Hyper Suprime-Cam Subaru Strategic Program Research Articles

The three-year shear catalog of the Subaru Hyper Suprime-Cam SSP Survey

Abstract We present the galaxy shear catalog that will be used for the three-year cosmological weak gravitational lensing analyses using data from the Wide layer of the Hyper Suprime-Cam (HSC) Subaru Strategic Program (SSP) Survey. The galaxy shapes are measured from the i-band imaging data acquired from 2014 to 2019 and calibrated with image simulations that resemble the observing conditions of the survey based on training galaxy images from the Hubble Space Telescope in the COSMOS region. The catalog covers an area of 433.48 deg2 of the northern sky, split into six fields. The mean i-band seeing is ${0{^{\prime \prime}_{.}}59}$. With conservative galaxy selection criteria (e.g., i-band magnitude brighter than 24.5), the observed raw galaxy number density is 22.9 arcmin−2, and the effective galaxy number density is 19.9 arcmin−2. The calibration removes the galaxy property-dependent shear estimation bias to the level |δm| < 9 × 10−3. The bias residual δm shows no dependence on redshift in the range 0 < z ≤ 3. We define the requirements for cosmological weak-lensing science for this shear catalog, and quantify potential systematics in the catalog using a series of internal null tests for systematics related to point-spread function modelling and shear estimation. A variety of the null tests are statistically consistent with zero or within requirements, but (i) there is evidence for PSF model shape residual correlations; and (ii) star–galaxy shape correlations reveal additive systematics. Both effects become significant on >1° scales and will require mitigation during the inference of cosmological parameters using cosmic shear measurements.

Star–Galaxy Image Separation with Computationally Efficient Gaussian Process Classification

Abstract We introduce a novel method for discerning optical telescope images of stars from those of galaxies using Gaussian processes (GPs). Although applications of GPs often struggle in high-dimensional data modalities such as optical image classification, we show that a low-dimensional embedding of images into a metric space defined by the principal components of the data suffices to produce high-quality predictions from real large-scale survey data. We develop a novel method of GP classification hyperparameter training that scales approximately linearly in the number of image observations, which allows for application of GP models to large-size Hyper Suprime-Cam Subaru Strategic Program data. In our experiments, we evaluate the performance of a principal component analysis embedded GP predictive model against other machine-learning algorithms, including a convolutional neural network and an image photometric morphology discriminator. Our analysis shows that our methods compare favorably with current methods in optical image classification while producing posterior distributions from the GP regression that can be used to quantify object classification uncertainty. We further describe how classification uncertainty can be used to efficiently parse large-scale survey imaging data to produce high-confidence object catalogs.

Subaru High-z Exploration of Low-luminosity Quasars (SHELLQs). XVI. 69 New Quasars at 5.8 < z < 7.0

Abstract We present the spectroscopic discovery of 69 quasars at 5.8 < z < 7.0, drawn from the Hyper Suprime-Cam (HSC) Subaru Strategic Program (SSP) imaging survey data. This is the 16th publication from the Subaru High-z Exploration of Low-Luminosity Quasars (SHELLQs) project, and it completes identification of all but the faintest candidates (i.e., i-band dropouts with z AB < 24 and y-band detections, and z-band dropouts with y AB < 24) with Bayesian quasar probability P Q B > 0.1 in the HSC-SSP third public data release (PDR3). The sample reported here also includes three quasars with P Q B < 0.1 at z ∼ 6.6, which we selected in an effort to completely cover the reddest point sources with simple color cuts. The number of high-z quasars discovered in SHELLQs has now grown to 162, including 23 type II quasar candidates. This paper also presents identification of seven galaxies at 5.6 < z < 6.7, an [O iii] emitter at z = 0.954, and 31 Galactic cool stars and brown dwarfs. High-z quasars and galaxies compose 75% and 16%, respectively, of all the spectroscopic SHELLQs objects that pass our latest selection algorithm with the PDR3 photometry. That is, a total of 91% of the objects lie at z > 5.6. This demonstrates that the algorithm has very high efficiency, even though we are probing an unprecedentedly low luminosity population down to M 1450 ∼ −21 mag.

