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NASA NTRS2005

A New Approach to using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 kilometers, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-kilometer scales are resolved in horizontal domains as large as 10,000 kilometers in two dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗

NASA NTRS2005

A New Approach to Using a Cloud-resolving Model to Study the Interactions Between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as l0,OOO km in two-dimensions, and 1,OOO x 1,OOO km2 in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗

NASA NTRS2005

A New Approach to using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗

NASA NTRS2006

Using Multi-scale Modeling System to Study the Interactions between Clouds, Precipitation, Aerosols, Radiation and Land Surface

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 kilometers, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-kilometer scales are resolved in horizontal domains as large as 10,000 kilometers in two-dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. A review of developments, improvements and applications of cloud models (GCE and WRF) at Goddard will be presented in this talk. In particular, a new approach to using multi-scale modeling system to study the interactions between clouds, precipitation, aerosols and land will be presented.

Tao, Wei-Kuo↗

NASA NTRS2006

Using Multi-scale Modeling System to Study the Interactions between Clouds, Precipitation, Aerosols, Radiation and Land Surface

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 kilometers, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial-lkm scales are resolved in horizontal domains as large as 10,000 kilometers in two-dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. A review of developments, improvements and applications of cloud models (GCE and WRF) at Goddard wlll be is presented in this talk. In particular, a new approach to using multi-scale modeling system to study the interactions between clouds, precipitation, aerosols and land will be presented.

Tao, Wei-Kuo↗

NASA NTRS2007

Using Multi-scale Modeling Systems to Study the Precipitation Processes

Tao, Wei-Kuo↗

NASA NTRS2008

A Multi-Scale Modeling System with Unified Physics

Tao, Wei-Kuo↗

NASA NTRS2006

Using Multi-scale Modeling System to Study the Interactions between Clouds, Precipitation, Aerosols, Radiation and Land Surface

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 sq km in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. A review of developments, improvements and applications of cloud models (GCE and WRF) at Goddard will be presented in this talk. In particular, a new approach to using multi-scale modeling system to study the interactions between clouds, precipitation, aerosols and land will be presented.

Tao, Wei-Kuo↗

NASA NTRS2004

Deep-Sea Video Cameras Without Pressure Housings

Underwater video cameras of a proposed type (and, optionally, their light sources) would not be housed in pressure vessels. Conventional underwater cameras and their light sources are housed in pods that keep the contents dry and maintain interior pressures of about 1 atmosphere (.0.1 MPa). Pods strong enough to withstand the pressures at great ocean depths are bulky, heavy, and expensive. Elimination of the pods would make it possible to build camera/light-source units that would be significantly smaller, lighter, and less expensive. The depth ratings of the proposed camera/light source units would be essentially unlimited because the strengths of their housings would no longer be an issue. A camera according to the proposal would contain an active-pixel image sensor and readout circuits, all in the form of a single silicon-based complementary metal oxide/semiconductor (CMOS) integrated- circuit chip. As long as none of the circuitry and none of the electrical leads were exposed to seawater, which is electrically conductive, silicon integrated- circuit chips could withstand the hydrostatic pressure of even the deepest ocean. The pressure would change the semiconductor band gap by only a slight amount . not enough to degrade imaging performance significantly. Electrical contact with seawater would be prevented by potting the integrated-circuit chip in a transparent plastic case. The electrical leads for supplying power to the chip and extracting the video signal would also be potted, though not necessarily in the same transparent plastic. The hydrostatic pressure would tend to compress the plastic case and the chip equally on all sides; there would be no need for great strength because there would be no need to hold back high pressure on one side against low pressure on the other side. A light source suitable for use with the camera could consist of light-emitting diodes (LEDs). Like integrated- circuit chips, LEDs can withstand very large hydrostatic pressures. If power-supply regulators or filter capacitors were needed, these could be attached in chip form directly onto the back of, and potted with, the imager chip. Because CMOS imagers dissipate little power, the potting would not result in overheating. To minimize the cost of the camera, a fixed lens could be fabricated as part of the plastic case. For improved optical performance at greater cost, an adjustable glass achromatic lens would be mounted in a reservoir that would be filled with transparent oil and subject to the full hydrostatic pressure, and the reservoir would be mounted on the case to position the lens in front of the image sensor. The lens would by adjusted for focus by use of a motor inside the reservoir (oil-filled motors already exist).

