Synthetic galaxy clusters and observations based on Dark Energy Survey Year 3 Data

Journal Article · 18 November 2021 · Monthly Notices of the Royal Astronomical Society

DOI: https://doi.org/10.1093/mnras/stab3269 · OSTI ID:1835147

Varga, T. N. ; Gruen, D. ; Seitz, S.; MacCrann, N. ; Sheldon, E.; Hartley, W. G.; Amon, A.; Choi, A.; Palmese, A. ; Zhang, Y.; Becker, M. R. ; McCullough, J.; Rozo, E.; Rykoff, E. S.; To, C.; Grandis, S.; Bernstein, G. M. ; Dodelson, S.; Eckert, K.; Everett, S. ; Gruendl, R. A.; Harrison, I. ; Herner, K.; Rollins, R. P.; Sevilla-Noarbe, I.; Troxel, M. A.; Yanny, B.; Zuntz, J. ; Diehl, H. T.; Jarvis, M.; Aguena, M. ; Allam, S.; Annis, J.; Bertin, E. ; Bhargava, S.; Brooks, D.; Carnero Rosell, A. ; Carrasco Kind, M. ; Carretero, J. ; Costanzi, M. ; da Costa, L. N.; Pereira, M. E. S.; De Vicente, J. ; Desai, S.; Dietrich, J. P.; Ferrero, I. ; Flaugher, B.; García-Bellido, J. ; Gaztanaga, E. ; Gerdes, D. W.; Gschwend, J.; Gutierrez, G.; Hinton, S. R. ; Honscheid, K.; Jeltema, T.; Kuehn, K.; Kuropatkin, N.; Maia, M. A. G.; March, M. ; Melchior, P. ; Menanteau, F.; Miquel, R.; Morgan, R.; Myles, J. ; Paz-Chinchón, F.; Plazas, A. A. ; Romer, A. K.; Sanchez, E.; Scarpine, V.; Schubnell, M.; Serrano, S.; Smith, M. ; Soares-Santos, M.; Suchyta, E. ; Swanson, M. E. C.; Tarle, G.; Thomas, D. ; Weller, J.

ABSTRACT We develop a novel data-driven method for generating synthetic optical observations of galaxy clusters. In cluster weak lensing, the interplay between analysis choices and systematic effects related to source galaxy selection, shape measurement, and photometric redshift estimation can be best characterized in end-to-end tests going from mock observations to recovered cluster masses. To create such test scenarios, we measure and model the photometric properties of galaxy clusters and their sky environments from the Dark Energy Survey Year 3 (DES Y3) data in two bins of cluster richness $$\lambda \in [30; 45)$$, $$\lambda \in [45; 60)$$ and three bins in cluster redshift ($$z\in [0.3; 0.35)$$, $$z\in [0.45; 0.5)$$ and $$z\in [0.6; 0.65)$$. Using deep-field imaging data, we extrapolate galaxy populations beyond the limiting magnitude of DES Y3 and calculate the properties of cluster member galaxies via statistical background subtraction. We construct mock galaxy clusters as random draws from a distribution function, and render mock clusters and line-of-sight catalogues into synthetic images in the same format as actual survey observations. Synthetic galaxy clusters are generated from real observational data, and thus are independent from the assumptions inherent to cosmological simulations. The recipe can be straightforwardly modified to incorporate extra information, and correct for survey incompleteness. New realizations of synthetic clusters can be created at minimal cost, which will allow future analyses to generate the large number of images needed to characterize systematic uncertainties in cluster mass measurements.

• Research Organization: Argonne National Laboratory (ANL), Argonne, IL (United States); Brookhaven National Laboratory (BNL), Upton, NY (United States); Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States); Univ. of Michigan, Ann Arbor, MI (United States); University of Michigan, Ann Arbor, MI (United States)
• Sponsoring Organization: European Union (EU); Germany Research Foundation (DFG); MINECO; National Science Foundation (NSF); USDOE; USDOE Office of Science (SC), High Energy Physics (HEP)
• Contributing Organization: DES Collaboration
• Grant/Contract Number: AC02-06CH11357; AC02-07CH11359; AC02-76SF00515; SC0012704; SC0019193
• OSTI ID: 1835147
• Report Number(s): BNL-223069-2022-JAAM; FERMILAB-PUB--21-049-AE; arXiv:2102.10414
• Journal Information: Monthly Notices of the Royal Astronomical Society, Journal Name: Monthly Notices of the Royal Astronomical Society Journal Issue: 4 Vol. 509; ISSN 0035-8711
• Publisher: Oxford University PressCopyright Statement
• Country of Publication: United Kingdom
• Language: English