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At least 37 records · Page 2

A High-Quality Workflow for Multi-Resolution Scientific Data Reduction and Visualization

Multi-resolution methods such as Adaptive Mesh Refinement (AMR) can enhance storage efficiency for HPC applications generating vast volumes of data. However, their applicability is limited and cannot be universally deployed across all applications. Furthermore, integrating lossy compression with multi-resolution techniques to further boost storage efficiency encounters significant barriers. To this end, we introduce an innovative workflow that facilitates high-quality multi-resolution data compression for both uniform and AMR simulations. Initially, to extend the usability of multi-resolution techniques, our workflow employs a compression-oriented Region of Interest (ROI) extraction method, transforming uniform data into a multi-resolution format. Subsequently, to bridge the gap between multi-resolution techniques and lossy compressors, we optimize three distinct compressors, ensuring their optimal performance on multi-resolution data. These optimizations can improve the compression ratio of SOTA approaches by up to 3.3× under the same data quality loss. Lastly, we incorporate an advanced uncertainty visualization method into our workflow to understand the potential impacts of lossy compression. Experimental evaluation demonstrates that our workflow achieves significant compression quality improvements.

Wang, Daoce↗

Associations between regional blood-brain barrier permeability, aging, and Alzheimer’s disease biomarkers in cognitively normal older adults

Background Increased blood-brain barrier permeability (BBBp) has been hypothesized as a feature of aging that may lead to the development of Alzheimer’s disease (AD). We sought to identify the brain regions most vulnerable to greater BBBp during aging and examine their regional relationship with neuroimaging biomarkers of AD. Methods We studied 31 cognitively normal older adults (OA) and 10 young adults (YA) from the Berkeley Aging Cohort Study (BACS). Both OA and YA received dynamic contrast-enhanced MRI (DCE-MRI) to quantify K trans values, as a measure of BBBp, in 37 brain regions across the cortex. The OA also received Pittsburgh compound B (PiB)-PET to create distribution volume ratios (DVR) images and flortaucipir (FTP)- PET to create partial volume corrected standardized uptake volume ratios (SUVR) images. Repeated measures ANOVA assessed the brain regions where OA showed greater BBBp than YA. In OA, K trans values were compared based on sex, Aβ positivity status, and APOE4carrier status within a composite region across the areas susceptible to aging. We used linear models and sparse canonical correlation analysis (SCCA) to examine the relationship between K trans and AD biomarkers. Results OA showed greater BBBp than YA predominately in the temporal lobe, with some involvement of parietal, occipital and frontal lobes. Within an averaged ROI of affected regions, there was no difference in K trans values based on sex or Aβ positivity, but OA who were APOE4carriers had significantly higher K trans values. There was no direct relationship between averaged K trans and global Aβ pathology, but there was a trend for an Ab status by tau interaction on K trans in this region. SCCA showed increased K trans was associated with increased PiB DVR, mainly in temporal and parietal brain regions. There was not a significant relationship between K trans and FTP SUVR. Discussion Our findings indicate that the BBB shows regional vulnerability during normal aging that overlaps considerably with the pattern of AD pathology. Greater BBBp in brain regions affected in aging is related to APOE genotype and may also be related to the pathological accumulation of Aβ.

