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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Mask-side Hyper-NA EUV imaging on the SHARP microscope

Hyper-NA, the prospective successor to high-numerical aperture (NA) extreme ultraviolet lithography (EUVL) could be inserted soon after 2030. Hyper-NA poses a number of challenges, including reduced depth of focus, amplified mask three-dimensional effects, and increased mask-side angular range. A Hyper-NA capable extreme ultraviolet (EUV) mask-imaging tool can address these challenges and accelerate research and development toward Hyper-NA. The Sharp High-Numerical Aperture Actinic Reticle Review Project (SHARP) EUV mask microscope is supporting mask-side high-NA imaging since 2015. Implementing mask-side Hyper-NA imaging in 2024 enables research and development toward the corresponding nodes of EUVL. Hyper-NA zoneplates at 0.75 4x/8x NA with a 6.7-deg chief ray angle and 0.85 4x/8x NA with a 7.4-deg chief ray angle are added to the SHARP microscope. Imaging at mask-side Hyper-NA is demonstrated. Imaging of 5-nm half-pitch (wafer scale) horizontal lines and spaces is demonstrated using dipole illumination. Imaging of 5-nm half-pitch (wafer scale) vertical lines and spaces is demonstrated using frequency-doubled imaging of 40-nm hp (mask scale) lines and spaces. Normalized image log slope (NILS) and modulation of Hyper-NA image data match closely to simulations for horizontal lines and spaces. A reduction in NILS of 0.3 or less is observed for vertical lines and spaces in the two-beam imaging regime. Through-focus image data are discussed, comparing different dipole sources and mask-side NAs. Mask-side Hyper-NA photomask imaging has been implemented and demonstrated on the SHARP microscope and is now available to users of the instrument.

Benk, Markus↗
DOE OSTI2023

Quantitative Characterization of Hyper-Local Atmospheric Greenhouse Gas Sources

Atmospheric greenhouse gas (GHG) emissions are often characterized using stationary, tower-based sensors. Ground based sensors reside in the turbulent boundary layer and are subject to intense concentration impulses from hyper-local (<100m) point sources of emissions. These high frequency spikes are often filtered out in broader emission flux studies, losing valuable information about how hyper-local sources influence receptors. In this study, we investigated how empirical atmospheric data can be used to locate and quantify a concurrently measured hyper-local point source in a dense urban setting. An eddy covariance style tower and a low-cost sensor tower were deployed in various locations around an urban, hyper-local CO2/CH4 emissions source (a continuously measured restaurant exhaust vent). A model using different processing and statistical techniques was built to examine the most effective procedures for source isolation, directional location, and emission quantification. Using excess concentrations above a minimum baseline, we identify the source using bivariate polar plots and quantify the relationship between source size, receptor distance, and statistical proxies. Furthermore, we find that varying statistical thresholds allows for identification of less influential sources which are drowned out by larger or closer sources. Finally, we show that large sources can be effectively characterized using low-cost sensors, a valuable outcome informing how networks for monitoring larger areas could be implemented. This work may provide a basis for source identification and monitoring protocols for networks that feature sensors influenced by hyper-local point sources, subject to site-specific assumptions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

S-OPT: A Points Selection Algorithm for Hyper-Reduction in Reduced Order Models

While projection-based reduced order models can reduce the dimension of full order solutions, the resulting reduced models may still contain terms that scale with the full order dimension. Hyper-reduction techniques are sampling-based methods that further reduce this computational complexity by approximating such terms with a much smaller dimension. The goal of this work is to introduce the points selection algorithm developed by Shin and Xiu as a hyper-reduction method. The selection algorithm was originally proposed as a stochastic collocation method for uncertainty quantification. Since the algorithm aims at maximizing a quantity $\mathcal{S}$ that measures both the column orthogonality and the determinant, we refer to the algorithm as S-OPT. Numerical examples are provided to demonstrate the performance of S-OPT and to compare its performance with a gappy proper orthogonal decomposition (POD) algorithm. Here, we found that using the S-OPT algorithm is shown to predict the full order solutions with higher accuracy than gappy POD especially when the number of sampling points is small, although we note that S-OPT shows slow asymptotic convergence with respect to the number of samples for some applications, e.g., Lagrangian hydrodynamics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Anthropogenic effects on flood hazards in a hyper-arid watershed: The 2015 Atacama floods

