We present cosmological constraints derived from peak counts, minimum counts, and the angular power spectrum of the Subaru Hyper SuprimeCam firstyear (HSC Y1) weak lensing shear catalogue. Weak lensing peak and minimum counts contain nonGaussian information and hence are complementary to the conventional twopoint statistics in constraining cosmology. In this work, we forwardmodel the three summary statistics and their dependence on cosmology, using a suite of Nbody simulations tailored to the HSC Y1 data. We investigate systematic and astrophysical effects including intrinsic alignments, baryon feedback, multiplicative bias, and photometric redshift uncertainties. We mitigate the impact of these systematics by applying cuts on angular scales, smoothing scales, signaltonoise ratio bins, and tomographic redshift bins. By combining peaks, minima, and the power spectrum, assuming a flatΛCDM model, we obtain $S_{8} \equiv \sigma _8\sqrt{\Omega _m/0.3}= 0.810^{+0.022}_{0.026}$, a 35 per cent tighter constraint than that obtained from the angular power spectrum alone. Our results are in agreement with other studies using HSC weak lensing shear data, as well as with Planck 2018 cosmology and recent CMB lensing constraints from the Atacama Cosmology Telescope and the South Pole Telescope.
 Award ID(s):
 1638509
 NSFPAR ID:
 10256994
 Date Published:
 Journal Name:
 Publications of the Astronomical Society of Japan
 Volume:
 72
 Issue:
 1
 ISSN:
 00046264
 Format(s):
 Medium: X
 Sponsoring Org:
 National Science Foundation
More Like this

ABSTRACT 
ABSTRACT We present cosmological constraints from the Subaru Hyper SuprimeCam (HSC) firstyear weak lensing shear catalogue using convolutional neural networks (CNNs) and conventional summary statistics. We crop 19 $3\times 3\, \mathrm{{deg}^2}$ subfields from the firstyear area, divide the galaxies with redshift 0.3 ≤ z ≤ 1.5 into four equally spaced redshift bins, and perform tomographic analyses. We develop a pipeline to generate simulated convergence maps from cosmological Nbody simulations, where we account for effects such as intrinsic alignments (IAs), baryons, photometric redshift errors, and point spread function errors, to match characteristics of the real catalogue. We train CNNs that can predict the underlying parameters from the simulated maps, and we use them to construct likelihood functions for Bayesian analyses. In the Λ cold dark matter model with two free cosmological parameters Ωm and σ8, we find $\Omega _\mathrm{m}=0.278_{0.035}^{+0.037}$, $S_8\equiv (\Omega _\mathrm{m}/0.3)^{0.5}\sigma _{8}=0.793_{0.018}^{+0.017}$, and the IA amplitude $A_\mathrm{IA}=0.20_{0.58}^{+0.55}$. In a model with four additional free baryonic parameters, we find $\Omega _\mathrm{m}=0.268_{0.036}^{+0.040}$, $S_8=0.819_{0.024}^{+0.034}$, and $A_\mathrm{IA}=0.16_{0.58}^{+0.59}$, with the baryonic parameters not being wellconstrained. We also find that statistical uncertainties of the parameters by the CNNs are smaller than those from the power spectrum (5–24 per cent smaller for S8 and a factor of 2.5–3.0 smaller for Ωm), showing the effectiveness of CNNs for uncovering additional cosmological information from the HSC data. With baryons, the S8 discrepancy between HSC firstyear data and Planck 2018 is reduced from $\sim 2.2\, \sigma$ to $0.3\!\!0.5\, \sigma$.