Science & Technology - Other Topics↗

HERO WEC V1.0 2024 - WEC-Sim Detailed Simulation Runs and Summary Data

This dataset includes results from simulations of NREL's hydraulic and electric reverse osmosis wave energy converter (HEREO WEC). Simulation runs include 135 wave cases that were based on the updated WEC-Sim model, which is linked below. The data represented in this repository is based on an updated WEC-Sim model using laboratory data to tune and refine the original WEC-Sim model for the V1.0 HERO WEC. The 135 wave cases represent waves with the following wave height and wave period ranges: - Significant Wave Height: 0.25 - 3.75m in 0.25m increments - Wave Period: 5 - 13 sec in 1 sec increments Each run was simulated using a Pierson-Moskowitz irregular wave spectrum with a 100 second ramp time, a total simulation time of 3,100 seconds, and a simulation time-step of 0.005s. A reference table has been included to map each multi condition run (MCR) case with each wave condition. Summary data set includes a spreadsheet and image files with matrices that are associated with data from simulation runs. All matrices cover the same significant wave height and wave periods from the simulation runs, in the same increments. The following matrices are included: - Power Abs: The average absorbed power from the WEC (calculated from anchor reaction force and heave velocity) - Power Hyd: The average hydraulic power output at pump (calculated from pump output flow and pressure) - Power - Hyd ROi: The average hydraulic power measured at the RO system inlet (calculated from RO system pressure and flow (pre-accumulator)) - Flow - Pump out: The average flowrate measured at the pump outlet - Flow - Perm: The average permeate (clean water) production - Flow - RO (pre): The average flowrate measured at the inlet of the RO system before the accumulators - Flow - RO (post): The average flowrate measured after the accumulator bank in the RO system - Pressure - RO: The average pressure measured at the inlet of the RO system This data set has been developed by the National Renewable Energy Laboratory, operated by the Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Water Power Technologies Office.

16 TIDAL AND WAVE POWER↗

Disruptive Technology for Carbon Negative Commodity Chemicals

This project was designed to develop an economically attractive process for the carbon negative production of the commodity biochemical succinic acid. To compete against petroleum derived biochemicals, the process must deliver high raw material conversion efficiency and high volumetric productivity to reduce both recurring and capital-related costs, respectively. The proposed process introduces additional electrons sourced from hydrogen into the biosynthetic pathway so that the carbon from two CO2 molecules can be combined with each glucose to significantly increase succinic acid yields. The process also uses ultrafiltration to continuously remove the product from the bioreactor to avoid product inhibition and extend the productive life of the cell extract. Genetic deletions and specific enzyme removal during extract preparation more efficiently direct both atomic and electronic resources toward product formation. A preliminary technoeconomic analysis indicates that these process innovations made possible by cell-free production will enable large scale production with attractive ROI and profitability. This two-year project provided some 29 distinct insights, analytical advances, and process improvements that resulted in a demonstration of process feasibility. However, an estimated two to three years of additional development will be required to achieve convincing pilot scale demonstrations that will motivate large scale investments.

60 APPLIED LIFE SCIENCES↗

Assessment and Simulation of Particulate Transport for Delivery of Solid Amendments into the Subsurface: FY25 Status Report

For particulate-based amendments to be viable for field-scale remediation at the Hanford Site (e.g., the 200 DV-1 Operable Unit), amendment particles need to be delivered a reasonable distance away from an injection well to provide cost effective in situ treatment. Field-scale particle transport models can estimate spatial deposition of amendment particles in the subsurface, which is critical for developing an overall remediation strategy. However, field-scale particle simulations are currently limited due to insufficient simulation capability and a lack of experimental data to validate and parameterize particle transport models. During this fiscal year, the following progress has been made toward a field-scale particle transport modeling evaluation: (1) in addition to the two particle transport models implemented last FY, four additional particle transport models have been implemented within PFLOTRAN; (2) a Python-based pre-screening tool was finalized, enabling users to quickly estimate the particle radius of influence (ROI) for any given particle-amendment system; and (3) an initial compatibility assessment was completed using both particle transport simulations deployed through the pre-screening tool, in conjunction with general guidelines to (a) identify the most suitable amendment particle sizes for various Hanford sediments and (b) evaluate amendment-delivery fluid compatibility. The preliminary compatibility assessment revealed that for amendment delivery success to the various Hanford target formations, amendment particle sizes will likely need to be smaller than the amendment sizes tested in the DV-1 treatability study. It is recommended that amendment particles be decreased in size, or alternative smaller size amendments be obtained from the manufacture, prior to any further experimental testing. Also, preliminary testing suggests that xanthan gum may be the most broadly compatible delivery fluid. Planned laboratory experiments will be instrumental in validating and refining the PFLOTRAN particulate transport model formulations, ultimately enabling predictive capabilities to facilitate the design of field-scale amendment delivery systems. This work consists of acquiring new theoretical or experimental knowledge. The information associated with this report should not be used as design input or operating parameters without additional qualification.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

