The richness-to-mass relation of CAMIRA galaxy clusters from weak-lensing magnification in the Subaru Hyper Suprime-Cam survey

Abstract

We present a statistical weak-lensing magnification analysis on an optically selected sample of 3029 CAMIRA galaxy clusters with richness N > 15 in the Subaru Hyper Suprime-Cam (HSC) survey. The CAMIRA sample spans a wide redshift range of 0.2 z < 1.1. We use two distinct populations of color-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 8.29σ , which is dominated by the high-z background. We forward-model the observed magnification data to constrain the richness-to-mass (N-M) relation for the CAMIRA sample. In this work, we can only constrain the normalization of the N-M relation by employing informative priors on the mass and redshift trends, and on the intrinsic scatter at fixed mass. The resulting scaling relation is N ∝ M 500 0.91±0.14 (1 + z) −0.45±0.75 , with a characteristic richness of N = (19.63 ± 3.16) and intrinsic log-normal scatter of 0.14 ± 0.07 at M 500 = 10 14 h −1 M . With the derived N-M relation, we provide magnification-calibrated mass estimates of individual CAMIRA clusters, with the typical uncertainty of ≈ 38% and ≈ 30% at richness≈ 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.

Cluster–galaxy weak lensing

“…2.6.3). Lensing magnification provides complementary and independent observational alternatives to gravitational shear, especially at high redshift where source galaxies are more difficult to resolve (Van Waerbeke et al 2010;Hildebrandt et al 2011;Ford et al 2014;Chiu et al 2016Chiu et al , 2020.…”

“…In real observations, we apply different cuts (e.g., size, magnitude, and color cuts) in source selection for measuring the shear and magnification effects, thus leading to different source-redshift distributions. In contrast to the former effect, measuring the effect of magnification bias does not require source galaxies to be spatially resolved, but it does require a stringent flux limit against incompleteness effects (Hildebrandt 2016;Chiu et al 2020).…”

“…It is therefore reasonable to use the single source-plane approximation for calculating the magnification bias of depleted source populations with a ( 0. In the regime of density enhancement (a [ 1), on the other hand, interpreting the observed lensing signal requires detailed knowledge of the intrinsic source luminosity function (see, e.g., Chiu et al 2016Chiu et al , 2020, especially in the nonlinear regime where the flux amplification factor is correspondingly large (say, lJ1:5). For example, a blue distant population of background galaxies is observed to have a well-defined redshift distribution that is fairly symmetric and peaked at a mean redshift of hz s i $ 2 (e.g., Lilly et al 2007;Medezinski et al 2010).…”

“…To avoid significant contamination and alleviate this problem as much as possible, one often relies on a stringent color-color selection (Sect. 4.1) to measure the lensing magnification signal from a distinct population of background galaxies (e.g., Broadhurst et al 2005b;Umetsu and Broadhurst 2008;Umetsu et al 2011bUmetsu et al , 2014Ziparo et al 2016;Chiu et al 2016Chiu et al , 2020. If well-calibrated photo-z PDFs are available from multiband observations, the impact of cluster contamination can be characterized and assessed by statistically decomposing the photo-z PDF P(z) into the cluster and random-field populations (e.g., Gruen et al 2014;Chiu et al 2020).…”

“…Thus, the weak shear lensing signal, as measured from small but coherent image distortions in galaxy shapes, can provide a direct measure of the projected mass distribution of galaxy clusters (e.g., Kaiser and Squires 1993;Fahlman et al 1994;Okabe and Umetsu 2008). On the other hand, lensing magnification can influence the observed surface number density of background galaxies seen behind clusters, by enhancing their apparent fluxes and expanding the area of sky (e.g., Broadhurst et al 1995Broadhurst et al , 2005bTaylor et al 1998;Umetsu et al 2011b;Chiu et al 2020). The former effect increases the source counts above the limiting flux, whereas the latter reduces the effective observing area in the source plane, thus decreasing the observed number of sources per unit solid angle.…”