Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances, Weak Lensing, and Galaxy Correlations

To, C.; Krause, E.; Rozo, Eduardo; Wu, Hao-Yi; Gruen, D.; Wechsler, Risa H.; Eifler, T. F.; Rykoff, E. S.; Costanzi, M.; Becker, Matthew R.; Bernstein, G. M.; Blazek, Jonathan; Bocquet, S.; Bridle, Sarah; Cawthon, R.; Choi, A.; Crocce, M.; Davis, C.; DeRose, J.; Drlica-Wagner, A.; Elvin-Poole, J.; Fang, X.; Farahi, Arya; Friedrich, Oliver; Gatti, M.; Gaztañaga, E.; Giannantonio, T.; Hartley, W. G.; Hoyle, B.; Jarvis, Mike; MacCrann, N.; McClintock, Thomas; Miranda, Vivian; Pereira, M. E. S.; Park, Y.; Porredon, A.; Prat, J.; Rau, Markus; Ross, Ashley J.; Samuroff, S.; Sánchez, C.; Sevilla-Noarbe, I.; Sheldon, E.; Troxel, M. A.; Varga, T. N.; Vielzeuf, P.; Zhang, Y.; Zuntz, Joe; Abbott, T. M. C.; Aguena, M.; Amon, A.; Annis, J.; Ávila, S.; Bertin, E.; Bhargava, S.; Brooks, D.; Burke, D. L.; Rosell, A. Carnero; Kind, M. Carrasco; Carretero, J.; Chang, C.; Conselice, C. J.; Costa, L. N. da; Davis, Tamara M.; Desai, S.; Diehl, H. T.; Dietrich, J. P.; Everett, S.; Evrard, A. E.; Ferrero, I.; Flaugher, B.; Fosalba, P.; Frieman, J.; García-Bellido, J.; Gruendl, R. A.; Gutiérrez, G.; Hinton, S. R.; Hollowood, D. L.; Honscheid, K.; Huterer, Dragan; James, D. J.; Jeltema, T.; Krön, Richard G.; Kuêhn, K.; Kuropatkin, N.; Lima, M.; Maia, M. A. G.; Marshall, J. L.; Menanteau, F.; Miquel, R.; Morgan, R.; Muir, J.; Myles, J.; Palmese, A.; Paz-Chinchón, F.; Plazas, A. A.; Romer, A. K.; Roodman, A.; Sánchez, E.; Santiago, B.; Scarpine, V.; Serrano, S.; Smith, M.; Suchyta, E.; Swanson, M. E. C.; Tarlè, G.; Thomas, D.; Tucker, D. L.; Weller, J.; Wester, W.; Wilkinson, R. D.

doi:10.1103/physrevlett.126.141301

Cited by 82 publications

(57 citation statements)

References 55 publications

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“…First, we find that our systematics parameters are successfully self-calibrated. We find anisotropic boost amplitudes ranging between 15-20%, which matches our findings from simulations as well as the observational constraints from To et al (2021). We also find miscentering fractions ∼ 15% and miscentering scales around 0.2-0.3 Mpc/ℎ, con-SDSS Fiducial 0 .…”

Section: Resultssupporting

confidence: 88%

“…From these studies, SP20 found that optically identified clusters were likely to be embedded in LSS elongated along the line-of-sight, e.g., filaments aligned with the line-of-sight, and importantly that this anisotropy led to large-scale boosts of the cluster lensing and cluster clustering signals (also see Osato et al 2018, for a similar discussion). These anisotropic boosts, which have now been observationally confirmed by To et al (2021), have significant implications for the joint cluster cosmology framework, as they break the isotropic halo model generally assumed in making lensing mass calibrations for clusters. If not properly modeled, these anisotropic boosts inevitably leads to errors in the cluster mass calibrations.…”

Section: Introductionmentioning

confidence: 69%

“…To et al (2021) presents another important cosmology result incorporating clusters, but is not directly comparable to this study as it also uses galaxy data (see alsoSalcedo et al 2020). …”

mentioning

confidence: 86%

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Cluster cosmology with anisotropic boosts: Validation of a novel forward modeling analysis and application on SDSS redMaPPer clusters

Park¹,

Sunayama²,

Takada³

et al. 2021

Preprint

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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 Ω m and high 𝜎 8 , combining to yield the lensing strength constraint 𝑆 8 = 0.718 +0.016 −0.015 . 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.