TASTI-GRID: Overview of the State of Oregon’s Resilience and Reliability [Slides]

This report is intended to help your state identify the most effective investments to improve grid resilience and reliability, based on analysis of outage data, weather events, and the current state of the electric grid. The information presented is derived from the best available data. The discussions and recommendations included provide context and valuable insights into potential high returns on investment (ROI). Specifically, the report offers an overview of electric grid resilience in Oregon, covering outage information, reasons for outages, calculated "resilience scores" across the state, and recommendations for both immediate and long-term investments in grid infrastructure. The document provides a concise overview of the analytical capabilities of the TASTI-GRID team. By utilizing additional data and resources, it synthesizes insights from the platform to present a distinct perspective on investing in grid resilience throughout Oregon. This document is not intended to influence or direct state-level decisions related to investments in grid resilience and reliability. TASTI-GRID should not be used for real-time monitoring, supporting the ESF #12 emergency response functions, or predicting the restoration times for outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗

JUSTIFI: Open-Source Software for Identifying and Quantifying Non-Energy Benefits

The integration of Non-Energy Benefits (NEBs) into energy efficiency initiatives is essential for operational excellence in manufacturing. This presentation and software demonstration explore how quantifying NEBs such as improved safety, increased quality, and enhanced productivity, can strengthen business cases for energy investments, leading to better payback periods and alignment with organizational goals. We introduce JUSTIFI, a free, open-source software by the U.S. Department of Energy that aids in the measurement of NEBs and enhances understanding of their impact on Key Performance Indicators (KPIs) and return on investment (ROI). JUSTIFI features an intuitive interface for identifying NEBs, customizable reporting tools, and comprehensive system cataloging, empowering companies to effectively communicate the value of energy efficiency projects. By leveraging this innovative tool, organizations can better navigate energy efficiency assessments and drive support for their energy management initiatives.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Improving Performance via Energy Efficiency JUSTIFI: Open-Source Software for Identifying and Quantifying Non-Energy Benefits

Energy efficiency is pivotal to achieving operational excellence, as it enhances value while reducing waste. This presentation explores the integration of non-energy benefits (NEBs) into energy efficiency projects, which can lead to risk reduction, value creation, and cost savings. By quantifying NEBs - such as improved safety, decreased pollution, and increased productivity - companies can strengthen their business cases for energy investments, ultimately improving payback periods and aligning with strategic goals. Designed for a diverse audience, from trained auditors to novices in energy assessments, we have developed open-source software called JUSTIFI, NEB finding methodology, and training materials which build on existing frameworks and leverages resources from the U.S. Department of Energy and Better Plants energy system analysis software suite such as MEASUR. This work aims to maximize ROI through NEB identification, utilizing tools like JUSTIFI and the NEBs Discovery Protocol.

97 MATHEMATICS AND COMPUTING↗

Advancing Artificial Intelligence with Liquid Argon Neutrino Experiments (Technical Report)

