Hyper Suprime-Cam Year 3 Results: Cosmology from Cosmic Shear Two-point Correlation Functions

TL;DR

This study delivers a blinded, tomographic cosmic shear analysis of the HSC-Y3 data to constrain S8 in a flat ΛCDM framework, incorporating 23 parameters to marginalize key systematics such as baryonic feedback, intrinsic alignments, photo-z, and PSF effects. By calibrating redshift distributions with CAMIRA-LRG cross-correlations and using a BACCO emulator for linear growth with HMCode for nonlinearities, the authors obtain S8 = 0.769_{-0.034}^{+0.031} and Ω_m = 0.256_{-0.044}^{+0.056}, with a robust consistency check showing no significant bias from modeling or B-mode systematics. They find a ~2σ tension with Planck 2018, consistent with other weak-lensing surveys, and demonstrate robustness across subfields and analysis variations, while highlighting redshift calibration systematics in the high-z bins. The results affirm the efficacy of HSC-Y3 for precision cosmology, outline strategies for controlling systematics in the final-year data, and set the stage for tighter constraints with future, larger surveys.

Abstract

We perform a blinded cosmology analysis with cosmic shear two-point correlation functions (2PCFs) measured from more than 25 million galaxies in the Hyper Suprime-Cam three-year shear catalog in four tomographic redshift bins ranging from 0.3 to 1.5. After conservative masking and galaxy selection, the survey covers 416 deg$^2$ of the northern sky with an effective galaxy number density of 15 arcmin$^{-2}$ over the four redshift bins. The 2PCFs adopted for cosmology analysis are measured in the angular range: $7.1 < θ/{\rm arcmin} < 56.6$ for $ξ_+$ and $31.2 <θ/{\rm arcmin} < 248$ for $ξ_-$, with a total signal-to-noise ratio of 26.6. We apply a conservative, wide, flat prior on the photometric redshift errors on the last two tomographic bins, and the relative magnitudes of the cosmic shear amplitude across four redshift bins allow us to calibrate the photometric redshift errors. With this flat prior on redshift errors, we find $Ω_{\rm m}=0.256_{-0.044}^{+0.056}$ and $S_8\equiv σ_8 \sqrt{Ω_{\rm m}/0.3}=0.769_{-0.034}^{+0.031}$ (both 68\% CI) for a flat $Λ$ cold dark matter cosmology. We find, after unblinding, that our constraint on $S_8$ is consistent with the Fourier space cosmic shear and the 3$\times$2pt analyses on the same HSC dataset. We carefully study the potential systematics from astrophysical and systematic model uncertainties in our fiducial analysis using synthetic data, and report no biases (including projection bias in the posterior space) greater than $0.5σ$ in the estimation of $S_8$. Our analysis hints that the mean redshifts of the two highest tomographic bins are higher than initially estimated. In addition, a number of consistency tests are conducted to assess the robustness of our analysis. Comparing our result with Planck-2018 cosmic microwave background observations, we find a ~$2σ$ tension for the $Λ$CDM model.

Figures (32)

• Figure 1: The map of effective number density $n_\text{eff}$ of galaxies across four redshift bins. A rectangular region in GAMA09H ($132.5 < \mathrm{ra}< 140$ [deg], $1.6<\mathrm{dec}<5$ [deg]) with very good seeing, a smaller number of input single exposures, and significant fourth-order PSF shape residual is removed from the original catalog.
• Figure 2: The comparison between $n(z)$ distributions (solid line) estimated by the joint calibration with CAMIRA-LRG sample HSC3_photoz_Rau2022 and those estimated by stacking the DEmPz (dashed lines), dNNz (dot-dashed lines) and mizuki (dotted lines) photo-$z$ posteriors from individual galaxies. The shaded grey histogram is the number density as a function of redshift of CAMIRA-LRGs used to calibrate the $n(z)$ distributions of the solid lines. The median redshifts for the four redshift bins (solid black lines) are 0.44, 0.75, 1.03 and 1.31, and the median redshift for the overall sample is 0.80 . The dashed black lines in the last two redshift bins are the $n(z)$ distributions after after the self-calibration in parameter inference (see text for details).
• Figure 3: The ten 2PCFs including four autocorrelations and six cross-correlations between the four tomographic redshift bins (labeled with 1--4). This plot shows the 2PCFs on scales $5.3 < \theta < 76$ [arcmin] for $\xi_+$, and $23.2 < \theta < 248$ [arcmin] for $\xi_-$. The unshaded region refers to the fiducial scale cut: $7.1 < \theta < 56.6$ [arcmin] for $\xi_+$, and $31.2 < \theta < 248$ [arcmin] for $\xi_-$ . The errorbars are estimated with mock catalogs. The total SNR of the measured 2PCFs is $26.6$ . The solid lines are the best-fit model of our fiducial analysis, as discussed in Section \ref{['subsec:inter_fid']}.
• Figure 4: The normalized covariance matrix (correlation coefficients) estimated with mock catalogs. Note that this plot shows the coefficients on scales $5.3 < \theta < 76$ [arcmin] for $\xi_+$, and $23.2 < \theta < 248$ [arcmin] for $\xi_-$. The fiducial scale cut --- $7.1 < \theta < 56.6$ [arcmin] for $\xi_+$, and $31.2 < \theta < 248$ [arcmin] for $\xi_-$ --- is a subset of this scale range.
• Figure 5: $B$-modes on 2PCFs measured from the HSC-Y3 catalog in four tomographic bins. The $p$-value of the measured $B$-modes relative to a model of exactly zero is 0.1143 for $\xi_+$ and 0.1237 for $\xi_-$, as shown in the legend. The errorbars are estimated with mock catalogs. The unshaded region refers to the fiducial scale cut.