An unprecedented precipitation event in the hyper-arid Atacama Desert of Northern Chile occurred in March 2015. Geomorphic alterations to the river channel and the coastal zone, coupled with the exceptional magnitude of the rainfall, caused catastrophic damage and loss of life. On the coast of the El Salado watershed, legacy mine tailings infilled the watershed-ocean connection, while the river channel was altered both by tailings and urbanization. The consequences of this event resulted from the coupling of anthropogenic geomorphic changes with an unusual climate event. Lack of field data, complex geomorphology and sediment loads influenced by human activity make analysing floods in these regions especially challenging. The objective of this work is to improve our understanding of the factors that control flood hazards by using numerical simulations to reconstruct the 2015 flood in El Salado. We carry out unsteady two-dimensional simulations fully coupled with the sediment concentration to identify the influence of tailing deposits, considering high-resolution data of the pre- and post-2015 flood topography. In conclusion, the results highlight the importance of specific event-based studies, using models that can help designing better strategies for climate change adaptation and risk mitigation, while providing information for risk reduction and channel restoration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Hyper‐Local Temperature Prediction Using Detailed Urban Climate Informatics

The accurate modeling of urban microclimate is a challenging task given the high surface heterogeneity of urban land cover and the vertical structure of street morphology. Recent years have witnessed significant efforts in numerical modeling and data collection of the urban environment. Nonetheless, it is difficult for the physical‐based models to fully utilize the high‐resolution data under the constraints of computing resources. The advancement in machine learning (ML) techniques offers the computational strength to handle the massive volume of data. In this study, we proposed a modeling framework that uses ML approach to estimate point‐scale street‐level air temperature from the urban‐resolving meso‐scale climate model and a suite of hyper‐resolution urban geospatial data sets, including three‐dimensional urban morphology, parcel‐level land use inventory, and weather observations from a sensor network. We implemented this approach in the City of Chicago as a case study to demonstrate the capability of the framework. The proposed approach vastly improves the resolution of temperature predictions in cities, which will help the city with walkability, drivability, and heat‐related behavioral studies. Moreover, we tested the model's reliability on out‐of‐sample locations to investigate the modeling uncertainties and the application potentials to the other areas. This study aims to gain insights into next‐gen urban climate modeling and guide the observation efforts in cities to build the strength for the holistic understanding of urban microclimate dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Enabling Hyper-Differential Sensitivity Analysis for Ill-Posed Inverse Problems

Inverse problems constrained by partial differential equations (PDEs) play a critical role in model development and calibration. In many applications, there are multiple uncertain parameters in a model that must be estimated. However, high dimensionality of the parameters and computational complexity of the PDE solves make such problems challenging. A common approach is to reduce the dimension by fixing some parameters (which we will call auxiliary parameters) to a best estimate and use techniques from PDE-constrained optimization to estimate the other parameters. In this article, hyper-differential sensitivity analysis (HDSA) is used to assess the sensitivity of the solution of the PDE-constrained optimization problem to changes in the auxiliary parameters. Foundational assumptions for HDSA require satisfaction of the optimality conditions which are not always practically feasible as a result of ill-posedness in the inverse problem. Here we introduce novel theoretical and computational approaches to justify and enable HDSA for ill-posed inverse problems by projecting the sensitivities on likelihood informed subspaces and defining a posteriori updates. Our proposed framework is demonstrated on a nonlinear multiphysics inverse problem motivated by estimation of spatially heterogeneous material properties in the presence of spatially distributed parametric modeling uncertainties.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Representing Fine‐Scale Topographic Effects on Surface Radiation Balance in Hyper‐Resolution Land Surface Models