Third data release of the Hyper Suprime-Cam Subaru Strategic Program

AbstractThis paper presents the third data release of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP), a wide-field multi-band imaging survey with the Subaru 8.2 m telescope. HSC-SSP has three survey layers (Wide, Deep, and UltraDeep) with different area coverages and depths, designed to address a wide array of astrophysical questions. This third release from HSC-SSP includes data from 278 nights of observing time and covers about 670 deg2 in all five broad-band filters (grizy) at the full depth (∼26 mag at 5σ depending on filter) in the Wide layer. If we include partially observed areas, the release covers 1470 deg2. The Deep and UltraDeep layers have $\sim\! 80\%$ of the originally planned integration times, and are considered done, as we have slightly changed the observing strategy in order to compensate for various time losses. There are a number of updates in the image processing pipeline. Of particular importance is the change in the sky subtraction algorithm; we subtract the sky on small scales before the detection and measurement stages, which has significantly reduced the number of false detections. Thanks to this and other updates, the overall quality of the processed data has improved since the previous release. However, there are limitations in the data (for example, the pipeline is not optimized for crowded fields), and we encourage the user to check the quality assurance plots as well as a list of known issues before exploiting the data. The data release website is 〈https://hsc-release.mtk.nao.ac.jp〉.

Hα emission in the outskirts of galaxies atz= 0.4

AbstractThis paper reports detections of Hα emission and stellar continuum out to approximately 30 physical kiloparsecs, and Hα directionality in the outskirts of Hα-emitting galaxies (Hα emitters) at $z$ = 0.4. This research adopts narrow-band selected Hα emitters at $z$ = 0.4 from the emission-line object catalog by Hayashi et al. (2020, PASJ, 72, 86), which is based on data in the Deep and Ultradeep layers of the Hyper Suprime-Cam Subaru Strategic Program. Deep narrow- and broad-band images of 8625 Hα emitters across 16.8 deg2 enable us to construct deep composite emission-line and continuum images. The stacked images show diffuse Hα emission (down to ∼5 × 10−20 erg s−1 cm−2 arcsec−2) and stellar continuum (down to ∼5 × 10−22 erg s−1 cm−2 Å−1 arcsec−2), extending beyond 10 kpc at stellar masses >109 $M_\odot$, parts of which may originate from stellar halos. Those radial profiles are broadly consistent with each other. In addition, we obtain a dependence of the Hα emission on the position angle because relatively higher Hα equivalent width has been detected along the minor-axis towards galaxy disks. While the Hα directionality could be attributed to biconical outflows, further research with hydrodynamic simulations is highly demanded to pin down the exact cause.

Photometric Objects Around Cosmic Webs (PAC) Delineated in a Spectroscopic Survey. II. Morphology, Color, and Size Dependences of the Stellar–Halo Mass Relation for Massive Galaxies

Abstract In this paper, we report a robust measurement of the morphology, color, and galaxy size dependences of the stellar–halo mass relation (SHMR) at the high-mass end (1011.3 M ⊙ < M ⋆ < 1011.7 M ⊙) at redshift z s ∼ 0.6. 3 3 Throughout the paper, we use z s for redshift and z for the z-band magnitude. Applying our method, Photometric objects Around Cosmic webs (PAC), developed in a previous work to Baryon Oscillation Spectroscopic Survey and Hyper Suprime-cam Subaru Strategic Program observations, we measure the excess surface density ( n ¯ 2 w p ( r p ) ) of satellites around massive central galaxies with different morphologies indicated by the Sérsic index n. We find that more compact (larger n) central galaxies are surrounded by more satellites. With the abundance matching method, we estimate the halo mass for the central galaxies and find that it increases monotonically with n, solid evidence for a morphology dependence of the SHMR. Specifically, our results show that most compact galaxies (n > 6) have a halo mass around 5.5 times larger than disk galaxies (n < 2). Similarly, using the effective radius R e and the rest-frame u − r color, we find that red (large) galaxies reside in halos that are in average 2.6 (2.3) times more massive than those hosting blue (small) galaxies.

