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Register a new userWeak lensing Analysis of X-Ray-selected XXL Galaxy Groups and Clusters with Subaru HSC Data
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We present a weak-lensing analysis of X-ray galaxy groups and clusters selected from the XMM-XXL survey using the first-year data from the Hyper Suprime-Cam (HSC) Subaru Strategic Program. Our joint weak-lensing and X-ray analysis focuses on 136 spectroscopically confirmed X-ray-selected systems at 0.031 < z < 1.033 detected in the 25sqdeg XXL-N region. We characterize the mass distributions of individual clusters and establish the concentration-mass (c-M) relation for the XXL sample, by accounting for selection bias and statistical effects, and marginalizing over the remaining mass calibration uncertainty. We find the mass-trend parameter of the c-M relation to be beta = -0.07 pm 0.28 and the normalization to be c200 = 4.8 pm 1.0 (stat) pm 0.8 (syst) at M200=10^{14}Msun/h and z = 0.3. We find no statistical evidence for redshift evolution. Our weak-lensing results are in excellent agreement with dark-matter-only c-M relations calibrated for recent LCDM cosmologies. The level of intrinsic scatter in c200 is constrained as sigma(ln[c200]) < 24% (99.7% CL), which is smaller than predicted for the full population of LCDM halos. This is likely caused in part by the X-ray selection bias in terms of the relaxation state. We determine the temperature-mass (Tx-M500) relation for a subset of 105 XXL clusters that have both measured HSC lensing masses and X-ray temperatures. The resulting Tx-M500 relation is consistent with the self-similar prediction. Our Tx-M500 relation agrees with the XXL DR1 results at group scales, but has a slightly steeper mass trend, implying a smaller mass scale in the cluster regime. The overall offset in the Tx-M500 relation is at the $1.5sigma$ level, corresponding to a mean mass offset of (34pm 20)%. We also provide bias-corrected, weak-lensing-calibrated M200 and M500 mass estimates of individual XXL clusters based on their measured X-ray temperatures.
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We utilize the galaxy shape catalogue from the first-year data release of the Subaru Hyper Suprime-cam Survey (HSC) to study the dark matter content of galaxy groups in the Universe using weak gravitational lensing. As our lens sample, we use galaxy groups that have been spectroscopically selected from the Galaxy Mass and Assembly galaxy survey in approximately 100 sq. degrees of the sky that overlap with the HSC survey. We restrict our analysis to the 1587 groups with at least five group members. We divide these galaxy groups into six bins each of galaxy group luminosity and group member velocity dispersion and measure the coherent tangential ellipticity pattern on background HSC galaxies imprinted by weak gravitational lensing. We measure the weak lensing signal with a signal-to-noise ratio of 55 and 51 for these two different selections, respectively. We use a Bayesian halo model framework to infer the halo mass distribution of our galaxy groups binned in the two different observable properties and obtain constraints on the power-law scaling relation between mean halo masses and the two group observable properties. We obtain a 5 percent constraint on the amplitude of the scaling relation between halo mass and group luminosity with $langle Mrangle = (0.81pm0.04)times10^{14}h^{-1}M_odot$ for $L_{rm grp}=10^{11.5}h^{-2}L_odot$, and a power-law index of $alpha=1.01pm0.07$. We also obtain a 5-percent constraint on the amplitude of the scaling relation between halo mass and velocity dispersion with $langle Mrangle=(0.93pm0.05)times10^{14}h^{-1}M_odot$ for $sigma=500{,rm kms}^{-1}$ and a power-law index $alpha=1.52pm0.10$, although these scaling relations are sensitive to the exact cuts applied to the number of group members. Comparisons with similar scaling relations from the literature indicate that our results are consistent, but have significantly reduced errors.
