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Xiangchong Li

Publications and source records attributed to Xiangchong Li.

At least 37 records · Page 2Linked to original sources

A Differentiable Perturbation-based Weak Lensing Shear Estimator

Upcoming imaging surveys will use weak gravitational lensing to study the large-scale structure of the Universe, demanding sub-percent accuracy for precise cosmic shear measurements. We present a new differentiable implementation of our perturbation-based shear estimator (FPFS), using JAX, which is publicly available as part of a new suite of analytic shear algorithms called AnaCal. This code can analytically calibrate the shear response of any nonlinear observable constructed with the FPFS shapelets and detection modes utilizing auto-differentiation (AD), generalizing the formalism to include a family of shear estimators with corrections for detection and selection biases. Using the AD capability of JAX, it calculates the full Hessian matrix of the non-linear observables, which improves the previously presented second-order noise bias correction in the shear estimation. As an illustration of the power of the new AnaCal framework, we optimize the effective galaxy number density in the space of the generalized shear estimators using an LSST-like galaxy image simulation for the ten-year LSST. For the generic shear estimator, the magnitude of the multiplicative bias $|m|$ is below $3\times 10^{-3}$ (99.7% confidence interval), and the effective galaxy number density is improved by 5%. We also discuss some planned future additions to the AnaCal software suite to extend its applicability beyond the FPFS measurements.

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Three-Dimensional Reconstruction of Weak-Lensing Mass Maps with a Sparsity Prior. II. Weighing Triaxial Cluster Halos

Continuing work presented in Li et al. (2021), we performed a series of tests to our high-resolution three-dimensional mass map reconstruction algorithm \splinv{}. We test the mass reconstruction accuracy against realistic mock catalogs generated using shear field produced by triaxial halos with the inner density profile of $ρ\propto r^{-1}$ and of $ρ\propto r^{-1.5}$. The galaxy shape noise is modeled based on the Year-1 Subaru Hyper Suprime-Cam (HSC) Survey. After reviewing mathematical details of our algorithm and dark matter halo models, we determine an optimal value of the coefficient of the adaptive LASSO regression penalty term for single halo reconstruction. We successfully measure halo masses for massive triaxial halos; the mass determination accuracy is 5 percent for halos with $M = 10^{14.6}~M_\odot$ at $0.0625\leq z \leq 0.2425$, and 5 percent for those with $10^{14.8}~M_\odot$ at $0.0625\leq z \leq 0.4675$, and 20 percent for $M= 10^{15.0} ~M_\odot$ and $M=10^{15.2}~M_\odot$ in the redshift range $0.0625\leq z \leq 0.4675$. The redshift estimate accuracy is consistently below $Δz /z \leq 0.05$ for the above halo masses in the range $0.1525\leq z \leq 0.4675$. We also demonstrate that the orientation of triaxial halos and systematic error in our halo model do not affect reconstruction result significantly. Finally, we present results from reconstruction of mass distribution using shear catalogs produced by multiple halos, to show \splinv{}'s capability using realistic shear maps from ongoing and future galaxy surveys.

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Hyper Suprime-Cam Year 3 Results: Cosmology from Cosmic Shear Two-point Correlation Functions