A Wide and Deep Exploration of Radio Galaxies with Subaru HSC (WERGS). VI. Distant Filamentary Structures Pointed Out by High-z Radio Galaxies at z ∼ 4

Abstract We present the environmental properties around high-z radio galaxies (HzRGs) at z ∼ 4, which have been poorly investigated because of their rarity. We use the largest samples of HzRGs and g-dropout galaxy overdense regions at z ∼ 4, which were constructed from the Hyper Suprime-Cam Subaru Strategic Program, to characterize the HzRG environments statistically. We measure the g-dropout galaxy overdensities around 21 HzRGs whose rest-frame 1.4 GHz radio luminosities (L 1.4 GHz) are 1026–27 W Hz−1. We find that the overdensities around the faint HzRGs with L 1.4 GHz ∼ 1026.0–26.5 W Hz−1 tend to be higher than those of the g-dropout galaxies. On the other hand, no significant difference of density environments is found between the luminous HzRGs with L 1.4 GHz ∼ 1026.5–27.0 W Hz−1 and the g-dropout galaxies. The HzRGs are found to occupy more massive halos than g-dropout galaxies through a cross-correlation between the HzRGs and g-dropout galaxies. This trend is more pronounced in the faint HzRGs. These results are consistent with a scenario where HzRGs get older and more massive as the radio luminosity decreases. The HzRGs are expected to trace the progenitors of Local Cluster halos from their calculated halo mass. In addition, we find that surrounding galaxies tend to distribute along the radio jet major axis of the HzRGs at angular distances of ≲500 physical kpc. Our findings imply the onset of the filamentary structures around the HzRGs at z ∼ 4.

HSC-XXL: Baryon budget of the 136 XXL groups and clusters

Abstract We present our determination of the baryon budget for an X-ray-selected XXL sample of 136 galaxy groups and clusters spanning nearly two orders of magnitude in mass (M500 ∼ 1013–1015 M⊙) and the redshift range 0 ≲ z ≲ 1. Our joint analysis is based on the combination of Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) weak-lensing mass measurements, XXL X-ray gas mass measurements, and HSC and Sloan Digital Sky Survey multiband photometry. We carry out a Bayesian analysis of multivariate mass-scaling relations of gas mass, galaxy stellar mass, stellar mass of brightest cluster galaxies (BCGs), and soft-band X-ray luminosity, by taking into account the intrinsic covariance between cluster properties, selection effect, weak-lensing mass calibration, and observational error covariance matrix. The mass-dependent slope of the gas mass–total mass (M500) relation is found to be $1.29_{-0.10}^{+0.16}$, which is steeper than the self-similar prediction of unity, whereas the slope of the stellar mass–total mass relation is shallower than unity; $0.85_{-0.09}^{+0.12}$. The BCG stellar mass weakly depends on cluster mass with a slope of $0.49_{-0.10}^{+0.11}$. The baryon, gas mass, and stellar mass fractions as a function of M500 agree with the results from numerical simulations and previous observations. We successfully constrain the full intrinsic covariance of the baryonic contents. The BCG stellar mass shows the larger intrinsic scatter at a given halo total mass, followed in order by stellar mass and gas mass. We find a significant positive intrinsic correlation coefficient between total (and satellite) stellar mass and BCG stellar mass and no evidence for intrinsic correlation between gas mass and stellar mass. All the baryonic components show no redshift evolution.

Where’s Swimmy?: Mining unique color features buried in galaxies by deep anomaly detection using Subaru Hyper Suprime-Cam data

Abstract We present the Swimmy (Subaru WIde-field Machine-learning anoMalY) survey program, a deep-learning-based search for unique sources using multicolored (grizy) imaging data from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). This program aims to detect unexpected, novel, and rare populations and phenomena, by utilizing the deep imaging data acquired from the wide-field coverage of the HSC-SSP. This article, as the first paper in the Swimmy series, describes an anomaly detection technique to select unique populations as “outliers” from the data-set. The model was tested with known extreme emission-line galaxies (XELGs) and quasars, which consequently confirmed that the proposed method successfully selected $\sim\!\! 60\%$–$70\%$ of the quasars and $60\%$ of the XELGs without labeled training data. In reference to the spectral information of local galaxies at z = 0.05–0.2 obtained from the Sloan Digital Sky Survey, we investigated the physical properties of the selected anomalies and compared them based on the significance of their outlier values. The results revealed that XELGs constitute notable fractions of the most anomalous galaxies, and certain galaxies manifest unique morphological features. In summary, deep anomaly detection is an effective tool that can search rare objects, and, ultimately, unknown unknowns with large data-sets. Further development of the proposed model and selection process can promote the practical applications required to achieve specific scientific goals.

