arXiv subjects

Ken Osato

Publications and source records attributed to Ken Osato.

At least 19 recordsLinked to original sources

arXiv2026

Weak-lensing Shear-Selected Galaxy Clusters from the Hyper Suprime-Cam Subaru Strategic Program: III. A precision cosmological sample enabled by optical confirmation

We develop fCAMIRA (forced-mode CAMIRA), a tool for optical cluster confirmation, and apply it to a sample of 129 weak-lensing (WL) shear-selected galaxy clusters identified in aperture-mass maps obtained from the Hyper Suprime-Cam Subaru Strategic Program Three-Year (HSC-SSP Y3) weak-lensing data. fCAMIRA is built upon the CAMIRA cluster-finding algorithm and relies on a red-sequence (RS) galaxy model that is calibrated in a data-driven way. The RS model adopts the metallicity-luminosity relation measured in this work using X-ray-selected clusters up to redshift $z\approx1.3$, followed by the calibration of color offsets using large spectroscopic samples. With the RS model, we build two types of galaxy richness maps, one obtained with a spatial filter matched to a typical cluster size of $R=0.8\,h^{-1}\,\mathrm{Mpc}$ and the other obtained with a fixed angular-size filter identical to that used in constructing the WL aperture-mass maps. The fCAMIRA algorithm utilizes these two richness maps, identifies all optical counterpart candidates along the line of sight of each shear-selected cluster, and measures the cluster photometric redshift from the highest-ranked counterpart. The ranking is determined by the fractional lensing contribution $f_{\mathrm{lens}}$ of each candidate. Using available spectroscopic cluster redshifts, we quantify the mean bias and scatter in the cluster photometric redshifts at levels of approximately 0.005 and 0.008, respectively, demonstrating excellent photometric-redshift performance. We compare the fCAMIRA photometric redshifts with estimates from direct positional cross-matching and find that approximately 8% of the total sample exhibits redshift discrepancies greater than 0.15. This outlier fraction is primarily attributed to projection effects, leading to the misidentification of the optical counterparts. (abridged)

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arXiv2026

From Dark Matter to Galaxies: Halo-Free Mock Generation via Conditional Point-Cloud Diffusion

We present a diffusion-based generative model for constructing realistic galaxy catalogues from dark matter density fields. The model takes a three-dimensional dark matter density field as input and generates galaxies directly as a point cloud with positions and physical properties, including star formation rate (SFR), without identifying dark matter haloes or subhaloes. We train the model on galaxy catalogues from the IllustrisTNG hydrodynamical simulation. The generated catalogues reproduce the spatial correspondence between galaxies and the underlying dark matter field, preferentially populating dense regions and filamentary structures. They also accurately reproduce the one- and two-dimensional distributions of SFR and stellar mass, the galaxy auto-power spectrum, and the galaxy--dark matter cross-power spectrum. The model generates galaxies associated with structures below the nominal resolution of the input density field by marginalising over unresolved small-scale structure rather than relying on a resolved halo catalogue. With an optimised diffusion sampling schedule, it generates a catalogue with SFR $> 1 ~\rm M_\odot/yr$ over a $(151.3 ~\rm Mpc)^3$ volume in approximately 10 seconds on a single GPU. Our model therefore provides a practical engine for producing large mock ensembles for upcoming galaxy redshift surveys and line-intensity mapping experiments, and offers a path toward simulation-based inference that bypasses halo finding and directly connects field-level dark matter statistics to observable galaxy populations.

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arXiv2026

Clustering of emission line galaxies with IllustrisTNG -- II. cosmology challenge with anisotropic correlation functions and ELG-halo connections

Emission line galaxies (ELGs) are the primary tracers of the large-scale structures of the Universe in ongoing Stage-IV cosmological spectroscopic surveys, which aim to measure the clustering statistics at higher redshifts $z \simeq 1.5 \text{--} 2$ with unprecedented precision. In this study, we construct realistic mock ELG samples with IllustrisTNG hydrodynamical simulations and stellar population synthesis framework. In order to validate the modelling of clustering, we measure the anisotropic correlation functions of mock ELGs and infer the linear growth rate, which is one of key cosmological parameters in galaxy clustering. As a control sample, we construct the mass-limited subhalo samples with the same number density as ELGs. The isotropic correlation functions in real space for both samples do not differ significantly. However, the quadrupole moment of the anisotropic correlation function, which is sensitive to the velocity of galaxies, is suppressed for ELGs, potentially due to the infalling motion of ELGs towards the centre of the hosting halos. The smaller amplitude leads to the underestimation of the linear growth rate and implies the velocity bias between ELGs and dark matter. When the analysis is limited to large scales $(\gtrsim 15 \, h^{-1} \, \mathrm{Mpc})$, the parameter bias vanishes. Next, we investigate the ELG-halo connection through the phase-space distribution of satellite ELGs within hosting halos and galactic conformity of star formation activity. The infalling motion is further confirmed by the phase-space distribution relative to the host halo, and this dynamics of ELGs challenges the assumption that the radial distribution of satellites follows that of dark matter.