We perform a blinded cosmology analysis with cosmic shear two-point correlation functions (2PCFs) measured from more than 25 million galaxies in the Hyper Suprime-Cam three-year shear catalog in four tomographic redshift bins ranging from 0.3 to 1.5. After conservative masking and galaxy selection, the survey covers 416 deg$^2$ of the northern sky with an effective galaxy number density of 15 arcmin$^{-2}$ over the four redshift bins. The 2PCFs adopted for cosmology analysis are measured in the angular range: $7.1 < θ/{\rm arcmin} < 56.6$ for $ξ_+$ and $31.2 <θ/{\rm arcmin} < 248$ for $ξ_-$, with a total signal-to-noise ratio of 26.6. We apply a conservative, wide, flat prior on the photometric redshift errors on the last two tomographic bins, and the relative magnitudes of the cosmic shear amplitude across four redshift bins allow us to calibrate the photometric redshift errors. With this flat prior on redshift errors, we find $Ω_{\rm m}=0.256_{-0.044}^{+0.056}$ and $S_8\equiv σ_8 \sqrt{Ω_{\rm m}/0.3}=0.769_{-0.034}^{+0.031}$ (both 68\% CI) for a flat $Λ$ cold dark matter cosmology. We find, after unblinding, that our constraint on $S_8$ is consistent with the Fourier space cosmic shear and the 3$\times$2pt analyses on the same HSC dataset. We carefully study the potential systematics from astrophysical and systematic model uncertainties in our fiducial analysis using synthetic data, and report no biases (including projection bias in the posterior space) greater than $0.5σ$ in the estimation of $S_8$. Our analysis hints that the mean redshifts of the two highest tomographic bins are higher than initially estimated. In addition, a number of consistency tests are conducted to assess the robustness of our analysis. Comparing our result with Planck-2018 cosmic microwave background observations, we find a ~$2σ$ tension for the $Λ$CDM model.

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Weak Lensing Tomographic Redshift Distribution Inference for the Hyper Suprime-Cam Subaru Strategic Program three-year shape catalogue

We present posterior sample redshift distributions for the Hyper Suprime-Cam Subaru Strategic Program Weak Lensing three-year (HSC Y3) analysis. Using the galaxies' photometry and spatial cross-correlations, we conduct a combined Bayesian Hierarchical Inference of the sample redshift distributions. The spatial cross-correlations are derived using a subsample of Luminous Red Galaxies (LRGs) with accurate redshift information available up to a photometric redshift of $z < 1.2$. We derive the photometry-based constraints using a combination of two empirical techniques calibrated on spectroscopic- and multiband photometric data that covers a spatial subset of the shear catalog. The limited spatial coverage induces a cosmic variance error budget that we include in the inference. Our cross-correlation analysis models the photometric redshift error of the LRGs to correct for systematic biases and statistical uncertainties. We demonstrate consistency between the sample redshift distributions derived using the spatial cross-correlations, the photometry, and the posterior of the combined analysis. Based on this assessment, we recommend conservative priors for sample redshift distributions of tomographic bins used in the three-year cosmological Weak Lensing analyses.

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Hyper Suprime-Cam Year 3 Results: Measurements of Clustering of SDSS-BOSS Galaxies, Galaxy-Galaxy Lensing and Cosmic Shear

We use the Sloan Digital Sky Survey (SDSS) BOSS galaxies and their overlap with approximately 416 sq. degree of deep $grizy$-band imaging from the Subaru Hyper Suprime-Cam Survey (HSC). We measure three two-point correlations that form the basis of the cosmological inference presented in our companion papers, Miyatake et al. and Sugiyama et al. We use three approximately volume limited subsamples of spectroscopic galaxies by their $i$-band magnitude from the SDSS-BOSS: LOWZ (0.1<z<0.35), CMASS1 (0.43<z<0.55) and CMASS2 (0.55<z<0.7), respectively. We present high signal-to-noise ratio measurements of the projected correlation functions of these galaxies, which is expected to be proportional to the matter correlation function times the bias of galaxies on large scales. In order to break the degeneracy between the amplitude of the matter correlation and the bias of these galaxies, we use the distortions of the shapes of galaxies in HSC due to weak gravitational lensing, to measure the galaxy-galaxy lensing signal, which probes the galaxy-matter cross-correlation of the SDSS-BOSS galaxies. We also measure the cosmic shear correlation functions from HSC galaxies which is related to the projected matter correlation function. We demonstrate the robustness of our measurements with a variety of systematic tests. Our use of a single sample of HSC source galaxies is crucial to calibrate any residual systematic biases in the inferred redshifts of our galaxies. We also describe the construction of a suite of mocks: i) spectroscopic galaxy catalogs which obey the clustering and abundance of each of the three SDSS-BOSS subsamples, and ii) galaxy shape catalogs which obey the footprint of the HSC survey and have been appropriately sheared by the large-scale structure expected in a $Λ$-CDM model. We use these mock catalogs to compute the covariance of each of our observables.