Land surface models are increasingly used to simulate land surface processes at hyper-spatial resolutions (e.g., ∼1 km). As model resolution increases, grid-scale topographic effects on surface radiation fluxes and their interactions between adjacent grids become more pronounced. However, current land surface models routinely neglect the fine-scale topographic effects on surface radiation balance. This study developed physically-based and computationally-efficient parameterizations (fineTOP) that explicitly resolve fine-scale topographic effects on downward shortwave and longwave radiation as well as land surface radiative properties. The newly developed parameterizations were implemented and tested in the Energy Exascale Earth System Model (E3SM) Land Model (ELM). Multi-decadal km-resolution ELM simulations over the California Sierra Nevada show that fine-scale topography significantly impacts the surface energy balance and snow processes across seasons. Slope determines the magnitude of topographic effects, while aspect controls their sign. For slopes larger than 30°, topography-induced change in annual surface temperature can be as large as 3.3 K. Regionally, the mean value and standard deviation of topography-induced changes in annual surface temperature are −0.22 ± 0.38 K and +0.25 ± 0.37 K over north-facing and south-facing slopes, respectively. Topography-induced changes in surface radiative properties account for 3.5% ± 13.8% of total topographic effects on annual net radiation. With fineTOP, ELM captures the aspect-dependence of snow cover fraction, snow water equivalent, and land surface temperature found in MODIS satellite observations and a snow reanalysis data set, while the default ELM fails to capture this phenomenon. The enhanced capability to represent fine-scale topographic effects on surface radiation balance can be used to advance understanding of the role of fine-scale topography in land surface processes and land-atmosphere interactions over mountainous regions.

Hao, Dalei [Pacific Northwest National Laboratory ↗
DOE OSTI2026

Recent efforts of vapour-phase strategies for EUV resist toward high- and hyper-NA extreme ultraviolet lithography

Extreme ultraviolet lithography (EUVL, λ = 13.5 nm) is critical for sub-1 nm technology nodes but remains constrained by inherent trade-offs among resolution, line-edge roughness (LER), and sensitivity. Stochastic effects originating from photon shot noise, low-energy secondary electron blur, and the random distribution of resist components further limit its advancement toward high numerical-aperture (NA, NA = 0.55) and hyper-NA (NA ≥0.75) EUVL. While the optimization of spin-on chemically amplified resists (CARs) continues, metal-oxide resists (MORs) have emerged as strong candidates for next-generation EUVL by incorporating metals with high EUV absorption coefficients, which enhances both resist sensitivity and etch resistance during pattern transfer. Besides spin-coating, recent advances in vapour-phase techniques, such as vapour-phase infiltration (VPI), chemical vapour deposition (CVD), and molecular atomic layer deposition (MALD), offer promising pathways to achieve new resist platforms, such as dry resists, that satisfy the stringent thickness and uniformity requirements of next-generation EUVL. These methods enable the direct incorporation of metal species into existing resist matrices or the formation of hybrid inorganic–organic resist platforms, thereby improving film uniformity, etch durability, and pattern fidelity while mitigating stochastic defects. This review highlights the latest advancements in vapour-phase-synthesized EUV resists, emphasizing material design, lithographic performance, and the underlying exposure mechanisms. Although still emerging, vapour-phase strategies are paving the way for an all-dry integration framework that could improve EUV patterning workflows and meet the demands of future technology nodes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

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 catalogue. 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, signal-to-noise ratio bins, and tomographic redshift bins. By combining peaks, minima, and the power spectrum, assuming a flat-ΛCDM model, we obtain S 8 ≡ σ 8 $\sqrt{Ω_m/0.3}$ = 0.810$^{+0.022}_{-0.026}$⁠, a 35 per cent 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.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Cosmological constraints using Minkowski functionals from the first year data of the Hyper Suprime-Cam