ABSTRACT We constrain the matter density Ωm and the amplitude of density fluctuations σ8 within the ΛCDM cosmological model with shear peak statistics and angular convergence power spectra using mass maps constructed from the first three years of data of the Dark Energy Survey (DES Y3). We use tomographic shear peak statistics, including crosspeaks: peak counts calculated on maps created by taking a harmonic space product of the convergence of two tomographic redshift bins. Our analysis follows a forwardmodelling scheme to create a likelihood of these statistics using Nbody simulations, using a Gaussian process emulator. We take into account the uncertainty from the remaining, largely unconstrained ΛCDM parameters (Ωb, ns, and h). We include the following lensing systematics: multiplicative shear bias, photometric redshift uncertainty, and galaxy intrinsic alignment. Stringent scale cuts are applied to avoid biases from unmodelled baryonic physics. We find that the additional nonGaussian information leads to a tightening of the constraints on the structure growth parameter yielding $S_8~\equiv ~\sigma _8\sqrt{\Omega _{\mathrm{m}}/0.3}~=~0.797_{0.013}^{+0.015}$ (68 per cent confidence limits), with a precision of 1.8 per cent, an improvement of 38 per cent compared to the angular power spectra only case. The results obtained with the angular power spectra and peak counts are found to be in agreement with each other and no significant difference in S8 is recorded. We find a mild tension of $1.5 \, \sigma$ between our study and the results from Planck 2018, with our analysis yielding a lower S8. Furthermore, we observe that the combination of angular power spectra and tomographic peak counts breaks the degeneracy between galaxy intrinsic alignment AIA and S8, improving cosmological constraints. We run a suite of tests concluding that our results are robust and consistent with the results from other studies using DES Y3 data.more » « less

ABSTRACT We present cosmological constraints from the analysis of angular power spectra of cosmic shear maps based on data from the first three years of observations by the Dark Energy Survey (DES Y3). Our measurements are based on the pseudoCℓ method and complement the analysis of the twopoint correlation functions in real space, as the two estimators are known to compress and select Gaussian information in different ways, due to scale cuts. They may also be differently affected by systematic effects and theoretical uncertainties, making this analysis an important crosscheck. Using the same fiducial Lambda cold dark matter model as in the DES Y3 realspace analysis, we find ${S_8 \equiv \sigma _8 \sqrt{\Omega _{\rm m}/0.3} = 0.793^{+0.038}_{0.025}}$, which further improves to S8 = 0.784 ± 0.026 when including shear ratios. This result is within expected statistical fluctuations from the realspace constraint, and in agreement with DES Y3 analyses of nonGaussian statistics, but favours a slightly higher value of S8, which reduces the tension with the Planck 2018 constraints from 2.3σ in the real space analysis to 1.5σ here. We explore less conservative intrinsic alignments models than the one adopted in our fiducial analysis, finding no clear preference for a more complex model. We also include small scales, using an increased Fourier mode cutoff up to $k_{\rm max}={5}\, {h}\, {\rm Mpc}^{1}$, which allows to constrain baryonic feedback while leaving cosmological constraints essentially unchanged. Finally, we present an approximate reconstruction of the linear matter power spectrum at present time, found to be about 20 per cent lower than predicted by Planck 2018, as reflected by the lower S8 value.more » « less

ABSTRACT We present posterior sample redshift distributions for the Hyper SuprimeCam Subaru Strategic Program Weak Lensing threeyear (HSC Y3) analysis. Using the galaxies’ photometry and spatial crosscorrelations, we conduct a combined Bayesian Hierarchical Inference of the sample redshift distributions. The spatial crosscorrelations are derived using a subsample of Luminous Red Galaxies (LRGs) with accurate redshift information available up to a photometric redshift of z < 1.2. We derive the photometrybased constraints using a combination of two empirical techniques calibrated on spectroscopic and multiband photometric data that cover a spatial subset of the shear catalogue. The limited spatial coverage induces a cosmic variance error budget that we include in the inference. Our crosscorrelation analysis models the photometric redshift error of the LRGs to correct for systematic biases and statistical uncertainties. We demonstrate consistency between the sample redshift distributions derived using the spatial crosscorrelations, the photometry, and the posterior of the combined analysis. Based on this assessment, we recommend conservative priors for sample redshift distributions of tomographic bins used in the threeyear cosmological Weak Lensing analyses.