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 $0.1leq z_{rm cl}leq 1.0$ with $Ngeq 15$ using the HSC first-year shear catalog covering $sim$$140$ ${rm deg^2}$. The exquisite depth and image quality of the HSC survey allow us to measure lensing signals around the high-redshift clusters at $0.7leq z_{rm cl}leq 1.0$ with a signal-to-noise ratio of 19 in the comoving radius range $0.5lesssim Rlesssim 15 h^{-1}{rm Mpc}$. We constrain richness-mass relations $P(ln N|M,z)$ of the 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 which are proportional to $ln (1+z)$ and $[ln (1+z)]^{2}$ into 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 the redshift. We show that the constraints on the mean relation $langle M|N rangle$ are consistent between the Planck and WMAP models, whereas the scatter values $sigma_{ln M|N}$ 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.
We use the Hyper Suprime-Cam Subaru Strategic Program S19A shape catalog to construct weak lensing shear-selected cluster samples. From aperture mass maps covering $sim 510$~deg$^2$ created using a truncated Gaussian filter, we construct a catalog of 187 shear-selected clusters that correspond to mass map peaks with the signal-to-noise ratio larger than 4.7. Most of the shear-selected clusters have counterparts in optically-selected clusters, from which we estimate the purity of the catalog to be higher than 95%. The sample can be expanded to 418 shear-selected clusters with the same signal-to-noise ratio cut by optimizing the shape of the filter function and by combining weak lensing mass maps created with several different background galaxy selections. We argue that dilution and obscuration effects of cluster member galaxies can be mitigated by using background source galaxy samples and adopting the filter function with its inner boundary larger than about $2$. The large samples of shear-selected clusters that are selected without relying on any baryonic tracer are useful for detailed studies of cluster astrophysics and cosmology.
We present a joint shear-and-magnification weak-lensing analysis of a sample of 16 X-ray-regular and 4 high-magnification galaxy clusters at 0.19<z<0.69 selected from the Cluster Lensing And Supernova survey with Hubble (CLASH). Our analysis uses wide-field multi-color imaging, taken primarily with Suprime-Cam on the Subaru Telescope. From a stacked shear-only analysis of the X-ray-selected subsample, we detect the ensemble-averaged lensing signal with a total signal-to-noise ratio of ~25 in the radial range of 200 to 3500kpc/h. The stacked tangential-shear signal is well described by a family of standard density profiles predicted for dark-matter-dominated halos in gravitational equilibrium, namely the Navarro-Frenk-White (NFW), truncated variants of NFW, and Einasto models. For the NFW model, we measure a mean concentration of $c_{200c}=4.01^{+0.35}_{-0.32}$ at $M_{200c}=1.34^{+0.10}_{-0.09} 10^{15}M_{odot}$. We show this is in excellent agreement with Lambda cold-dark-matter (LCDM) predictions when the CLASH X-ray selection function and projection effects are taken into account. The best-fit Einasto shape parameter is $alpha_E=0.191^{+0.071}_{-0.068}$, which is consistent with the NFW-equivalent Einasto parameter of $sim 0.18$. We reconstruct projected mass density profiles of all CLASH clusters from a joint likelihood analysis of shear-and-magnification data, and measure cluster masses at several characteristic radii. We also derive an ensemble-averaged total projected mass profile of the X-ray-selected subsample by stacking their individual mass profiles. The stacked total mass profile, constrained by the shear+magnification data, is shown to be consistent with our shear-based halo-model predictions including the effects of surrounding large-scale structure as a two-halo term, establishing further consistency in the context of the LCDM model.
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 $sim 3000$ optically selected galaxy clusters detected by the independent cluster-finding algorithm CAMIRA over a wide redshift range of $0.1<z_{rm cl}<1.0$ from the second public data release of the Hyper Suprime-Cam (HSC) Subaru Strategic Program covering $sim 427~{rm deg}^2$ 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 $0.7<z_{rm cl}<1.0$, 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 $1sigma$ precisions of $sim 15%$ at $0.4<z_{rm cl}<0.7$ and $0.7<z_{rm cl}<1.0$. These constraints are more consistent with the model predictions ($lesssim 1sigma$) than their $20%$ smaller values as suggested by the previous studies with the redMaPPer ($sim 2sigma$). 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 that 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.
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