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A General Framework for Removing Point Spread Function Additive Systematics in Cosmological Weak Lensing Analysis

Cosmological weak lensing measurements rely on a precise measurement of the shear two-point correlation function (2PCF) along with a deep understanding of systematics that affect it. In this work, we demonstrate a general framework for detecting and modeling the impact of PSF systematics on the cosmic shear 2PCF, and mitigating its impact on cosmological analysis. Our framework can describe leakage and modeling error from all spin-2 quantities contributed by the PSF second and higher moments, rather than just the second moments, using the cross-correlations between galaxy shapes and PSF moments. We interpret null tests using the HSC Year 3 (Y3) catalogs with this formalism, and find that leakage from the spin-2 combination of PSF fourth moments is the leading contributor to additive shear systematics, with total contamination that is an order of magnitude higher than that contributed by PSF second moments alone. We conducted a mock cosmic shear analysis for HSC Y3, and find that, if uncorrected, PSF systematics can bias the cosmological parameters $Ω_m$ and $S_8$ by $\sim$0.3$σ$. The traditional second moment-based model can only correct for a 0.1$σ$ bias, leaving the contamination largely uncorrected. We conclude it is necessary to model both PSF second and fourth moment contamination for HSC Y3 cosmic shear analysis. We also reanalyze the HSC Y1 cosmic shear analysis with our updated systematics model, and identify a 0.07$σ$ bias on $Ω_m$ when using the more restricted second moment model from the original analysis. We demonstrate how to self-consistently use the method in both real space and Fourier space, assess shear systematics in tomographic bins, and test for PSF model overfitting.

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Optical Cluster Cosmology with SDSS redMaPPer clusters and HSC-Y3 lensing measurements

We present cosmology results obtained from a blind joint analysis of the abundance, projected clustering, and weak lensing of galaxy clusters measured from the Sloan Digital Sky Survey (SDSS) redMaPPer cluster catalog and the Hyper-Suprime Cam (HSC) Year3 shape catalog. We present a full-forward model for the cluster observables, which includes empirical modeling for the anisotropic boosts on the lensing and clustering signals of optical clusters. We validate our analysis via mock cluster catalogs which include observational systematics, such as the projection effect and the effect of baryonic feedback, and find that our analysis can robustly constrain cosmological parameters in an unbiased manner without any informative priors on our model parameters. The joint analysis of our observables in the context of the flat $Λ$CDM model results in cosmological constraints for $S_8\equiv σ_8 \sqrt{Ω_{\rm m} / 0.3}=0.816^{+0.041}_{-0.039}$. Our result is consistent with the $S_8$ inference from other cosmic microwave background- and large scale structure-based cosmology analyses, including the result from the \emph{Planck} 2018 primary CMB analysis.

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Photometric Redshift Uncertainties in Weak Gravitational Lensing Shear Analysis: Models and Marginalization

Recovering credible cosmological parameter constraints in a weak lensing shear analysis requires an accurate model that can be used to marginalize over nuisance parameters describing potential sources of systematic uncertainty, such as the uncertainties on the sample redshift distribution $n(z)$. Due to the challenge of running Markov Chain Monte-Carlo (MCMC) in the high dimensional parameter spaces in which the $n(z)$ uncertainties may be parameterized, it is common practice to simplify the $n(z)$ parameterization or combine MCMC chains that each have a fixed $n(z)$ resampled from the $n(z)$ uncertainties. In this work, we propose a statistically-principled Bayesian resampling approach for marginalizing over the $n(z)$ uncertainty using multiple MCMC chains. We self-consistently compare the new method to existing ones from the literature in the context of a forecasted cosmic shear analysis for the HSC three-year shape catalog, and find that these methods recover similar cosmological parameter constraints, implying that using the most computationally efficient of the approaches is appropriate. However, we find that for datasets with the constraining power of the full HSC survey dataset (and, by implication, those upcoming surveys with even tighter constraints), the choice of method for marginalizing over $n(z)$ uncertainty among the several methods from the literature may significantly impact the statistical uncertainties on cosmological parameters, and a careful model selection is needed to ensure credible parameter intervals.