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Section: Resultssupporting

confidence: 88%

Section: Introductionmentioning

confidence: 69%

See 1 more Smart Citation

Cluster cosmology with anisotropic boosts: Validation of a novel forward modeling analysis and application on SDSS redMaPPer clusters

Park¹,

Sunayama²,

Takada³

et al. 2021

Preprint

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“…The 0.07 shift in 𝑏 𝑣 is within the stated 1𝜎 error of G15 (Δ𝑏 𝑣 = 0.08) so the revised mass estimate remains consistent with the wide 68% confidence interval of the original F16 estimate determined using the G15 constraints. The revised EVL normalization also remains consistent with existing weak lensing estimates, including the recent multi-probe estimate of To et al (2021).…”

Section: Updating the Mass -Richness Normalization Of F16supporting

confidence: 82%

Galaxy Velocity Bias in Cosmological Simulations: Towards Percent-level Calibration

Anbajagane,

Aung,

Evrard

et al. 2021

Preprint

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Galaxy cluster masses, rich with cosmological information, can be estimated from internal dark matter (DM) velocity dispersions, which in turn can be observationally inferred from satellite galaxy velocities. However, galaxies are biased tracers of the DM, and the bias can vary over host halo and galaxy properties as well as time. We precisely calibrate the velocity bias, 𝑏 𝑣 -defined as the ratio of galaxy and DM velocity dispersions -as a function of redshift, host halo mass, and galaxy stellar mass threshold (𝑀 ★, sat ), for massive halos (𝑀 200c > 10 13.5 M ) from five cosmological simulations: IllustrisTNG, Magneticum, Bahamas + Macsis, The Three Hundred Project, and MultiDark Planck-2. We first compare scaling relations for galaxy and DM velocity dispersion across simulations; the former is estimated using a new ensemble velocity likelihood method that is unbiased for low galaxy counts per halo, while the latter uses a local linear regression. The simulations show consistent trends of 𝑏 𝑣 increasing with 𝑀 200c and decreasing with redshift and 𝑀 ★, sat . The ensemble-estimated theoretical uncertainty in 𝑏 𝑣 is 2-3%, but becomes percent-level when considering only the three highest resolution simulations. We update the mass-richness normalization previously estimated by Farahi et al. (2016) for an SDSS redMaPPer cluster sample. The improved accuracy of our 𝑏 𝑣 estimates reduces the mass normalization uncertainty from 22% to 8%, demonstrating that dynamical estimation techniques can be competitive with weak lensing in calibrating population mean masses. We discuss necessary steps for further improving this precision. Our estimates for 𝑏 𝑣 (𝑀 200c , 𝑀 ★, sat , 𝑧) are made publicly available.

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“…Projection effects have a variety of origins, such as the anisotropic distribution of satellite galaxies within the halo, and the presence of large-scale structure along the line-of-sight to the cluster. While the calibration of the Mvir-richness relation now routinely includes mis-centering effects when modelling cluster ∆Σ profiles (e.g., Murata et al 2018Murata et al , 2019McClintock et al 2019), projection bias is still a major issue (e.g., Costanzi et al 2019;Sunayama et al 2020;Abbott et al 2020b;To et al 2021a). In this paper, we show that M -based proxies using both larger apertures or outer mass display stacked ∆Σ profiles that are consistent with having negligible mis-centering effect and projection bias (see Figure 9 and § 6.3) -this is very exciting as it suggests that outer mass measures such as M , [50,100] directly trace central galaxies and could yield a more simple selection function than richness-based methods.…”

Section: Implications For Optical Cluster Findingmentioning

confidence: 99%

The Outer Stellar Mass of Massive Galaxies: A Simple Tracer of Halo Mass with Scatter Comparable to Richness and Reduced Projection Effects

Huang,

Leauthaud,

Bradshaw

et al. 2021

Preprint

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Using the weak gravitational lensing data from the Hyper Suprime-Cam Subaru Strategic Program (HSC survey), we study the potential of different stellar mass estimates in tracing halo mass. We consider galaxies with log 10 (M /M )> 11.5 at 0.2 < z < 0.5 with carefully measured light profiles, and clusters from the redMaP-Per and CAMIRA richness-based algorithms. We devise a method (the "Top-N test") to evaluate the scatter in the halo mass-observable relation for different tracers, and to inter-compare halo mass proxies in four number density bins using stacked galaxygalaxy lensing profiles. This test reveals three key findings. Stellar masses based on CModel photometry and aperture luminosity within R <30 kpc are poor proxies of halo mass. In contrast, the stellar mass of the outer envelope is an excellent halo mass proxy. The stellar mass within R = [50, 100] kpc, M ,[50,100] , has performance comparable to the state-of-the-art richness-based cluster finders at log 10 M vir 14.0 and could be a better halo mass tracer at lower halo masses. Finally, using N-body simulations, we find that the lensing profiles of massive halos selected by M , [50,100] are consistent with the expectation for a sample without projection or mis-centering effects. Richness-selected clusters, on the other hand, display an excess at R ∼ 1 Mpc in their lensing profiles, which may suggest a more significant impact from selection biases. These results suggest that M -based tracers have distinct advantages in identifying massive halos, which could open up new avenues for cluster cosmology. The codes and data used in this work can be found here:

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Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances, Weak Lensing, and Galaxy Correlations

Cited by 82 publications

References 55 publications

Cluster cosmology with anisotropic boosts: Validation of a novel forward modeling analysis and application on SDSS redMaPPer clusters

Cluster cosmology with anisotropic boosts: Validation of a novel forward modeling analysis and application on SDSS redMaPPer clusters

Galaxy Velocity Bias in Cosmological Simulations: Towards Percent-level Calibration

The Outer Stellar Mass of Massive Galaxies: A Simple Tracer of Halo Mass with Scatter Comparable to Richness and Reduced Projection Effects

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