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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 $sim 3000$ 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.
We critically examine the methodology behind the claimed observational detection of halo assembly bias using optically selected galaxy clusters by Miyatake et al. (2016) and More et al. (2016). We mimic the optical cluster detection algorithm and app
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) surve
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 spec
We analyze the clustering of galaxies in the first public data release of the HSC Subaru Strategic Program. Despite the relatively small footprints of the observed fields, the data are an excellent proxy for the deep photometric datasets that will be
This paper presents the second data release of the Hyper Suprime-Cam Subaru Strategic Program, a wide-field optical imaging survey on the 8.2 meter Subaru Telescope. The release includes data from 174 nights of observation through January 2018. The W