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Hyper Suprime-Cam Year 3 Results: Cosmology from Galaxy Clustering and Weak Lensing with HSC and SDSS using the Emulator Based Halo Model

We present cosmology results from a blinded joint analysis of cosmic shear, $ξ_{\pm}(\vartheta)$, galaxy-galaxy weak lensing, $Δ\!Σ(R)$, and projected galaxy clustering, $w_{\rm p}(R)$, measured from the Hyper Suprime-Cam three-year (HSC-Y3) shape catalog and the Sloan Digital Sky Survey (SDSS) DR11 spectroscopic galaxy catalog - a 3$\times$2pt cosmology analysis. We define luminosity-cut samples of SDSS galaxies to serve as the tracers of $w_{\rm p}$ and as the lens samples for $Δ\!Σ$ in three spectroscopic redshift bins spanning the range $0.15<z<0.7$. For the $ξ_{\pm}$ and $Δ\!Σ$ measurements, we use a single source sample over 416 deg$^2$, selected from HSC-Y3 based on having photometric redshifts (photo-$z$) greater than 0.75. For cosmological parameter inference, we use Dark Emulator combined with a halo occupation distribution prescription to model $w_{\rm p}$ and $Δ\!Σ$ down to quasi-nonlinear scales. In our baseline analysis we employ an uninformative flat prior of the residual photo-$z$ error to model a residual bias in the mean redshift of HSC source galaxies. We obtain a robust constraint on the cosmological parameters for the flat $Λ$CDM model: $S_8=σ_8(Ω_{\rm m}/0.3)^{0.5}=0.763^{+0.040}_{-0.036}$ (68% C.I.), or the best-constrained parameter given by $S'_8=σ_8(Ω_{\rm m}/0.3)^{0.22}=0.721\pm 0.028$, determined with about 4% fractional precision. Our HSC-Y3 data exhibits about 2.5$σ$ tension with the Planck inferred $S_8$ value for the $Λ$CDM model, and hints at a non-zero residual photo-$z$ bias implying that the true mean redshift of the HSC galaxies at $z\gtrsim 0.75$ is higher than that implied by the original photo-$z$ estimates.

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Hyper Suprime-Cam Year 3 Results: Cosmology from Cosmic Shear Power Spectra

We measure weak lensing cosmic shear power spectra from the three-year galaxy shear catalog of the Hyper Suprime-Cam (HSC) Subaru Strategic Program imaging survey. The shear catalog covers $416 \ \mathrm{deg}^2$ of the northern sky, with a mean $i$-band seeing of 0.59 arcsec and an effective galaxy number density of 15 $\mathrm{arcmin}^{-2}$ within our adopted redshift range. With an $i$-band magnitude limit of 24.5 mag, and four tomographic redshift bins spanning $0.3 \leq z_{\mathrm{ph}} \leq 1.5$ based on photometric redshifts, we obtain a high-significance measurement of the cosmic shear power spectra, with a signal-to-noise ratio of approximately 26.4 in the multipole range $300<\ell<1800$. The accuracy of our power spectrum measurement is tested against realistic mock shear catalogs, and we use these catalogs to get a reliable measurement of the covariance of the power spectrum measurements. We use a robust blinding procedure to avoid confirmation bias, and model various uncertainties and sources of bias in our analysis, including point spread function systematics, redshift distribution uncertainties, the intrinsic alignment of galaxies and the modeling of the matter power spectrum. For a flat $Λ$CDM model, we find $S_8 \equiv σ_8 (Ω_m/0.3)^{0.5} =0.776^{+0.032}_{-0.033}$, which is in excellent agreement with the constraints from the other HSC Year 3 cosmology analyses, as well as those from a number of other cosmic shear experiments. This result implies a $\sim$$2σ$-level tension with the Planck 2018 cosmology. We study the effect that various systematic errors and modeling choices could have on this value, and find that they can shift the best-fit value of $S_8$ by no more than $\sim$$0.5σ$, indicating that our result is robust to such systematics.