Halo-model Analysis of the Clustering of Photometric Luminous Red Galaxies at 0.10 ≤ z ≤1.05 from the Subaru Hyper Suprime-Cam Survey

Abstract We present the clustering analysis of photometric luminous red galaxies (LRGs) at a redshift range of 0.1 ≤ z ≤ 1.05 using 615,317 photometric LRGs selected from the Hyper Suprime-Cam Subaru Strategic Program, covering ∼124 deg2. Our sample covers a broad range of stellar masses and photometric redshifts and enables a halo occupation distribution analysis to study the redshift and stellar-mass dependence of dark halo properties of LRGs. We find a tight correlation between the characteristic dark halo mass to host central LRGs, M min , and the number density of LRGs, independently of redshifts, indicating that the formation of LRGs is associated with the global environment. The M min of LRGs depends only weakly on the stellar mass M ⋆ at M ⋆ ≲ 1010.75 h −2 M ⊙ at 0.3 < z < 1.05, in contrast to the case for all photometrically selected galaxies, for which M min shows significant dependence on M ⋆ even at low M ⋆. The weak stellar-mass dependence is indicative of the dark halo mass being the key parameter for the formation of LRGs, rather than the stellar mass. Our result suggests that the halo mass of ∼1012.5±0.2 h −1 M ⊙ is the critical mass for an efficient halo quenching due to the halo environment. We compare our result with the result of the hydrodynamical simulation to find that low-mass LRGs at z ∼ 1 will increase their stellar masses by an order of magnitude from z = 1 to 0 through mergers and satellite accretions, and that a large fraction of massive LRGs at z < 0.9 consist of LRGs that recently migrated from massive green valley galaxies or those that evolved from less massive LRGs through mergers and satellite accretions.

Hyper Suprime-Cam Subaru Strategic Program: A Mass-dependent Slope of the Galaxy Size−Mass Relation at z < 1

Abstract We present the galaxy size−mass (R e –M *) distributions using a stellar mass complete sample of ∼1.5 million galaxies, covering ∼100 deg2, with log ( M * / M ⊙ ) > 10.2 ( 9.2 ) over the redshift range 0.2 < z < 1.0 (z < 0.6) from the second public data release of the Hyper Suprime-Cam Subaru Strategic Program. We confirm that, at fixed redshift and stellar mass over the range of log ( M * / M ⊙ ) < 11 , star-forming galaxies are on average larger than quiescent galaxies. The large sample of galaxies with accurate size measurements, thanks to the excellent imaging quality, also enables us to demonstrate that the R e –M * relations of both populations have a form of a broken power law, with a clear change of slopes at a pivot stellar mass M p . For quiescent galaxies, below an (evolving) pivot mass of log ( M p / M ⊙ ) = 10.2 – 10.6 , the relation follows R e ∝ M ∗ 0.1 ; above M p the relation is steeper and follows R e ∝ M * 0.6 – 0.7 . For star-forming galaxies, below log ( M p / M ⊙ ) ∼ 10.7 the relation follows R e ∝ M * 0.2 ; above M p the relation evolves with redshift and follows R e ∝ M * 0.3 – 0.6 . The shallow power-law slope for quiescent galaxies below M p indicates that large low-mass quiescent galaxies have sizes similar to those of their counterpart star-forming galaxies. We take this as evidence that large low-mass quiescent galaxies have been recently quenched (presumably through environment-specific processes) without significant structural transformation. Interestingly, the pivot stellar mass of the R e –M * relations for both populations also coincides with the mass at which half of the galaxy population is quiescent, implying that the pivot mass represents the transition of galaxy growth from being dominated by in situ star formation to being dominated by (dry) mergers.