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arXiv2026

Cross-correlating galaxies and cosmic dispersion measures: Constraints on the gas-to-halo mass relation from 2MASS galaxies and 133 localized fast radio bursts

We conduct a cross-correlation analysis between large-scale structures traced by the Two Micron All Sky Survey (2MASS) galaxy catalog and the cosmic dispersion measures of 133 localized fast radio bursts (FRBs). The cross-correlation signal is measured as a function of the comoving separation $R$ between 2MASS galaxies and background FRB sightlines, making full use of the available redshift information for both datasets. Our measurements are consistent with a null detection over the range $0.01 < R\, [h^{-1}\mathrm{Mpc}] < 1$. Using a halo-based model in which free-electron density profiles are drawn from the hydrodynamical simulation IllustrisTNG-300 (TNG300), we show that the null signal at $R \sim 0.01\, h^{-1}\mathrm{Mpc}$ is inconsistent with the TNG300 prediction. This discrepancy indicates that the hot-gas mass fraction in halos with masses of $10^{12-13}\, M_\odot$ hosting 2MASS galaxies must be lower than that predicted by TNG300. A simple phenomenological modification of the TNG300 model suggests that the hot-gas mass fraction in halos of $10^{12-13}\, M_\odot$ should be below $\sim 10\%$ of the global baryon fraction in the nearby universe, implying the need for stronger feedback in this mass range. Our constraints are consistent with those inferred from X-ray emission and Sunyaev-Zel'dovich measurements in galaxies, while providing a direct estimate of the hot-gas mass fraction that does not rely on electron-temperature measurements. These results demonstrate that galaxy-FRB cross correlations offer a powerful probe of feedback processes in galaxy formation.

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arXiv2026

Illuminating the Physics of Cosmic Origin and Evolution: A UK Space Frontiers 2035 White Paper

Understanding the Universe's origins and evolution remains one of the most fundamental challenges in modern cosmology. This white paper explores three key science priorities in this field: unravelling the physics of cosmic inflation, investigating the accelerating expansion of the Universe, and precisely measuring the sum of the neutrino masses. Achieving these goals requires a dedicated survey to map the large-scale structure at high redshift in unprecedented detail. We describe how this can be achieved through a mission concept called SIRMOS, providing a high-throughput, highly multiplexed spectroscopic capability to obtain accurate redshifts for over 100 million galaxies over a wide sky area. Such a survey would leverage the deepest existing wide-area photometric catalogues for targeting, with spectra offering continuous 1.25-2.5~$\mu$m wavelength coverage at moderate resolution, allowing precise redshift measurements in the $1<z<4$ range with minimal bias. We outline the scientific opportunities this presents. Recent years have seen significant advances in instrumentation, including digital micromirror devices, complex telescope mirrors, large detector arrays, and data processing pipelines. While these technologies have been demonstrated in terrestrial applications, such a survey is a unique opportunity to apply these proven capabilities in space to address fundamental questions in cosmology. Participation in such a mission will simultaneously deliver a compelling science case, help align UK Space Agency and STFC strategies, demonstrate the UK's growing capability in end-to-end space missions, and strengthen the national space economy through high-value industrial participation.

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arXiv2025

Denoising weak lensing mass maps with diffusion model and generative adversarial network

The matter distribution of the Universe can be mapped through the weak gravitational lensing (WL) effect: small distortions of the shapes of distant galaxies, which reflects the inhomogeneity of the cosmic density field. The most dominant contaminant in the WL effect is the shape noise; the signal is diluted due to the finite number of source galaxies. In order to explore the full potential of WL measurements, sharpening the signal by removing the shape noise from the observational data, i.e., WL denoising, is a pressing issue. Machine learning approaches, in particular, deep generative models, have proven effective at the WL denoising task. We implement a denoising model based on the diffusion model (DM) and conduct systematic in-depth comparisons with generative adversarial networks (GANs), which have been applied in previous works for WL denoising. Utilizing the large suite of mock simulations of WL observations, we demonstrate that DM surpasses GAN in the WL denosing task in multiple aspects: (1) the training process is more stable, (2) taking the average of multiple samples from DM can robustly reproduce the true signal, and (3) DM can recover various statistics with higher accuracy.