The grant allowed two main contributions: 1) The development of a first successful demonstration of the employment of Optimal Transport in liquid argon time projection chamber neutrino detectors. Optimal Transport, used in other contexts and specifically with LHC calorimetric data, was adapted to address a key particle identification challenge in LArTPCs: the separation of pi0 backgrounds from single-electrons produced in charged-current electron neutrino interactions. The work, leveraging ML methods such as k-nearest-neighbor (kNN) and support-vector-machine (SVM), showed an increase in background rejection of a factor of two or more. Work is now ongoing to incorporate this development in physics analyses for LArTPC experiments and more broadly expand the use of OT in LArTPC detectors including DUNE. This work was done in collaboration with the phenomenology group led by Nathaniel Craig at UCSB. 2) The deployment of NuGraph2, a graph neural network developed for LArTPC reconstruction, in the MicroBooNE experiment. NuGraph2 uses novel graph-neural-network methods on the rather simple LArTPC inputs of reconstructed hits, greatly simplifying the workflow compared to the use of waveform or signal-deconvolved wire ROIs. The network performed particle classification and was shown to address many challenging problems in LArTPC imaging including track-shower separation and the identification of protons and charged pions from primary muons. Our group collaborated with Giuseppe Cerati (FNAL scientist) who is one of the core developers of NuGraph2 to integrate this tool in MicroBooNE’s analysis framework. This consisted in tow key contributions: a) Studying performance on real data, which came with several months of iterations because the MC-trained version of the network was found to show significant bias that our group investigated and addressed. b) Integrating the output hit labeling of NuGraph2 into the existing particle tracking and shower reconstruction code. As a result of this work led by our team NuGraph2 is now enabling a suite of new analyses which benefit from enhanced capabilities and thus broader physics reach. The grant supported primarily the salary of UCSB graduate student Chuyue “Michaelia” Fang as well as partial summer salary support for PI Caratelli. Some funds were used for travel by Michaelia to ML related schools and conferences.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Return on Investment and Sustainability of HVDC Links: Role of Diagnostics, Condition Monitoring, and Material Innovations

HVDC cable systems are becoming an upscaled technical option, compared to AC, because of various factors, including easier interconnections, lower losses, and longer transmission distances. In addition, renewables providing direct DC energy, electrified transportation, and aerospace where DC can be favored because of higher carried specific power all point in the direction of broad future usage of HV and MV DC links. However, contrary to AC, there is little return from on-field installation as regards long-term cable reliability and aging processes. This gap must be covered by intensive research, and contributing to this research is the purpose of this paper. The focus is on key points for HVDC (and MVDC) cable reliability and sustainability, from design modeling able to account for voltage transients and extrinsic aging (such as that caused by partial discharges) to the impact of aging on insulation conductivity (which rules the electric field distribution, thus aging rate). Also, recyclable and nanostructured materials, as well as health conditions, are considered. It is shown how cable design can account for accelerated aging due to voltage transients, as well as for aging-time dependence of conductivity, and how design can be free of extrinsic aging caused by PDs. Algorithms for health condition evaluations, which have additional value in a relatively new technology such as HVDC polymeric cables, are applied to insulation system aging under partial discharges, showing how they can provide an indication of insulation degradation globally or locally (weak spots) and of possible maintenance times. All of this can effectively contribute to reducing the risk of major cable breakdown and damage under operation, which would significantly affect the return on investment (ROI).

Montanari, Gian Carlo (ORCID:0000000320258693)↗

Evaluating Direct and Indirect Influence on EV Charging Stations Across the US

The adoption of new technology for electric vehicles (EV) and mobility applications can bring underappreciated vulnerabilities to the power grid. One area of potential fraud and adversarial influence is through the business ecosystem of startups that own and deploy EV technology. Yet, there are no models or analyses that map the network of organizations and people that have direct and indirect influence over technologies currently deployed in the grid. To fill this gap, we develop a multilayer network model to measure direct and indirect influence on EV charging stations. First, we create and adversarial socio-technical network (ASTN) model via a data fusion pipeline for different US regions of interest (ROI). Then, we develop an integrated ASTN for Chicago, Los Angeles, New York, and Philadelphia. We rank EV charging companies direct influence within each geographic region as well as indirect influence via social network analysis. While some companies have strong direct and indirect influence (i.e., ChargePoint) others show a mismatch between their influence over charging stations and their position within the social network. For example, Tesla has strong direct influence on stations and weak indirect influence over competitors. In contrast, 7Charge has weak direct influence over stations, but strong indirect influence over competitors.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