Cunningham, Thomas↗

DOE OSTI2025

Cosmological constraints from the Planck cluster catalogue with DES shear profiles and Chandra observations

We present cosmological constraints from the Planck PSZ2 cosmological cluster sample, using weak-lensing shear profiles from Dark Energy Survey (DES) data and X-ray observations from the Chandra telescope for the mass calibration. We compute hydrostatic mass estimates for all clusters in the PSZ2 sample with a scaling relation between their Sunyaev-Zeldovich signal and X-ray derived hydrostatic mass, calibrated with the Chandra data. We introduce a method to correct these masses with a hydrostatic mass bias using shear profiles from wide-field galaxy surveys. We simultaneously fit the number counts of the PSZ2 sample and the mass calibration with the DES data, finding $Ω_\text{m}=0.312^{+0.018}_{-0.024}$, $σ_8=0.777\pm 0.024$, $S_8\equiv σ_8 \sqrt{Ω_\text{m} / 0.3}=0.791^{+0.023}_{-0.021}$, and $(1-b)=0.844^{+0.055}_{-0.062}$ for our baseline analysis when combined with BAO data. When considering a hydrostatic mass bias evolving with mass, we find $Ω_\text{m}=0.353^{+0.025}_{-0.031}$, $σ_8=0.751\pm 0.023$, and $S_8=0.814^{+0.019}_{-0.020}$. We verify the robustness of our results by exploring a variety of analysis settings, with a particular focus on the definition of the halo centre used for the extraction of shear profiles. We compare our results with a number of other analyses, in particular two recent analyses of cluster samples obtained from SPT and eROSITA data that share the same mass calibration data set. We find that our results are in overall agreement with most late-time probes, in very mild tension with CMB results (1.6$σ$), and in significant tension with results from eROSITA clusters (2.9$σ$). We confirm that our mass calibration is consistent with the eROSITA analysis by comparing masses for clusters present in both Planck and eROSITA samples, eliminating it as a potential cause of tension.

Aymerich, G. [Orsay, IAS; AIM, Saclay] (ORCID:0009↗

DOE OSTI2021

Strength, deformation, and equation of state of tungsten carbide to 66 GPa

Here, strength, texture, and equation of state of hexagonal tungsten monocarbide (WC) have been determined under quasi-hydrostatic and non-hydrostatic compression to 66 GPa using angle-dispersive X-ray diffraction in the diamond anvil cell. Quasi-hydrostatic compression in a Ne pressure medium demonstrates that nanocrystalline WC is slightly less incompressible than bulk-scale WC, with respective bulk moduli of K 0 = 377 ± 7 and 397 ± 7 GPa and pressure derivatives K 0 ’ = 3.8 ± 0.3 and 3.7 ±0.3. This decrease in incompressibility with grain size is similar to behavior observed in other ceramics. Under nonhydrostatic compression, WC supports a mean differential stress of ~12-15 GPa at plastic yielding, which occurs at ~30 GPa. Strength in WC is anisotropic, with the (001) plane supporting 29-42% higher stress than stresses calculated from mean strain. Simulations using an Elasto-ViscoPlastic Self-Consistent model indicate that strength inferred from lattice strain theory may be overestimated due to effects of plastic deformation. Plastic deformation generates a texture maximum near $\langle\bar{2}110\rangle$ in the compression orientation, initially through prismatic slip on the {$10\bar{1}0$}$\langle\bar{1}2\bar{1}0\rangle$ and {$10\bar{1}0$}$\langle0001\rangle$ slip systems, followed by activation of pyramidal slip on {$10\bar{1}1$}$\langle\bar{2}113\rangle$ at ~40-50 GPa.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Dislocation nano-hydrides in nickel: Nucleation, evolution and effects on dislocation behaviors

Nano-hydrides have been predicted to precipitate at the core of edge dislocations in the Ni-H system, a mechanism that may promote hydrogen embrittlement. However, nano-hydride nucleation, growth, and effects on dislocation behavior have seldom been explored. This work combines molecular dynamics grand canonical Monte Carlo (MD-GCMC) simulations and continuum modeling to uncover a wide range of phenomena linked to dislocation nano-hydrides. Simulations reveal that nano-hydrides can be stabilized at dislocation cores with all character angles, including screw segments, due to the hydrostatic stresses around the cores of the Shockley partials. Nano-hydride nucleation takes place in these regions, and growth is dictated by the character angle θ of the perfect dislocation. The equilibrium stacking fault width d eq varies dynamically to increase the local hydrostatic stress field and facilitate the formation of the nano-hydride, forming a constriction-like feature and leading to three distinct behaviors: d eq decreases for θ > 30°, d eq remains unchanged for θ = 30°, and d eq increases for θ < 30°. Remote hydrostatic and Escaig stresses are also shown to influence the nucleation stage, implying stress concentrations such as those ahead of crack tips may facilitate nano-hydride precipitation. Moreover, we identify a new hydrogen-induced 60° dislocation reaction that emits a Shockley partial on a conjugate plane, with potential implications for twin nucleation. Testable predictions from this study are then used to reinterpret previous results from the literature. In conclusion, these findings provide a comprehensive framework to assess nano-hydride formation and evolution at dislocations in nickel and other face-centered cubic metals, with important implications to hydrogen embrittlement.