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arXiv2025

Measurement of angular cross-correlation between the cosmological dispersion measure and the thermal Sunyaev--Zeldovich effect

The dispersion measures (${\rm DMs}$) from fast radio bursts (FRBs) and the thermal Sunyaev--Zeldovich (tSZ) effect probe the free-electron density and thermal pressure, respectively, in the intergalactic medium (IGM) and the intervening galaxies and clusters. Their combination enables disentangling the gas density and temperature. In this work, we present the first detection of an angular cross-correlation between the ${\rm DMs}$ and the Compton $y$ parameter of the tSZ effect. The theoretical expectation is calculated using the halo model $\texttt{HMx}$, calibrated with hydrodynamic simulations. The observational cross-correlation is measured over angular separations of $1^\prime$--$1000^\prime$ using the ${\rm DMs}$ from $133$ localized FRBs and the $y$-maps from the Planck satellite and the Atacama Cosmology Telescope (ACT). We detect a positive correlation with amplitudes of $\mathcal{A}=2.01 \pm 0.50$ ($4.0 \sigma$) for Planck and $\mathcal{A}=1.23 \pm 0.82$ ($1.5 \sigma$) for ACT, where $\mathcal{A}=1$ corresponds to the theoretical prediction of the Planck 2018 $\Lambda$CDM cosmology. Assuming an isothermal gas, the measured amplitude implies an average electron temperature of $\approx 2 \times 10^7 \, {\rm K}$. The correlation is highly sensitive to the matter clustering parameter $\sigma_8$ and to baryon feedback, and its dependence on other cosmological and astrophysical parameters -- such as the ionized fraction and the Hubble constant -- differs from that of the ${\rm DM}$ alone. This suggests that future joint analyses of the ${\rm DMs}$ and the tSZ effect could help break degeneracies among these parameters.

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arXiv2025

Modelling Galaxy Clustering and Tomographic Galaxy-Galaxy Lensing with HSC Y3 and SDSS using the Point-Mass Correction Model and Redshift Self-Calibration

The combination of galaxy-galaxy weak lensing and galaxy clustering is a powerful probe of the cosmological model, and exploration of how to best model and extract this information from the signals is essential. We present the measurement of the galaxy-galaxy weak lensing signals using the SDSS DR11 spectroscopic galaxies as lens galaxies, and the HSC Y3 shear catalog as source galaxies, binned into four tomographic bins by their photometric redshift. The SDSS DR11 galaxies, with a redshift range $0.15<z<0.7$, are binned into three redshift bins, each as a probe for measuring the projected correlation function, $w_p(R_p)$. We measure the galaxy-galaxy lensing signal $\Delta \Sigma (R_p)$ in 12 lens-source bin pairs and show that there is no evidence for significant systematic biases in the measurement with null testing. We combine our $w_p(R_p)$ and $\Delta \Sigma (R_p)$ ($2\times2$pt) data vectors and perform likelihood inference with a flat $\Lambda$CDM model. For $\Delta \Sigma (R_p)$, we extend the lower limit of the scale cut compared to previous HSC Y3 analyses to $2 h^{-1}$Mpc by including a point-mass correction term in addition to the minimal bias model. We present various tests to validate our model and provide extended consistency tests. In the $\Lambda$CDM context, our fiducial model yields $S_8 = 0.804^{+0.051}_{-0.051}$. The $2\times2$pt data vector provides redshift parameter constraints for the third and fourth redshift bins $\Delta z_3 = -0.079^{+0.074}_{-0.084}$, and $\Delta z_4 = -0.203^{+0.167}_{-0.206}$, which is consistent with results from the previous tomographic cosmic shear studies, and serves as the foundation for a future $3\times 2$pt analysis.

