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Recent constraints on the splashback radius around optically selected galaxy clusters from the redMaPPer cluster-finding algorithm in the literature have shown that the observed splashback radius is |${\sim}20\%$| smaller than that predicted by N -body simulations. We present analyses on the splashback features around ∼ 3000 optically selected galaxy clusters detected by the independent cluster-finding algorithm CAMIRA over a wide redshift range of 0.1 < z cl < 1.0 from the second public data release of the Hyper Suprime-Cam (HSC) Subaru Strategic Program covering ∼427 deg2 for the cluster catalog. We detect the splashback feature from the projected cross-correlation measurements between the clusters and photometric galaxies over the wide redshift range, including for high-redshift clusters at 0.7 < z cl < 1.0, thanks to deep HSC images. We find that constraints from red galaxy populations only are more precise than those without any color cut, leading to 1σ precisions of |${\sim}15\%$| at 0.4 < z cl < 0.7 and 0.7 < z cl < 1.0. These constraints at 0.4 < z cl < 0.7 and 0.7 < z cl < 1.0 are more consistent with the model predictions (≲1σ) than their |$20\%$| smaller values as suggested by the previous studies with the redMaPPer (∼2σ). We also investigate selection effects of the optical cluster-finding algorithms on the observed splashback features by creating mock galaxy catalogs from a halo occupation distribution model, and find such effects to be sub-dominant for the CAMIRA cluster-finding algorithm. We also find that the redMaPPer-like cluster-finding algorithm induces a smaller inferred splashback radius in our mock catalog, especially at lower richness, which can well explain the smaller splashback radii in the literature. In contrast, these biases are significantly reduced when increasing its aperture size. This finding suggests that aperture sizes of optical cluster finders that are smaller than splashback feature scales can induce significant biases on the inferred location of a splashback radius. [ABSTRACT FROM AUTHOR]

We present a statistical weak-lensing magnification analysis on an optically selected sample of 3029 CAMIRA (Cluster finding Algorithm based on Multiband Identification of Red-sequence gAlaxies) galaxy clusters with richness N > 15 at redshift 0.2 ≤ z < 1.1 in the Subaru Hyper Suprime-Cam survey. We use two distinct populations of colour-selected, flux-limited background galaxies, namely the low- z and high- z samples at mean redshifts of ≈1.1 and ≈1.4, respectively, from which to measure the weak-lensing magnification signal by accounting for cluster contamination as well as masking effects. Our magnification bias measurements are found to be uncontaminated according to validation tests against the 'null-test' samples for which the net magnification bias is expected to vanish. The magnification bias for the full CAMIRA sample is detected at a significance level of 9.51σ, which is dominated by the high- z background. We forward-model the observed magnification data to constrain the normalization of the richness-to-mass (N – M) relation for the CAMIRA sample with informative priors on other parameters. The resulting scaling relation is N ∝ (M 500)0.92 ± 0.13(1 + z)−0.48 ± 0.69, with a characteristic richness of N = 17.72 ± 2.60 and intrinsic lognormal scatter of 0.15 ± 0.07 at M 500 = 1014  h −1 M⊙. With the derived N – M relation, we provide magnification-calibrated mass estimates of individual CAMIRA clusters, with the typical uncertainty of ≈39 and ≈32  per cent at richness of ≈20 and ≈40, respectively. We further compare our magnification-inferred N – M relation with those from the shear-based results in the literature, finding good agreement. [ABSTRACT FROM AUTHOR]

We present results from a set of simulations designed to constrain the weak lensing shear calibration for the Hyper Suprime-Cam (HSC) survey. These simulations include HSC observing conditions and galaxy images from the Hubble Space Telescope (HST), with fully realistic galaxy morphologies and the impact of nearby galaxies included. We find that the inclusion of nearby galaxies in the images is critical to reproducing the observed distributions of galaxy sizes and magnitudes, due to the non-negligible fraction of unrecognized blends in ground-based data, even with the excellent typical seeing of the HSC survey (0.58 arcsec in the i band). Using these simulations, we detect and remove the impact of selection biases due to the correlation of weights and the quantities used to define the sample (S/N and apparent size) with the lensing shear. We quantify and remove galaxy property-dependent multiplicative and additive shear biases that are intrinsic to our shear estimation method, including an ∼10 per cent-level multiplicative bias due to the impact of nearby galaxies and unrecognized blends. Finally, we check the sensitivity of our shear calibration estimates to other cuts made on the simulated samples, and find that the changes in shear calibration are well within the requirements for HSC weak lensing analysis. Overall, the simulations suggest that the weak lensing multiplicative biases in the first-year HSC shear catalogue are controlled at the 1 per cent level. [ABSTRACT FROM AUTHOR]

Constraining the relation between the richness N and the halo mass M over a wide redshift range for optically selected clusters is a key ingredient for cluster-related science in optical surveys, including the Subaru Hyper Suprime-Cam (HSC) survey. We measure stacked weak-lensing profiles around 1747 HSC CAMIRA clusters over a redshift range of 0.1 ≤ z cl ≤ 1.0 with N ≥ 15 using the HSC first-year shear catalog covering ∼140 deg2. The exquisite depth and image quality of the HSC survey allow us to measure lensing signals around high-redshift clusters at 0.7 ≤ z cl ≤ 1.0 with a signal-to-noise ratio of 19 within the comoving radius range |$0.5\lesssim R\lesssim 15\, h^{-1}\:{\rm Mpc}$|⁠. We constrain the richness–mass relations P (ln  N  ∣  M, z) of HSC CAMIRA clusters assuming a log-normal distribution without informative priors on model parameters, by jointly fitting to the lensing profiles and abundance measurements under both Planck and WMAP cosmological models. We show that our model gives acceptable p -values when we add redshift-dependent terms proportional to ln (1 + z) and [ln (1 + z)]2 in the mean and scatter relations of P (ln  N  ∣  M, z). Such terms presumably originate from the variation of photometric redshift errors as a function of redshift. We show that constraints on the mean relation 〈 M  ∣  N 〉 are consistent between the Planck and WMAP models, whereas the scatter values σln  M  ∣  N for the Planck model are systematically larger than those for the WMAP model. We also show that the scatter values for the Planck model increase toward lower richness values, whereas those for the WMAP model are consistent with constant values as a function of richness. This result highlights the importance of the scatter in the mass–richness relation for cluster cosmology. [ABSTRACT FROM AUTHOR]