Dislocations↗

DOE OSTI2020

Microstructural and micro-mechanical analysis of 14YWT nanostructured Ferritic alloy after varying thermo-mechanical processing paths into tubing

Microstructural analyses and micro-pillar compression were conducted on 14YWT nanostructured ferritic alloy (NFA) to compare different processing pathways: hydrostatic extrusion and Pilger processing with varying annealing temperatures into thin walled tubing, and after hot extrusion and cross-rolling into a plate. Hydrostatic extrusion at 815 °C resulted in the smallest grain sizes and highest yield strength of 1.20 GPa. Pilger processing with annealing at 800 °C had fine grained regions and bands of coarse grains, leading to a large variation in yield strength of 0.9–1.40 GPa. Higher annealing temperatures of 1200 °C after pilger processing significantly increased the grain size and lowered the yield strength to 1.01 GPa. These tubes showed a stronger (111) crystallographic texture in the normal direction and elongated grains in the extrusion direction. Characterization of the nano-oxides using TEM reveals more numerous, smaller oxides present in tubing processed at lower temperatures. Overall, this work shows NFA tubing after hydrostatic extrusion and pilger processing can lead to fine grained microstructures and texturing leading to higher yield strengths at lower annealing temperatures (e.g. 800 °C).

14YWT↗

DOE OSTI2022

A high accuracy/resolution spectral element/Fourier–Galerkin method for the simulation of shoaling non-linear internal waves and turbulence in long domains with variable bathymetry

A high-order hybrid continuous-Galerkin numerical method, designed for the simulation of non-linear, non -hydrostatic internal waves and turbulence in long computational domains with complex bathymetry, is presented. The spatial discretization in the non-periodic wave-propagating directions, utilizes the nodal spectral element method. Such a high-order element-based discretization allows the highly accurate representation of complex domain geometry along with the flexibility of concentrating resolution in areas of interest. Under the assumption of the normal-to-isobath propagation of non-linear internal waves, a third periodic direction is incorporated via a Fourier-Galerkin discretization. The distinct non-hydrostatic nature of non-linear internal waves and, any instabilities and turbulence therein, necessitates the numerically challenging solution of the pressure Poisson problem. A defining feature of this work is the application of a domain decomposition approach, combined with block-Jacobi/deflation-based preconditioning to the pressure Poisson problem. Such a combined approach is particularly suitable for the long high aspect-ratio complex domains of interest and enables the efficient high-accuracy reproduction of the non-hydrostatic dynamics of non-linear internal waves. Implementation details are also described in the context of the stability of the solver and its parallelization strategy. A series of benchmarks of increasing complexity demonstrate the robustness of the flow solver. The benchmarks culminate with the three-dimensional simulation of a convectively breaking mode-one non-linear internal wave over a realistic South-China-Sea bathymetric transect and background current/stratification profiles.

Deflation↗

DOE OSTI2024

Deviatoric stress-induced metallization, layer reconstruction and collapse of van der Waals bonded zirconium disulfide

In contrast to two-dimensional (2D) monolayer materials, van der Waals layered transition metal dichalcogenides exhibit rich polymorphism, making them promising candidates for novel superconductor, topological insulators and electrochemical catalysts. Here, we highlight the role of hydrostatic pressure on the evolution of electronic and crystal structures of layered ZrS2. Under deviatoric stress, our electrical experiments demonstrate a semiconductor-to-metal transition above 30.2 GPa, while quasi-hydrostatic compression postponed the metallization to 38.9 GPa. Both X-ray diffraction and Raman results reveal structural phase transitions different from those under hydrostatic pressure. Under deviatoric stress, ZrS2 rearranges the original ZrS6 octahedra into ZrS8 cuboids at 5.5 GPa, in which the unique cuboids coordination of Zr atoms is thermodynamically metastable. The structure collapses to a partially disordered phase at 17.4 GPa. These complex phase transitions present the importance of deviatoric stress on the highly tunable electronic properties of ZrS2 with possible implications for optoelectronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Heterostructure design to achieve high quality, high density GaAs 2D electron system with g -factor tending to zero