We use Minkowski functionals to analyse weak lensing convergence maps from the first-year data release of the Subaru Hyper Suprime-Cam (HSC-Y1) survey. Minkowski functionals provide a description of the morphological properties of a field, capturing the non-Gaussian features of the Universe matter-density distribution. Using simulated catalogues that reproduce survey conditions and encode cosmological information, we emulate Minkowski functionals predictions across a range of cosmological parameters to derive the best-fit from the data. By applying multiple scales cuts, we rigorously mitigate systematic effects, including baryonic feedback and intrinsic alignments. From the analysis, combining constraints of the angular power spectrum and Minkowski functionals, we obtain S8≡σ8Ωm/0.3=0.808−0.046+0.033 and Ωm=0.293−0.043+0.157⁠. These results represent a 40 per cent improvement on the S8 constraints compared to using power spectrum only. Minkowski functionals results are consistent with other two-point, and higher order statistics constraints using the same data, being in agreement with CMB results from the Planck S8 measurements. Our study demonstrates the power of Minkowski functionals beyond two-point statistics to constrain and break the degeneracy between Ωm and σ8⁠.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

First constraints from marked angular power spectra with Subaru Hyper Suprime-Cam Survey First-Year Data

We present the first application of marked power spectra to weak lensing data, using maps from the Subaru Hyper Suprime-Cam Year 1 (HSC-Y1) survey. Marked convergence fields, constructed by weighting the convergence field with non-linear functions of its smoothed version, are designed to encode higher-order information while remaining computationally tractable. Using simulations tailored to the HSC-Y1 data, we test three mark functions that up- or down-weight different density environments. Our results show that combining multiple types of marked auto and cross-spectra improves constraints on the clustering amplitude parameter S8≡σ8Ωm/0.3 by ≈43 per cent compared to standard two-point power spectra. When applied to the HSC-Y1 data, this translates into a constraint on S8=0.807±0.024⁠. We assess the sensitivity of the marked power spectra to systematics, including baryonic effects, intrinsic alignment, photometric redshifts, and multiplicative shear bias. We note that some of the additional information introduced by the marked field originates from scales smaller than the scale cut, and is partly Gaussian in nature. This does not invalidate our systematic tests. These results demonstrate the promise of marked statistics as a practical and powerful tool for extracting non-Gaussian information from weak lensing surveys.

Cowell, Jessica A. [Oxford U.; Tokyo U., IPMU] (OR↗
DOE OSTI2023

AGN number fraction in galaxy groups and clusters at z < 1.4 from the Subaru Hyper Suprime-Cam survey

Abstract One of the key questions on active galactic nuclei (AGN) in galaxy clusters is how AGN could affect the formation and evolution of member galaxies and galaxy clusters in the history of the Universe. To address this issue, we investigate the dependence of AGN number fraction (fAGN) on cluster redshift (zcl) and distance from the cluster center (R$/$R200). We focus on more than 27000 galaxy groups and clusters at 0.1 < zcl < 1.4 with more than 1 million member galaxies selected from the Subaru Hyper Suprime-Cam. By combining various AGN selection methods based on infrared (IR), radio, and X-ray data, we identify 2688 AGN. We find that (i) fAGN increases with zcl and (ii) fAGN decreases with R$/$R200. The main contributors to the rapid increase of fAGN towards high-z and cluster center are IR- and radio-selected AGN, respectively. These results indicate that the emergence of the AGN population depends on the environment and redshift, and galaxy groups and clusters at high z play an important role in AGN evolution. We also find that cluster–cluster mergers may not drive AGN activity in at least the cluster center, while we have tentative evidence that cluster–cluster mergers could enhance AGN activity in the outskirts of (particularly massive) galaxy clusters.

