonic effects. We implement an analysis pipeline that joins the cluster abundance likelihood with a multi-observable likelihood for the SZ, optical richness, and weak-lensing measurements for each individual cluster. We validate that our analysis pipeline can recover unbiased cosmological constraints by analyzing mocks that closely resemble the cluster sample extracted from the SPT-SZ, SPTpol~ECS, and SPTpol~500d surveys and the DES Year~3 and HST-39 weak-lensing datasets. This work represents a crucial prerequisite for the subsequent cosmological analysis of the real dataset.
Comment: submitted to PRD
Comment: submitted to PRD