ABSTRACT
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∝ (M500)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 M500 = 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.
Simulations of AGN Feedback in Galaxy Clusters and Groups: Impact on Gas Fractions and the
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