Hydrostatic pressure is a useful tool that can tune several key parameters in solid state materials. For example, the Landé g-factor in GaAs two-dimensional electron systems (2DESs) is expected to change from its bulk value g ≃ -0.44 to zero and even to positive values under sufficiently large hydrostatic pressure. Although this presents an intriguing platform to investigate electron-electron interaction in a system with g = 0, studies are quite limited because the GaAs 2DES density decreases significantly with increasing hydrostatic pressure. Here, we show that a simple model, based on pressure-dependent changes in the conduction band alignment, quantitatively explains this commonly observed trend. Furthermore, we demonstrate that the decrease in the 2DES density can be suppressed by more than a factor of 3 through an innovative heterostructure design.

Physics↗

DOE OSTI2021

Structural transitions of 4:1 methanol–ethanol mixture and silicone oil under high pressure

A 4:1 (volume ratio) methanol–ethanol (ME) mixture and silicone oil are two of the most widely used liquid pressure-transmitting media (PTM) in high-pressure studies. Their hydrostatic limits have been extensively studied using various methods; however, the evolution of the atomic structures associated with their emerging nonhydrostaticity remains unclear. Here, we monitor their structures as functions of pressure up to ∼30 GPa at room temperature using in situ high-pressure synchrotron x-ray diffraction (XRD), optical micro-Raman spectroscopy, and ruby fluorescence spectroscopy in a diamond anvil cell. No crystallization is observed for either PTM. The pressure dependence of the principal diffraction peak position and width indicates the existence of a glass transition in the 4:1 ME mixture at ∼12 GPa and in the silicone oil at ∼3 GPa, beyond which a pressure gradient emerges and grows quickly with pressure. There may be another liquid-to-liquid transition in the 4:1 ME mixture at ∼5 GPa and two more glass-to-glass transitions in the silicone oil at ∼10 GPa and ∼16 GPa. By contrast, Raman signals only show peak weakening and broadening for typical structural disordering, and Raman spectroscopy seems to be less sensitive than XRD in catching these structural transitions related to hydrostaticity variations in both PTM. These results uncover rich pressure-induced transitions in the two PTM and clarify their effects on hydrostaticity with direct structural evidence. The high-pressure XRD and Raman data on the two PTM obtained in this work could also be helpful in distinguishing between signals from samples and those from PTM in future high-pressure experiments.

Chen, Xiehang (ORCID:0000000168541506)↗

DOE OSTI2026

Weak Lensing Mass Calibration of the ACT DR5 Galaxy Clusters with the DES Year 3 Weak Lensing Data

We use weak gravitational lensing measurements from Year 3 Dark Energy Survey data to calibrate the masses of 443 galaxy clusters selected via the Sunyaev-Zel'dovich effect from Atacama Cosmology Telescope Data Release 5 maps of the cosmic microwave background. We incorporate redshift and SZ measurements for individual clusters into a hierarchical model for the stacked lensing signals and perform Bayesian analyses to constrain the hydrostatic mass bias of the clusters. Our treatment of systematic uncertainties includes a prescription for measuring and accounting for the weak lensing boost factor, consideration of a miscentering effect, as well as marginalization over uncertainties in the source galaxy photometric redshift distributions and shear calibration. The resultant constraints on the normalization of the mass-observable relation have a precision of approximately 7%, with the mean WL halo mass of M $_{500c}$ = 5.4 × 10$^{14}$ M $_{⊙}$. We measure the bias between the true cluster mass and the mass estimated from the SZ signal based on an X-ray-calibrated scaling relation assuming hydrostatic equilibrium, to be 1 - b = 0.74$^{+0.06}$ $_{-0.05}$ over the full sample. When splitting the clusters into high (z = 0.43-0.70) and low (z = 0.15-0.43) redshift bins, we measure 1 - b = 0.58$^{+0.06}$ $_{-0.05}$ and 0.81$^{+0.08}$ $_{-0.06}$, respectively. When introducing additional freedom in redshift and mass to the hydrostatic bias model, we find that 1 - b decreases with redshift (with the power law of -1.8$^{+0.5}$ $_{-0.6}$, 99.95% confidence), consistent with findings from other recent studies, while we do not find any significant trend in mass. We also demonstrate that our result is robust against various systematics such as a scale cut, priors on baryonic and miscentering parameters, and degree of scatter in mass-observable relation. The weak-lensing mass calibration presented in this study will be a useful tool for using the ACT clusters as probes of astrophysics, and as a step towards using their abundance as a cosmological probe.

Shin, T. [Carnegie Mellon U.] (ORCID:0000000263895↗