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arXiv2025

Cosmology and Source Redshift Constraints from Galaxy Clustering and Tomographic Weak Lensing with HSC Y3 and SDSS using the Point-Mass Correction Model

The combination of galaxy clustering and weak lensing is a powerful probe of the cosmology model. We present a joint analysis of galaxy clustering and weak lensing cosmology using SDSS data as the tracer of dark matter (lens sample) and the HSC Y3 dataset as source galaxies. The analysis divides HSC Y3 galaxies into four tomographic bins for both galaxy-galaxy lensing and cosmic shear measurements, and employs a point-mass correction model to utilize galaxy-galaxy lensing signals down to 2$h^{-1}$Mpc, extending up to 70$h^{-1}$Mpc. These strategies enhance the signal-to-noise ratio of the galaxy-galaxy lensing data vector. Using a flat $\Lambda$CDM model, we find $S_8 = 0.780^{+0.029}_{-0.030}$, and using a $w$CDM model, we obtain $S_8 = 0.756^{+0.038}_{-0.036}$ with $w = -1.176^{+0.310}_{-0.346}$. We apply uninformative priors on the redshift mean-shift parameters for the third and fourth tomographic bins. Leveraging the self-calibration power of tomographic weak lensing, we measure $\Delta z_3 = -0.112^{+0.046}_{-0.049}$ and $\Delta z_4 = -0.185^{+0.071}_{-0.081}$, in agreement with previous HSC Y3 results. This demonstrates that weak lensing self-calibration can achieve redshift constraints comparable to other methods such as photometric and clustering redshift calibration.

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arXiv2025

CosmoGLINT: Cosmological Generative Model for Line Intensity Mapping with Transformer

Modelling star-forming galaxies is crucial for upcoming observations of large-scale matter and galaxy distributions with galaxy redshift surveys and line intensity mapping (LIM). We introduce CosmoGLINT (Cosmological Generative model for Line INtensity mapping with Transformer), a Transformer-based generative framework designed to create realistic galaxy populations from dark matter (DM)-only simulations. CosmoGLINT auto-regressively generates sequences of galaxy properties -- including star formation rate (SFR), distance to the halo centre, and radial and tangential velocities relative to the halo -- conditioned on halo mass. Trained on the IllustrisTNG hydrodynamic simulation, the model reproduces key statistical properties of the original data, including the voxel intensity distribution and the power spectrum both in real and redshift space. It can efficiently generate a number of different realisations of the designated galaxy populations, enabling the creation of mock LIM/redshift survey catalogues from large halo catalogues produced by fast DM-only simulations. We show that our model trained at multiple redshifts can be applied to DM halo lightcone data to generate a realistic mock galaxy lightcone with incorporating the redshift evolution of the galaxy population. The mock catalogues can be readily used to derive statistical quantities and to develop data analysis pipelines for ongoing and future wide-field surveys.

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arXiv2025

Denoising weak lensing mass maps with diffusion model: systematic comparison with generative adversarial network

Removing the shape noise from the observed weak lensing field, i.e., denoising, enhances the potential of WL by accessing information at small scales where the shape noise dominates without denoising. We utilise two machine learning (ML) models for denosing: generative adversarial network (GAN) and diffusion model (DM). We evaluate the performance of denosing with GAN and DM utilising the large suite of mock WL observations, which serve as the training and test data sets. We apply denoising to 1,000 noisy mass maps with GAN and DM models trained with 39,000 mock observations. Both models can fairly well reproduce the true convergence map on large scales. Then, we measure cosmological statistics: power spectrum, bispectrum, one-point probability distribution function, peak and minima counts, and scattering transform coefficients. We find that DM outperforms GAN in almost all considered statistics and recovers the correct statistics down to small scales. For example, the angular power spectrum can be recovered with DM up to multipoles $\ell \lesssim 6000$ while the noise power spectrum dominates from $\ell \simeq 2000$. We also conduct stress tests on the trained model; denoising the maps with different characteristics, e.g., different source redshifts, from the training data. The performance degrades at small scales, but the statistics can still be recovered at large scales. Though the training of DM is more computationally demanding compared with GAN, there are several advantages: numerically stable training, higher performance in the reconstruction of cosmological statistics, and sampling multiple realisations once the model is trained. It has been known that DM can generate higher-quality images in real-world problems than GAN, the superiority has been confirmed as well in the WL denoising problem.