Subaru Hyper Suprime-Cam revisits the large-scale environmental dependence on galaxy morphology over 360 deg2 atz= 0.3–0.6

AbstractThis study investigates the role of large-scale environments on the fraction of spiral galaxies at z = 0.3–0.6 sliced to three redshift bins of Δz = 0.1. Here, we sample 276220 massive galaxies in a limited stellar mass of 5 × 1010 solar mass (∼M*) over 360 deg2, as obtained from the Second Public Data Release of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). By combining projected two-dimensional density information (Shimakawa et al. 2021, MNRAS, 503, 3896) and the CAMIRA cluster catalog (Oguri et al. 2018, PASJ, 70, S20), we investigate the spiral fraction across large-scale overdensities and in the vicinity of red sequence clusters. We adopt transfer learning to reduce the cost of labeling spiral galaxies significantly and then perform stacking analysis across the entire field to overcome the limitations of sample size. Here we employ a morphological classification catalog by the Galaxy Zoo Hubble (Willett et al., 2017, MNRAS, 464, 4176) to train the deep learning model. Based on 74103 sources classified as spirals, we find moderate morphology–density relations on a 10 comoving Mpc scale, thanks to the wide-field coverage of HSC-SSP. Clear deficits of spiral galaxies have also been confirmed, in and around 1136 red sequence clusters. Furthermore, we verify whether there is a large-scale environmental dependence on rest-frame u − r colors of spiral galaxies; such a tendency was not observed in our sample.

The Intrinsic Shapes of Low Surface Brightness Galaxies (LSBGs): A Discriminant of LSBG Galaxy Formation Mechanisms

Abstract We use the low surface brightness galaxy (LSBG) samples created from the Hyper Suprime-Cam Subaru Strategic Program (781 galaxies), the Dark Energy Survey (20977 galaxies), and the Legacy Survey (selected via H i detection in the Arecibo Legacy Fast ALFA Survey, 188 galaxies) to infer the intrinsic shape distribution of the LSBG population. To take into account the effect of the surface brightness cuts employed when constructing LSBG samples, we simultaneously model both the projected ellipticity and the apparent surface brightness in our shape inference. We find that the LSBG samples are well characterized by oblate spheroids, with no significant difference between red and blue LSBGs. This inferred shape distribution is in good agreement with similar inferences made for ultra-diffuse cluster galaxy samples, indicating that environment does not play a key role in determining the intrinsic shape of LSBGs. We also find some evidence that LSBGs are more thickened than similarly massive high surface brightness dwarfs. We compare our results to intrinsic shape measures from contemporary cosmological simulations, and find that the observed LSBG intrinsic shapes place considerable constraints on the formation path of such galaxies. In particular, LSBG production via the migration of star formation to large radii produces intrinsic shapes in good agreement with our observational findings.

Ionizing radiation from AGNs at z > 3.3 with the Subaru Hyper Suprime-Cam Survey and the CFHT Large Area U-band Deep Survey (CLAUDS)

ABSTRACT We use deep and wide imaging data from the CFHT Large Area U-band Deep Survey (CLAUDS) and the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) to constrain the ionizing radiation (Lyman Continuum, LyC) escape fraction from active galactic nuclei (AGNs) at z ∼ 3–4. For 94 AGNs with spectroscopic redshifts at 3.3 < z < 4.0, we use their U/i-band flux ratios to estimate LyC transmission of individual AGNs. The distribution of their LyC transmission shows values lower than the range of LyC transmission values for IGM of the same redshift range, which suggests that LyC escape fraction of AGNs at z > 3.3 is considerably lower than unity in most cases. We do not find any trend in LyC transmission values depending on their UV luminosities. Based on the photometry of stacked images we find the average flux ratio of LyC and non-ionizing UV photons escaping from the objects (fLyC/fUV)out = 0.182 ± 0.043 for AGNs at 3.3 < z < 3.6, which corresponds to LyC escape fraction fesc = 0.303 ± 0.072 if we assume a fiducial intrinsic SED of AGN. Based on the estimated LyC escape fraction and the UV luminosity function (UVLF) of AGNs, we argue that UV-selected AGNs’ contribution to the LyC emissivity at the epoch is minor, although the size of their contribution largely depends on the shape of the UVLF.