Hashiguchi, Aoi↗
DOE OSTI2024

Final results of the search for new Milky Way satellites in the Hyper Suprime-Cam Subaru Strategic Program survey: Discovery of two more candidates

Abstract We present the final results of our search for new Milky Way (MW) satellites using the data from the Hyper Suprime-Cam (HSC) Subaru Strategic Program (SSP) survey over ∼1140 deg2. In addition to three candidates that we have already reported, we have identified two new MW satellite candidates in the constellations of Sextans, at a heliocentric distance of D⊙ ≃ 126 kpc, and Virgo, at D⊙ ≃ 151 kpc, named Sextans II and Virgo III, respectively. Their luminosities (Sext II: MV ≃ −3.9 mag; Vir III: MV ≃ −2.7 mag) and half-light radii (Sext II: rh ≃ 154 pc; Vir III: rh ≃ 44 pc) place them in the region of size–luminosity space of ultra-faint dwarf galaxies (UFDs). Including four previously known satellites, there are a total of nine satellites in the HSC-SSP footprint. This discovery rate of UFDs is much higher than that predicted from the recent models for the expected population of MW satellites in the framework of cold dark matter models, thereby suggesting that we encounter a too many satellites problem. Possible solutions to settle this tension are also discussed.

Homma, Daisuke↗
DOE OSTI2023

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, galaxy-galaxy weak lensing, and projected galaxy clustering, measured from the Hyper Suprime-Cam three-year (HSC-Y3) shape catalog and the Sloan Digital Sky Survey (SDSS) DR11 spectroscopic galaxy catalog—a cosmology analysis. We define luminosity-cut, and therefore nearly volume-limited, samples of SDSS galaxies to serve as the tracers of w p and as the lens samples for Δ⁢Σ in three spectroscopic redshift bins spanning the range 0.15± and Δ⁢Σ measurements, we use a single sample of about seven million source galaxies over 416 deg 2 , selected from HSC-Y3 based on having photometric redshifts (photo-z) greater than 0.75. The deep, high-quality HSC-Y3 data enable significant detections of the Δ⁢Σ signals, with integrated signal-to-noise ratio S/N~24 in the range 3≤R/[ℎ –1 Mpc]≤30 over the three lens samples. ξ ± has S/N ~19 in the range 8' ≤$\theta$ ≤5⁢0' and 30' ≤$\theta$ ≤15⁢0' for ξ + and ξ – , respectively. For cosmological parameter inference, we use the dark emulator package, combined with a halo occupation distribution prescription for the relation between galaxies and halos, to model w p and Δ⁢Σ down to quasinonlinear scales, and we estimate cosmological parameters after marginalizing over nuisance parameters. In our baseline analysis we employ an uninformative flat prior of the residual photo-z error, given by Π⁡(Δz ph )=$U$⁡(–1,1), to model a residual bias in the mean redshift of HSC source galaxies. Comparing the relative lensing amplitudes for Δ⁢Σ in the three redshift bins and for ξ ± with the single HSC source galaxy sample allows us to calibrate the photo-z parameter Δ⁢z ph to the precision of σ⁡(Δ⁢z ph )≃0.09. With these methods, we obtain a robust constraint on the cosmological parameters for the flat Λ⁢CDM model: S 8 =σ 8 ⁢(Ω m /0.3) 0.5 =$0.763^{+0.040}_{–0.036}$, or the best-constrained parameter given by $S^{'}_{8}$ = σ 8 ⁢(Ω m /0.3) 0.22 =0.721±0.028, determined with about 4% fractional precision. Based on multidimensional tension metrics, HSC-Y3 data exhibits about 2.5σ tension with the cosmological constraint inferred by Planck for the Λ⁢CDM model, and hints at a nonzero residual photo-z bias implying that the true mean redshift of the HSC galaxies at z ≳0.75 is higher than that implied by the original photo-z estimates.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Hyper Suprime-Cam Year 3 results: Cosmology from cosmic shear two-point correlation functions

Here, we perform a blinded cosmology analysis with cosmic shear two-point correlation functions 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/arcmin < 56.6 for ξ + and 31.2 < θ/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 m = 0.25⁢6$^{+0.056}_{–0.044}$ and S 8 ≡ σ 8 ⁢$\sqrt{Ω_{m}/0.3}$ = 0.76⁢9$^{+0.031}_{–0.034}$ (both 68% C.I.) 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 × 2 pt 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.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Hyper Suprime-Cam Year 3 results: Cosmology from cosmic shear power spectra