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Analytical Weak-lensing Shear Responses of Galaxy Properties and Galaxy Detection

Shear estimation bias from galaxy detection and blending identification is now recognized as an issue for ongoing and future weak lensing surveys. Currently, the empirical approach to correcting for this bias involves numerically shearing every observed galaxy and rerunning the detection and selection process. In this work, we provide an analytical correction for this bias that is accurate to subpercent level and far simpler to use. With the interpretation that smoothed image pixel values and galaxy properties are projections of the image signal onto a set of basis functions, we analytically derive the linear shear responses of both the pixel values and the galaxy properties (i.e., magnitude, size and shape) using the shear responses of the basis functions. With these derived shear responses, we correct for biases from shear-dependent galaxy detection and galaxy sample selection. With the analytical covariance matrix of measurement errors caused by image noise on pixel values and galaxy properties, we correct for the noise biases in galaxy shape measurement and the detection/selection process to the second-order in noise. The code used for this paper can carry out the detection, selection, and shear measurement for ~1000 galaxies per CPU second. The algorithm is tested with realistic image simulations, and we find, after the analytical correction (without relying on external image calibration) for the detection/selection bias of about $-4\%$, the multiplicative shear bias is $-0.12 \pm 0.10\%$ for isolated galaxies; and $-0.3 \pm 0.1\%$ for blended galaxies with Hyper Suprime-Cam observational condition.

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Cosmological constraints from HSC survey first-year data using deep learning

We present cosmological constraints from the Subaru Hyper Suprime-Cam (HSC) first-year weak lensing shear catalogue using convolutional neural networks (CNNs) and conventional summary statistics. We crop 19 $3\times3\,\mathrm{{deg}^2}$ sub-fields from the first-year area, divide the galaxies with redshift $0.3\le z\le1.5$ into four equally-spaced redshift bins, and perform tomographic analyses. We develop a pipeline to generate simulated convergence maps from cosmological $N$-body simulations, where we account for effects such as intrinsic alignments (IAs), baryons, photometric redshift errors, and point spread function errors, to match characteristics of the real catalogue. We train CNNs that can predict the underlying parameters from the simulated maps, and we use them to construct likelihood functions for Bayesian analyses. In the $Λ$ cold dark matter model with two free cosmological parameters $Ω_\mathrm{m}$ and $σ_8$, we find $Ω_\mathrm{m}=0.278_{-0.035}^{+0.037}$, $S_8\equiv(Ω_\mathrm{m}/0.3)^{0.5}σ_8=0.793_{-0.018}^{+0.017}$, and the IA amplitude $A_\mathrm{IA}=0.20_{-0.58}^{+0.55}$. In a model with four additional free baryonic parameters, we find $Ω_\mathrm{m}=0.268_{-0.036}^{+0.040}$, $S_8=0.819_{-0.024}^{+0.034}$, and $A_\mathrm{IA}=-0.16_{-0.58}^{+0.59}$, with the baryonic parameters not being well-constrained. We also find that statistical uncertainties of the parameters by the CNNs are smaller than those from the power spectrum (5--24 percent smaller for $S_8$ and a factor of 2.5--3.0 smaller for $Ω_\mathrm{m}$), showing the effectiveness of CNNs for uncovering additional cosmological information from the HSC data. With baryons, the $S_8$ discrepancy between HSC first-year data and Planck 2018 is reduced from $\sim2.2\,σ$ to $0.3\text{--}0.5\,σ$.

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

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 deg$^2$ of the northern sky, split into six fields. The mean $i$-band seeing is 0.59 arcsec. 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 a level: $|δm|<9\times 10^{-3}$. The bias residual $δm$ shows no dependence on redshift in the range $0 1$ degree scales and will require mitigation during the inference of cosmological parameters using cosmic shear measurements.