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arXiv2025

Dust-obscured Galaxies with Broken Power-law Spectral Energy Distributions Discovered by UNIONS

We report on the spectral energy distributions (SEDs) of infrared-bright dust-obscured galaxies (DOGs) with $(i - [22])_{\rm AB} \geq 7.0$. Using photometry from the deep and wide Ultraviolet Near-Infrared Optical Northern Survey, combined with near-IR and mid-IR data from the UKIRT Infrared Deep Sky Survey and the Wide-field Infrared Survey Explorer, we successfully identified 382 DOGs in $\sim$ 170 deg$^2$. Among them, the vast majority (376 DOGs) were classified into two subclasses: bump DOGs (132/376) and power-law (PL) DOGs (244/376), which are dominated by star formation and active galactic nucleus (AGN), respectively. Through the SED analysis, we found that roughly half (120/244) of the PL DOGs show ``broken'' power-law SEDs. The significant red slope from optical to near-IR in the SEDs of these ``broken power-law DOGs'' (BPL DOGs) probably reflects their large amount of dust extinction. In other words, BPL DOGs are more heavily obscured AGNs, compared to PL DOGs with non-broken power-law SEDs.

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arXiv2025

UNIONS: The Ultraviolet Near-Infrared Optical Northern Survey

The Ultraviolet Near-Infrared Optical Northern Survey (UNIONS) is a "collaboration of collaborations" that is using the Canada-France-Hawai'i Telescope, the Pan-STARRS telescopes, and the Subaru Observatory to obtain $ugriz$ images of a core survey region of 6250 deg$^2$ of the northern sky. The $10\sigma$ point source depth of the data, as measured within a 2-arcsecond diameter aperture, are $[u,g,r,i,z] = [23.7, 24.5, 24.2, 23.8, 23.3]$\ in AB magnitudes. UNIONS is addressing some of the most fundamental questions in astronomy, including the properties of dark matter, the growth of structure in the Universe from the very smallest galaxies to large-scale structure, and the assembly of the Milky Way. It is set to become the major ground-based legacy survey for the northern hemisphere for the next decade and provides an essential northern complement to the static-sky science of the Vera C. Rubin Observatory's Legacy Survey of Space and Time. UNIONS supports the core science mission of the {\it Euclid} space mission by providing the data necessary in the northern hemisphere for the calibration of the wavelength dependence of the {\it Euclid} point-spread function and derivation of photometric redshifts in the North Galactic Cap. This region contains the highest quality sky for {\it Euclid}, with low backgrounds from the zodiacal light, stellar density, extinction, and emission from Galactic cirrus. Here, we describe the UNIONS survey components, science goals, data products, and the current status of the overall program.

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arXiv2024

MPI-Rockstar: a Hybrid MPI and OpenMP Parallel Implementation of the Rockstar Halo finder

MPI-Rockstar is a massively parallel halo finder based on the Rockstar phase-space temporal halo finder code, which is one of the most extensively used halo finding codes. Compared to the original code, parallelized by a primitive socket communication library, we parallelized it in a hybrid way using MPI and OpenMP, which is suitable for analysis on the hybrid shared and distributed memory environments of modern supercomputers. This implementation can easily handle the analysis of more than a trillion particles on more than 100,000 parallel processes, enabling the production of a huge dataset for the next generation of cosmological surveys. As new functions to the original Rockstar code, MPI-Rockstar supports HDF5 as an output format and can output additional halo properties such as the inertia tensor.

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arXiv2024

Baryon Pasting the Uchuu Lightcone Simulation

We present the Baryon Pasted (BP) X-ray and thermal Sunyaev-Zel'dovich (tSZ) maps derived from the half-sky Uchuu Lightcone simulation. These BP-Uchuu maps are constructed using more than $75$ million dark matter halos with masses $M_{500c} \geq 10^{13} M_\odot$ within the redshift range $0 \leq z \leq 2$. A distinctive feature of our BP-Uchuu Lightcone maps is their capability to assess the influence of both extrinsic and intrinsic scatter caused by triaxial gaseous halos and internal gas characteristics, respectively, at the map level. We show that triaxial gas drives substantial scatter in X-ray luminosities of clusters and groups, accounting for nearly half of the total scatter in core-excised measurements. Additionally, scatter in the thermal pressure and gas density profiles of halos enhances the X-ray and SZ power spectra, leading to biases in cosmological parameter estimates. These findings are statistically robust due to the extensive sky coverage and large halo sample in the BP-Uchuu maps. The BP-Uchuu maps are publicly available on https://app.globus.org/file-manager?origin_id=cf8dadb7-b6e9-4e2c-abc1-0813877efc13 .

