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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 < zcl< 1.0 from the second public data release of the Hyper Suprime-Cam (HSC) Subaru Strategic Program covering ∼427 deg2for 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 < zcl< 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 < zcl< 0.7 and 0.7 < zcl< 1.0. These constraints at 0.4 < zcl< 0.7 and 0.7 < zcl< 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.

This paper presents the second data release of the Hyper Suprime-Cam Subaru Strategic Program, a wide-field optical imaging survey using the 8.2 m Subaru Telescope. The release includes data from 174 nights of observation through 2018 January. The Wide layer data cover about 300 deg$^2$in all five broad-band filters ($grizy$) to the nominal survey exposure (10 min in $gr$and 20 min in $izy$). Partially observed areas are also included in the release; about 1100 deg$^2$is observed in at least one filter and one exposure. The median seeing in the i-band is ${0_{.}^{\prime \prime }6}$, demonstrating the superb image quality of the survey. The Deep (26 deg$^2$) and UltraDeep (4 deg$^2$) data are jointly processed and the UltraDeep-COSMOS field reaches an unprecedented depth of $i\sim 28$at $5 \, \sigma$for point sources. In addition to the broad-band data, narrow-band data are also available in the Deep and UltraDeep fields. This release includes a major update to the processing pipeline, including improved sky subtraction, PSF modeling, object detection, and artifact rejection. The overall data quality has been improved, but this release is not without problems; there is a persistent deblender problem as well as new issues with masks around bright stars. The user is encouraged to review the issue list before utilizing the data for scientific explorations. All the image products as well as catalog products are available for download. The catalogs are also loaded into a database, which provides an easy interface for users to retrieve data for objects of interest. In addition to these main data products, detailed galaxy shape measurements withheld from Public Data Release 1 (PDR1) are now available to the community. The shape catalog is drawn from the S16A internal release, which has a larger area than PDR1 (160 deg$^2$). All products are available at the data release site, https://hsc-release.mtk.nao.ac.jp/.

Constraining the relation between the richness Nand the halo mass Mover 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 ≤ zcl≤ 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 ≤ zcl≤ 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)]2in 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∣ Nfor 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 measure cosmic weak lensing shear power spectra with the Subaru Hyper Suprime-Cam (HSC) survey first-year shear catalog covering 137 deg2of the sky. Thanks to the high effective galaxy number density of ∼17 arcmin−2, even after conservative cuts such as a magnitude cut of i< 24.5 and photometric redshift cut of 0.3 ≤ z≤ 1.5, we obtain a high-significance measurement of the cosmic shear power spectra in four tomographic redshift bins, achieving a total signal-to-noise ratio of 16 in the multipole range 300 ≤ ℓ ≤ 1900. We carefully account for various uncertainties in our analysis including the intrinsic alignment of galaxies, scatters and biases in photometric redshifts, residual uncertainties in the shear measurement, and modeling of the matter power spectrum. The accuracy of our power spectrum measurement method as well as our analytic model of the covariance matrix are tested against realistic mock shear catalogs. For a flat Λ cold dark matter model, we find $S\,_{8}\equiv \sigma _8(\Omega _{\rm m}/0.3)^\alpha =0.800^{+0.029}_{-0.028}$for α = 0.45 ($S\,_8=0.780^{+0.030}_{-0.033}$for α = 0.5) from our HSC tomographic cosmic shear analysis alone. In comparison with Planck cosmic microwave background constraints, our results prefer slightly lower values of S8, although metrics such as the Bayesian evidence ratio test do not show significant evidence for discordance between these results. We study the effect of possible additional systematic errors that are unaccounted for in our fiducial cosmic shear analysis, and find that they can shift the best-fit values of S8by up to ∼0.6 σ in both directions. The full HSC survey data will contain several times more area, and will lead to significantly improved cosmological constraints.

We present optimized source galaxy selection schemes for measuring cluster weak lensing (WL) mass profiles unaffected by cluster member dilution from the Subaru Hyper Suprime-Cam Strategic Survey Program (HSC-SSP). The ongoing HSC-SSP survey will uncover thousands of galaxy clusters to z≲ 1.5. In deriving cluster masses via WL, a critical source of systematics is contamination and dilution of the lensing signal by cluster members, and by foreground galaxies whose photometric redshifts are biased. Using the first-year CAMIRA catalog of ∼900 clusters with richness larger than 20 found in ∼140 deg2of HSC-SSP data, we devise and compare several source selection methods, including selection in color–color space (CC-cut), and selection of robust photometric redshifts by applying constraints on their cumulative probability distribution function (P-cut). We examine the dependence of the contamination on the chosen limits adopted for each method. Using the proper limits, these methods give mass profiles with minimal dilution in agreement with one another. We find that not adopting either the CC-cut or P-cut methods results in an underestimation of the total cluster mass (13% ± 4%) and the concentration of the profile (24% ± 11%). The level of cluster contamination can reach as high as ∼10% at R≈ 0.24 Mpc/hfor low-zclusters without cuts, while employing either the P-cut or CC-cut results in cluster contamination consistent with zero to within the 0.5% uncertainties. Our robust methods yield a ∼60 σ detection of the stacked CAMIRA surface mass density profile, with a mean mass of M200c= [1.67 ± 0.05(stat)] × 1014M⊙/h.

The Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) is a three-layered imaging survey aimed at addressing some of the most important outstanding questions in astronomy today, including the nature of dark matter and dark energy. The survey has been awarded 300 nights of observing time at the Subaru Telescope, and it started in 2014 March. This paper presents the first public data release of HSC-SSP. This release includes data taken in the first 1.7 yr of observations (61.5 nights), and each of the Wide, Deep, and UltraDeep layers covers about 108, 26, and 4 square degrees down to depths of i∼ 26.4, ∼26.5, and ∼27.0 mag, respectively (5 σ for point sources). All the layers are observed in five broad bands (grizy), and the Deep and UltraDeep layers are observed in narrow bands as well. We achieve an impressive image quality of 0${^{\prime\prime}_{.}}$6 in the iband in the Wide layer. We show that we achieve 1%–2% point spread function (PSF) photometry (root mean square) both internally and externally (against Pan-STARRS1), and ∼10 mas and 40 mas internal and external astrometric accuracy, respectively. Both the calibrated images and catalogs are made available to the community through dedicated user interfaces and database servers. In addition to the pipeline products, we also provide value-added products such as photometric redshifts and a collection of public spectroscopic redshifts. Detailed descriptions of all the data can be found online. The data release website is https://hsc-release.mtk.nao.ac.jp.

The Subaru Strategic Program (SSP) is an ambitious multi-band survey using the Hyper Suprime-Cam (HSC) on the Subaru telescope. The Wide layer of the SSP is both wide and deep, reaching a detection limit of i∼ 26.0 mag. At these depths, it is challenging to achieve accurate, unbiased, and consistent photometry across all five bands. The HSC data are reduced using a pipeline that builds on the prototype pipeline for the Large Synoptic Survey Telescope. We have developed a Python-based, flexible framework to inject synthetic galaxies into real HSC images, called SynPipe. Here we explain the design and implementation of SynPipeand generate a sample of synthetic galaxies to examine the photometric performance of the HSC pipeline. For stars, we achieve 1% photometric precision at i∼ 19.0 mag and 6% precision at i∼ 25.0 in the iband (corresponding to statistical scatters of ∼0.01 and ∼0.06 mag respectively). For synthetic galaxies with single-Sérsic profiles, forced CModelphotometry achieves 13% photometric precision at i∼ 20.0 mag and 18% precision at i∼ 25.0 in the iband (corresponding to statistical scatters of ∼0.15 and ∼0.22 mag respectively). We show that both forcedpoint spread function and CModelphotometry yield unbiased color estimates that are robust to seeing conditions. We identify several caveats that apply to the version of HSC pipeline used for the first public HSC data release (DR1) that need to be taking into consideration. First, the degree to which an object is blended with other objects impacts the overall photometric performance. This is especially true for point sources. Highly blended objects tend to have larger photometric uncertainties, systematically underestimated fluxes, and slightly biased colors. Secondly, >20% of stars at 22.5 < i< 25.0 mag can be misclassified as extended objects. Thirdly, the current CModelalgorithm tends to strongly underestimate the half-light radius and ellipticity of galaxy with i> 21.5 mag.

We present and characterize the catalog of galaxy shape measurements that will be used for cosmological weak lensing measurements in the Wide layer of the first year of the Hyper Suprime-Cam (HSC) survey. The catalog covers an area of 136.9 deg2split into six fields, with a mean i-band seeing of 0${^{\prime\prime}_{.}}$58 and 5σ point-source depth of i∼ 26. Given conservative galaxy selection criteria for first-year science, the depth and excellent image quality results in unweighted and weighted source number densities of 24.6 and 21.8 arcmin−2, respectively. We define the requirements for cosmological weak lensing science with this catalog, then focus on characterizing potential systematics in the catalog using a series of internal null tests for problems with point-spread function (PSF) modeling, shear estimation, and other aspects of the image processing. We find that the PSF models narrowly meet requirements for weak lensing science with this catalog, with fractional PSF model size residuals of approximately 0.003 (requirement: 0.004) and the PSF model shape correlation function ρ1< 3 × 10−7(requirement: 4 × 10−7) at 0${^{\circ}_{.}}$5 scales. A variety of galaxy shape-related null tests are statistically consistent with zero, but star–galaxy shape correlations reveal additive systematics on >1° scales that are sufficiently large as to require mitigation in cosmic shear measurements. Finally, we discuss the dominant systematics and the planned algorithmic changes to reduce them in future data reductions.

In this paper, we describe the optical imaging data processing pipeline developed for the Subaru Telescope’s Hyper Suprime-Cam (HSC) instrument. The HSC Pipeline builds on the prototype pipeline being developed by the Large Synoptic Survey Telescope’s Data Management system, adding customizations for HSC, large-scale processing capabilities, and novel algorithms that have since been reincorporated into the LSST codebase. While designed primarily to reduce HSC Subaru Strategic Program (SSP) data, it is also the recommended pipeline for reducing general-observer HSC data. The HSC pipeline includes high-level processing steps that generate coadded images and science-ready catalogs as well as low-level detrending and image characterizations.

Hyper Suprime-Cam (HSC) is a wide-field imaging camera on the prime focus of the 8.2-m Subaru telescope on the summit of Mauna Kea in Hawaii. A team of scientists from Japan, Taiwan, and Princeton University is using HSC to carry out a 300-night multi-band imaging survey of the high-latitude sky. The survey includes three layers: the Wide layer will cover 1400 deg2in five broad bands (grizy), with a 5 σ point-source depth of r≈ 26. The Deep layer covers a total of 26 deg2in four fields, going roughly a magnitude fainter, while the UltraDeep layer goes almost a magnitude fainter still in two pointings of HSC (a total of 3.5 deg2). Here we describe the instrument, the science goals of the survey, and the survey strategy and data processing. This paper serves as an introduction to a special issue of the Publications of the Astronomical Society of Japan, which includes a large number of technical and scientific papers describing results from the early phases of this survey.