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Three-Dimensional Reconstruction of Weak Lensing Mass Maps with a Sparsity Prior. I. Cluster Detection

We propose a novel method to reconstruct high-resolution three-dimensional mass maps using data from photometric weak-lensing surveys. We apply an adaptive LASSO algorithm to perform a sparsity-based reconstruction on the assumption that the underlying cosmic density field is represented by a sum of Navarro-Frenk-White halos. We generate realistic mock galaxy shape catalogues by considering the shear distortions from isolated halos for the configurations matched to Subaru Hyper Suprime-Cam Survey with its photometric redshift estimates. We show that the adaptive method significantly reduces line-of-sight smearing that is caused by the correlation between the lensing kernels at different redshifts. Lensing clusters with lower mass limits of $10^{14.0} h^{-1}M_{\odot}$, $10^{14.7} h^{-1}M_{\odot}$, $10^{15.0} h^{-1}M_{\odot}$ can be detected with 1.5-$σ$ confidence at the low ($z<0.3$), median ($0.3\leq z< 0.6$) and high ($0.6\leq z< 0.85$) redshifts, respectively, with an average false detection rate of 0.022 deg$^{-2}$. The estimated redshifts of the detected clusters are systematically lower than the true values by $Δz \sim 0.03$ for halos at $z\leq 0.4$, but the relative redshift bias is below $0.5\%$ for clusters at $0.4<z\leq 0.85$. The standard deviation of the redshift estimation is $0.092$. Our method enables direct three-dimensional cluster detection with accurate redshift estimates.

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Weak gravitational lensing shear measurement with FPFS: analytical mitigation of noise bias and selection bias

Dedicated 'Stage IV' observatories will soon observe the entire extragalactic sky, to measure the 'cosmic shear' distortion of galaxy shapes by weak gravitational lensing. To measure the apparent shapes of those galaxies, we present an improved version of the Fourier Power Function Shapelets (FPFS) shear measurement method. This now includes analytic corrections for sources of bias that plague all shape measurement algorithms: including noise bias (due to noise in nonlinear combinations of observable quantities) and selection bias (due to sheared galaxies being more or less likely to be detected). Crucially, these analytic solutions do not rely on calibration from external image simulations. For isolated galaxies, the small residual $\sim$$10^{-3}$ multiplicative bias and $\lesssim$$10^{-4}$ additive bias now meet science requirements for Stage IV experiments. FPFS also works accurately for faint galaxies and robustly against stellar contamination. Future work will focus on deblending overlapping galaxies. The code used for this paper can process $>$$1000$ galaxy images per CPU second and is available from https://github.com/mr-superonion/FPFS.

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Cosmological inference from the emulator based halo model II: Joint analysis of galaxy-galaxy weak lensing and galaxy clustering from HSC-Y1 and SDSS

We present high-fidelity cosmology results from a blinded joint analysis of galaxy-galaxy weak lensing ($Δ\!Σ$) and projected galaxy clustering ($w_{\rm p}$) measured from the Hyper Suprime-Cam Year-1 (HSC-Y1) data and spectroscopic Sloan Digital Sky Survey (SDSS) galaxy catalogs in the redshift range $0.15<z<0.7$. We define luminosity-limited samples of SDSS galaxies to serve as the tracers of $w_{\rm p}$ in three spectroscopic redshift bins, and as the lens samples for $Δ\!Σ$. For the $Δ\!Σ$ measurements, we select a single sample of 4 million source galaxies over 140 deg$^2$ from HSC-Y1 with photometric redshifts (photo-$z$) greater than 0.75, enabling a better handle of photo-$z$ errors by comparing the $Δ\!Σ$ amplitudes for the three lens redshift bins. For cosmological parameter inference, we use an input galaxy-halo connection model built on the {\tt Dark Emulator} package with a halo occupation distribution that includes nuisance parameters to marginalize over modeling uncertainties. We model the $Δ\!Σ$ and $w_{\rm p}$ measurements on scales from $R\simeq 3$ and $2\,h^{-1}{\rm Mpc}$, respectively, up to $30\,h^{-1}{\rm Mpc}$ assuming a flat $Λ$CDM cosmology. With various tests using mock catalogs described in Miyatake et al. (2021), we show that any bias in the clustering amplitude $S_8\equiv σ_8(Ω_{\rm m}/0.3)^{0.5}$ due to uncertainties in the galaxy-halo connection is less than $\sim50$\% of the statistical uncertainty of $S_8$, {\it unless} the assembly bias effect is unexpectedly large. Our best-fit models have $S_8=0.795^{+0.049}_{-0.042}$ (mode and 68\% credible interval) for the flat $Λ$CDM model; we find tighter constraints on the quantity $S_8(α=0.17)\equivσ_8(Ω_{\rm m}/0.3)^{0.17} =0.745^{+0.039}_{-0.031}$. (abriged)