The Sizes of Quasar Host Galaxies in the Hyper Suprime-Cam Subaru Strategic Program

Abstract The relationship between quasars and their host galaxies provides clues on how supermassive black holes (SMBHs) and massive galaxies are jointly assembled. To elucidate this connection, we measure the structural and photometric properties of the host galaxies of ∼5000 Sloan Digital Sky Survey quasars at 0.2 < z < 1 using five-band (grizy) optical imaging from the Hyper Suprime-Cam Subaru Strategic Program. An automated analysis tool is used to forward-model the blended emission of the quasar as characterized by the point-spread function and the underlying host galaxy as a two-dimensional Sérsic profile. We find that quasars are preferentially hosted by massive star-forming galaxies with disklike light profiles. Furthermore, the size distribution of quasar hosts is broad at a given stellar mass and the average values exhibit a size–stellar mass relation as seen with inactive galaxies. In contrast, the sizes of quasar hosts are more compact than those of inactive star-forming galaxies on average, but not as compact as those of quiescent galaxies of similar stellar masses. This is true irrespective of quasar properties, including the bolometric luminosity, Eddington ratio, and black hole mass. These results are consistent with a scenario in which galaxies are concurrently fueling an SMBH and building their stellar bulge from a centrally concentrated gas reservoir. Alternatively, quasar hosts may be experiencing a compaction process in which stars from the disk and inflowing gas are responsible for growing the bulge. In addition, we confirm that the host galaxies of type 1 quasars have a bias of being closer to face-on systems, suggesting that galactic-scale dust can contribute to obscuring the broad-line region.

Brightest cluster galaxies are statistically special from z = 0.3 to z = 1

ABSTRACT We study brightest cluster galaxies (BCGs) in ∼5000 galaxy clusters from the Hyper Suprime-Cam (HSC) Subaru Strategic Program. The sample is selected over an area of 830 deg2 and is uniformly distributed in redshift over the range of z = 0.3−1.0. The clusters have stellar masses in the range of 1011.8−1012.9M⊙. We compare the stellar mass of the BCGs in each cluster to what we would expect if their masses were drawn from the mass distribution of the other member galaxies of the clusters. The BCGs are found to be ‘special’, in the sense that they are not consistent with being a statistical extreme of the mass distribution of other cluster galaxies. This result is robust over the full range of cluster stellar masses and redshifts in the sample, indicating that BCGs are special up to a redshift of z = 1.0. However, BCGs with a large separation from the centre of the cluster are found to be consistent with being statistical extremes of the cluster member mass distribution. We discuss the implications of these findings for BCG formation scenarios.

Photometric redshift estimation with a convolutional neural network: NetZ

Galaxy redshifts are a key characteristic for nearly all extragalactic studies. Since spectroscopic redshifts require additional telescope and human resources, millions of galaxies are known without spectroscopic redshifts. Therefore, it is crucial to have methods for estimating the redshift of a galaxy based on its photometric properties, the so-called photo-z. We have developed NetZ, a new method using a convolutional neural network (CNN) to predict the photo-z based on galaxy images, in contrast to previous methods that often used only the integrated photometry of galaxies without their images. We use data from the Hyper Suprime-Cam Subaru Strategic Program (HSC SSP) in five different filters as the training data. The network over the whole redshift range between 0 and 4 performs well overall and especially in the high-z range, where it fares better than other methods on the same data. We obtained a precision |zpred − zref| of σ = 0.12 (68% confidence interval) with a CNN working for all galaxy types averaged over all galaxies in the redshift range of 0 to ∼4. We carried out a comparison with a network trained on point-like sources, highlighting the importance of morphological information for our redshift estimation. By limiting the scope to smaller redshift ranges or to luminous red galaxies, we find a further notable improvement. We have published more than 34 million new photo-z values predicted with NetZ. This shows that the new method is very simple and swift in application, and, importantly, it covers a wide redshift range that is limited only by the available training data. It is broadly applicable, particularly with regard to upcoming surveys such as the Rubin Observatory Legacy Survey of Space and Time, which will provide images of billions of galaxies with similar image quality as HSC. Our HSC photo-z estimates are also beneficial to the Euclid survey, given the overlap in the footprints of the HSC and Euclid.

