Cluster cosmology with anisotropic boosts: validation of a novel forward modelling analysis and application on SDSS redMaPPer clusters. Issue 4 (25th November 2022)

• Record Type: Journal Article
• Authors: Park, Youngsoo; Sunayama, Tomomi; Takada, Masahiro; Kobayashi, Yosuke; Miyatake, Hironao; More, Surhud; Nishimichi, Takahiro; Sugiyama, Sunao
• Is Part Of: Monthly notices of the Royal Astronomical Society. Volume 518:Issue 4(2023)
• Page Start: 5171
• Page End: 5189
• Publication Date: 2022-11-25
• Subjects: galaxies: clusters: general -- large-scale structure of Universe -- gravitational lensing: weak -- cosmology: theory; Astronomy -- Periodicals; Periodicals; 520.5
• DOI: 10.1093/mnras/stac3410
• Languages: English
• ISSNs: 0035-8711

Abstract

ABSTRACT: We present a novel analysis for cluster cosmology that fully forward models the abundances, weak lensing, and the clustering of galaxy clusters. Our analysis notably includes an empirical model for the anisotropic boosts impacting the lensing and clustering signals of optical clusters. These boosts arise from a preferential selection of clusters surrounded by anisotropic large-scale structure, a consequence of the limited discrimination between line-of-sight interlopers and true cluster members offered by photometric surveys. We validate our analysis via a blind cosmology challenge on mocks, and find that we can obtain tight and unbiased cosmological constraints without informative priors or external calibrations on any of our model parameters. We then apply our analysis on the SDSS redMaPPer clusters, and find results favoring low Ωm and high σ8, combining to yield the lensing strength constraint $S_8 = 0.715_{-0.021}^{+0.024}$ . We investigate potential drivers behind these results through a series of post-unblinding tests, noting that our results are consistent with existing cluster cosmology constraints but clearly inconsistent with other CMB/LSS based cosmology results. From these tests, we find hints that a suppression in the cluster lensing signal may be driving our results.