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HSC Year 1 cosmology results with the minimal bias method: HSC$\times$BOSS galaxy-galaxy weak lensing and BOSS galaxy clustering

We present cosmological parameter constraints from a blinded joint analysis of galaxy-galaxy weak lensing, $Δ\!Σ(R)$, and projected correlation function, $w_\mathrm{p}(R)$, measured from the first-year HSC (HSC-Y1) data and SDSS spectroscopic galaxies over $0.15 0.75$ for the $Δ\!Σ$ measurements, selected based on their photometric redshifts. For theoretical template, we use the "minimal bias" model for the cosmological clustering observables for the flat $Λ$CDM cosmological model. We compare the model predictions with the measurements in each redshift bin on large scales, $R>12$ and $8~h^{-1}\mathrm{Mpc}$ for $Δ\!Σ(R)$ and $w_\mathrm{p}(R)$, respectively, where the perturbation theory-inspired model is valid. When we employ weak priors on cosmological parameters, without CMB information, we find $S_8=0.936^{+0.092}_{-0.086}$, $σ_8=0.85^{+0.16}_{-0.11}$, and $Ω_\mathrm{m}=0.283^{+0.12}_{-0.035}$ for the flat $Λ$CDM model. Although the central value of $S_8$ appears to be larger than those inferred from other cosmological experiments, we find that the difference is consistent with expected differences due to sample variance, and our results are consistent with the other results to within the statistical uncertainties. (abriged)

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The eROSITA Final Equatorial-Depth Survey (eFEDS): X-ray Observable-to-Mass-and-Redshift Relations of Galaxy Clusters and Groups with Weak-Lensing Mass Calibration from the Hyper Suprime-Cam Subaru Strategic Program Survey

We present the first weak-lensing mass calibration and X-ray scaling relations of galaxy clusters and groups selected in the $eROSITA$ Final Equatorial Depth Survey (eFEDS) observed by Spectrum Roentgen Gamma/$eROSITA$ over a contiguous footprint with an area of $\approx140$ deg$^2$, using the three-year (S19A) weak-lensing data from the Hyper Suprime-Cam (HSC) Subaru Strategic Program survey. In this work, a sample of $434$ optically confirmed galaxy clusters (and groups) at redshift $0.01\lesssim z \lesssim1.3$ with a median of $0.35$ is studied, of which $313$ systems are uniformly covered by the HSC survey to enable the extraction of the weak-lensing shear observable. In a Bayesian population modelling, we perform a blind analysis for the weak-lensing mass calibration by simultaneously modelling the observed count rate $η$ and the shear profile $g$ of individual clusters through the count rate-to-mass-and-redshift ($η$--$M_{500}$--$z$) and weak-lensing mass-to-mass-and-redshift ($M_{\mathrm{WL}}$--$M_{500}$--$z$) relations, respectively, while accounting for the bias in these observables using simulation-based calibrations. As a result, the count rate-inferred and lensing-calibrated cluster mass is obtained from the joint modelling of the scaling relations, as the ensemble mass spanning a range of $10^{13}h^{-1}M_{\odot}\lesssim M_{500}\lesssim10^{15} h^{-1}M_{\odot}$ with a median of $\approx10^{14} h^{-1}M_{\odot}$ for the eFEDS sample. With the mass calibration, we further model the X-ray observable-to-mass-and-redshift relations, including the rest-frame soft-band and bolometric luminosity ($L_{\mathrm{X}}$ and $L_{\mathrm{b}}$), the emission-weighted temperature $T_{\mathrm{X}}$, the mass of intra-cluster medium $M_{\mathrm{g}}$, and the mass proxy $Y_{\mathrm{X}}$, which is the product of $T_{\mathrm{X}}$ and $M_{\mathrm{g}}$. (abridged)

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