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arXiv2024

Cosmology from HSC Y1 Weak Lensing with Combined Higher-Order Statistics and Simulation-based Inference

We present cosmological constraints from weak lensing with the Subaru Hyper Suprime-Cam (HSC) first-year (Y1) data, using a simulation-based inference (SBI) method. % We explore the performance of a set of higher-order statistics (HOS) including the Minkowski functionals, counts of peaks and minima, and the probability distribution function and compare them to the traditional two-point statistics. The HOS, also known as non-Gaussian statistics, can extract additional non-Gaussian information that is inaccessible to the two-point statistics. We use a neural network to compress the summary statistics, followed by an SBI approach to infer the posterior distribution of the cosmological parameters. We apply cuts on angular scales and redshift bins to mitigate the impact of systematic effects. Combining two-point and non-Gaussian statistics, we obtain $S_8 \equiv \sigma_8 \sqrt{\Omega_m/0.3} = 0.804_{-0.040}^{+0.041}$ and $\Omega_m = 0.344_{-0.090}^{+0.083}$, similar to that from non-Gaussian statistics alone. These results are consistent with previous HSC analyses and Planck 2018 cosmology. Our constraints from non-Gaussian statistics are $\sim 25\%$ tighter in $S_8$ than two-point statistics, where the main improvement lies in $\Omega_m$, with $\sim 40$\% tighter error bar compared to using the angular power spectrum alone ($S_8 = 0.766_{-0.056}^{+0.054}$ and $\Omega_m = 0.365_{-0.141}^{+0.148}$). We find that, among the non-Gaussian statistics we studied, the Minkowski functionals are the primary driver for this improvement. Our analyses confirm the SBI as a powerful approach for cosmological constraints, avoiding any assumptions about the functional form of the data's likelihood.

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arXiv2024

Perturbation Theory Remixed II: Improved Modeling of Nonlinear Bispectrum

We present the application of the $n$-th order Eulerian Perturbation Theory ($n$EPT) for modeling the matter bispectrum in real space as an advancement over the Standard Perturbation Theory (SPT). The $n$EPT method, detailed in Wang et al. (2023) \cite{Wang2023nEPT}, sums up the density perturbations up to the $n$-th order before computing summary statistics such as bispectrum. Taking advantage of grid-based calculation of SPT (GridSPT), we make a realization-based comparison of the analytical nonlinear bispectrum predictions from $n$EPT and SPT against a suite of $N$-body simulations. Using a spherical-bispectrum visualization scheme, we show that $n$EPT bispectrum matches better than SPT bispectrum over a wide range of scales in general $w$CDM cosmologies. Like the power spectrum case, we find that $n$EPT bispectrum modeling accuracy is controlled by $\sigma_8(z) \equiv \sigma_8 D(z)$, where $D(z)$ is the linear growth factor at a redshift $z$. Notably, the 6EPT doubles the bispectrum model's validity range compared to the one-loop SPT for $\sigma_8(z) < 0.5$, corresponding to redshifts $z\ge1$ for the best-fitting Planck-2018 cosmology. For $n\ge5$, however, $n$EPT bispectrum depends sensitively on the cut-off scale or the grid resolution. The percent-level modeling accuracy achieved for the spherical bispectrum (where we average over all triangular configurations) becomes much degraded when fixing configurations. Thus, we show that the validity range of the field-level cosmological inferences must be different from that derived from averaged summary statistics such as $n$-point correlation functions.

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arXiv2023

Cosmology from weak lensing peaks and minima with Subaru Hyper Suprime-Cam survey first-year data

We present cosmological constraints derived from peak counts, minimum counts, and the angular power spectrum of the Subaru Hyper Suprime-Cam first-year (HSC Y1) weak lensing shear catalog. Weak lensing peak and minimum counts contain non-Gaussian information and hence are complementary to the conventional two-point statistics in constraining cosmology. In this work, we forward-model the three summary statistics and their dependence on cosmology, using a suite of $N$-body simulations tailored to the HSC Y1 data. We investigate systematic and astrophysical effects including intrinsic alignments, baryon feedback, multiplicative bias, and photometric redshift uncertainties. We mitigate the impact of these systematics by applying cuts on angular scales, smoothing scales, statistic bins, and tomographic redshift bins. By combining peaks, minima, and the power spectrum, assuming a flat-$\Lambda$CDM model, we obtain $S_{8} \equiv \sigma_8\sqrt{\Omega_m/0.3}= 0.810^{+0.022}_{-0.026}$, a 35\% tighter constraint than that obtained from the angular power spectrum alone. Our results are in agreement with other studies using HSC weak lensing shear data, as well as with Planck 2018 cosmology and recent CMB lensing constraints from the Atacama Cosmology Telescope and the South Pole Telescope.

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