Here, we measure weak lensing cosmic shear power spectra from the 3-year galaxy shear catalog of the Hyper Suprime-Cam (HSC) Subaru Strategic Program imaging survey. The shear catalog covers 416 deg 2 of the northern sky, with a mean i-band seeing of 0.59 arcsec and an effective galaxy number density of 15 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 ≤ z ph ≤ 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 < ℓ < 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 ≡ σ 8 (Ω m /0.3) 0.5 = ${0.776}_{—0.033}^{+0.032}$, 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 ~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 ~ 0.5σ, indicating that our result is robust to such systematics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Hyper Suprime-Cam Year 3 results: Measurements of clustering of SDSS-BOSS galaxies, galaxy-galaxy lensing, and cosmic shear

Here we utilize the Sloan Digital Sky Survey Baryon Oscillation Spectroscopic Survey (SDSS-BOSS) galaxies and its overlap with approximately 416 sq degrees of deep grizy-band imaging from the Subaru Hyper Suprime-Cam Survey (HSC). We perform measurements of three two-point correlations which 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 projected matter correlation function on large scales with a proportionality constant dependent on the bias of galaxies. In order to help break the degeneracy between the amplitude of the matter correlation and the bias of these spectroscopic galaxies, we use the distortions of the shapes of fainter galaxies in HSC due to weak gravitational lensing, to measure the galaxy-galaxy lensing signal, which probes the projected galaxy-matter cross-correlation function 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 by subjecting each of them to 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 Lambda Cold Dark Matter model. Finally, we use these mock catalogs to compute the covariance of each of our observables.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Hyper Suprime-Cam Year 3 results: Cosmology from galaxy clustering and weak lensing with HSC and SDSS using the minimal bias model

Here, we present cosmological parameter constraints from a blind joint analysis of three two-point correlation functions measured from the Year 3 Hyper Suprime-Cam (HSC-Y3) imaging data, covering about 416 deg 2 , and the SDSS DR11 spectroscopic galaxies spanning the redshift range [0.15, 0.70]. We subdivide the SDSS galaxies into three luminosity-cut, and therefore nearly volume-limited samples separated in redshift, each of which acts as a large-scale structure tracer characterized by the measurement of the projected correlation function, w p ⁡(R). We also use the measurements of the galaxy-galaxy weak-lensing signal Δ⁢Σ⁡(R) for each of these SDSS samples which act as lenses for a secure sample of source galaxies selected from the HSC-Y3 shape catalog based on their photometric redshifts. We combine these measurements with the cosmic shear correlation functions, ξ ± ⁡($\vartheta$) measured for our HSC source sample. We model these observables with the minimal bias model of the galaxy clustering observables in the context of a flat Λ⁢CDM cosmology. We use conservative scale cuts, R >12 and 8⁢ℎ -1 Mpc for Δ⁢Σ and w p , respectively, where the minimal bias model is valid, in addition to conservative prior on the residual bias in the mean redshift of the HSC photometric source galaxies. We present various validation tests of our model as well as analysis methods. Our baseline analysis yields S 8 = $0.77⁢5^{+0.043}_{-0.038}$ (68% C.I.) for the Λ⁢CDM model, after marginalizing over uncertainties in other parameters. Our value of S 8 is consistent with that from the Planck 2018 data, but the credible interval of our result is still relatively large. We show that various internal consistency tests based on different splits of the data are passed. Our results are statistically consistent with those of a companion paper, which extends this analysis to smaller scales with an emulator-based halo model, using Δ⁢Σ⁡(R) and w p ⁡(R) down to R >3 and 2⁢ℎ -1 Mpc, respectively.

79 ASTRONOMY AND ASTROPHYSICS↗