Effects of overlapping sources on cosmic shear estimation: Statistical sensitivity and pixel-noise bias

The next generation of dark-energy imaging surveys — so called “Stage-IV” surveys, such as that of the Rubin Observatory Legacy Survey of Space and Time (LSST) — will cross a threshold in the number density of detected sources on the sky that requires qualitatively different image analysis and measurement techniques compared to the current generation of Stage-III surveys.In Stage-IV surveys, a significant amount of the cosmologically useful information is due to sources whose images overlap with those of other sources on the sky.We focus on the weak gravitational lensing probe, for which we expect the largest impact since the cosmic shear signal is primarily encoded in the estimated shapes of observed galaxies and thus directly impacted by overlaps.We introduce a framework based on the Fisher formalism to analyze the effect of the overlapping sources (“blending”) on the estimation of cosmic shear. This method gives concrete predictions for the minimum loss of information due to noise and blending for any choice of “deblending” scheme and shape-measurement algorithm.Our studies account for undetected sources but do not address their full effects and biases they may introduce.We use simulated images and predict this impact of blending for three surveys:the Dark Energy Survey (DES),the Hyper-Suprime Cam Subaru Strategic Program (HSC-SSP),and the Rubin LSST.Our methodology successfully estimates the statistical sensitivity to weak lensing for DES and HSC early results.For LSST, we present the expected loss in statistical sensitivity for the ten-year survey due to blending.We find that for approximately 62% of galaxies that are likely to be detected in full-depth LSST images, at least 1% of the flux in their pixels is from overlapping sources. We also find that the statistical correlations between measures of overlapping galaxies and, to a much lesser extent (0.2%) the higher shot noise level due to their presence, decrease the effective number density of galaxies, N eff, by ∼ 18%. We calculate an upper limit on N eff of 39.4 galaxies per arcmin2 in r band.We study the impact of stars on as a function of stellar density and illustrate the diminishing returns of extending the survey into lower Galactic latitudes.We extend the simulation-based Fisher formalism to predict the expected increase in pixel-noise bias due to blending for maximum-likelihood (ML) shape estimators.We find that noise bias depends sensitively on the particular shape estimator and measure of ensemble-average shape that is used, and properties of the galaxy that include redshift-dependent quantities such as size and luminosity.The source code for these studies is available online.[The documented software developed for the catalog-level studies are available in the open-source LSST DESC github repository https://github.com/LSSTDESC/WeakLensingDeblending. The software for analyzing one or two galaxies with user-defined parameters is in the open-source github repository https://github.com/ismael-mendoza/ShapeMeasurementFisherFormalism.]

Detection of cosmic magnification via galaxy shear-galaxy number density correlation from HSC survey data

We propose a novel method to detect cosmic magnification signals by cross-correlating foreground convergence fields constructed from galaxy shear measurements with background galaxy positional distributions, namely shear-number density correlation. We apply it to the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) survey data. With 27 non-independent data points and their full covariance, $\chi_0^2\approx 34.1$ and $\chi_T^2\approx 24.0$ with respect to the null and the cosmological model with the parameters from HSC shear correlation analyses in Hamana et al. 2020 (arXiv:1906.06041), respectively. The Bayes factor of the two is $\log_{10}B_{T0}\approx 2.2$ assuming equal model probabilities of null and HSC cosmology, showing a clear detection of the magnification signals. Theoretically, the ratio of the shear-number density and shear-shear correlations can provide a constraint on the effective multiplicative shear bias $\bar m$ using internal data themselves. We demonstrate the idea with the signals from our HSC-SSP mock simulations and rescaling the statistical uncertainties to a survey of $15000\deg^2$. For two-bin analyses with background galaxies brighter than $m_{lim}=23$, the combined analyses lead to a forecasted constraint of $\sigma(\bar m) \sim 0.032$, $2.3$ times tighter than that of using the shear-shear correlation alone. Correspondingly, $\sigma(S_8)$ with $S_8=\sigma_8(\Omega_\mathrm{m}/0.3)^{0.5}$ is tightened by $\sim 2.1$ times. Importantly, the joint constraint on $\bar m$ is nearly independent of cosmological parameters. Our studies therefore point to the importance of including the shear-number density correlation in weak lensing analyses, which can provide valuable consistency tests of observational data, and thus to solidify the derived cosmological constraints.

Hundreds of weak lensing shear-selected clusters from the Hyper Suprime-Cam Subaru Strategic Program S19A data

Abstract 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 ∼510 deg2 created using a truncated Gaussian filter, we construct a catalog of 187 shear-selected clusters that correspond to mass map peaks with 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 a 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.