A Simple Panel System to Overcome Interface Challenges for Retrofits: Preprint

Retrofitting buildings is usually an expensive and labor-intensive process. Weatherization measures can improve comfort and energy affordability to some extent, but deep energy retrofits are needed to optimize performance and comfort, and to achieve significant energy cost savings. Barriers to deep energy retrofits include a limited supply of skilled labor, different building types, planning complexity, split incentives, and a long or non-existent ROI horizon. The "Simple Panel System" (SPS) workflow developed and demonstrated in this effort streamlines deep energy retrofits by applying advanced site capture, machine learning, and mixed reality to panelized construction. The result is a one-stop, product-independent solution for rapidly scalable retrofits with the potential to reduce construction time and project costs by 50%. Soft costs are reduced by more than 66%, total costs by more than 50%, and field construction time by more than 50% - not to mention the reduction in construction waste, improvement in working conditions, and the ability to scale without an influx of skilled labor. This paper presents the SPS and the preliminary results and findings from the pilot project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Deep desert aquifers as an archive for Mid- to Late Pleistocene hydroclimate: An example from the southeastern Mediterranean

Many efforts have been made to illuminate the nature of past hydroclimates in semi-arid and arid regions, where current and future shifts in water availability have enormous consequences on human subsistence. Deep desert aquifers, where groundwater is stored for prolonged periods, might serve as a direct record of major paleo-recharge events. To date, groundwater-based paleoclimate reconstructions have mainly focused on a relatively narrow timescale (up to ∼40 kyr), limited by the relatively short half-life of the widely used radiocarbon (5.73 kyr). Here we demonstrate the usage of deep regional aquifers in the arid southeastern Mediterranean as a hydroclimate archive for earlier Mid-to-Late Pleistocene epochs. State-of-the-art dating tools, primarily the 81 Kr radioisotope (t 1/2 = 229 kyr), were combined with other atmosphere-derived tracers to illuminate the impact of four distinguishable wetter episodes over the past 400 kyr, with differences in climatic conditions and paleo-recharge locations. Variations in stable water isotope composition suggest moisture transport from more proximal (Mediterranean) and distal (Atlantic) sources to different parts of the region at distinct times. Large variability in the computed noble gas-based recharge temperature (NGT), ranging ~15–30 °C, cannot be explained by climate variations solely, and points to different recharge pathways, including geothermal heating in the deep unsaturated zone and recharge from high-elevation (colder) regions. The obtained groundwater record complements and enhances the interpretation of other terrestrial archives in the arid region, including a contribution of valuable information regarding the moisture source origin as reflected in the deuterium-excess values, which is unattainable from the common practice analysis of calcitic cave deposits. We conclude that similar applications in other deep (hundred-m-order) regional groundwater systems (e.g., the Sahara desert aquifers) can significantly advance our understanding of long-term (up to 1 Myr) paleo-hydroclimate in arid regions, including places where no terrestrial remnants, such as cave, lake, and spring sediments, are available.

Atom Trap Trace Analysis↗

Assessment of integral models for non-Boussinesq lazy plumes using numerical simulations

Integral modelling of turbulent buoyant plumes is crucial for rapid predictions of plume characteristics. While the governing equations are typically derived using self-similarity and a Boussinesq approximation, these assumptions may not hold for plumes originating from finite-area sources with large density ratios. Here, this work evaluates the accuracy of integral-scale models for non-Boussinesq lazy plumes using high-fidelity numerical simulations of turbulent helium plumes. We analyse the plume kinematics by computing vertical fluxes, plume radius and radial profiles, establishing some disparities between common practice and physical accuracy. We identify how the definition of the plume radius changes the perception of the plume structure when the flow is not self-similar and derive a relationship between the flux-based and threshold-based definitions without requiring self-similarity. We then examine the plume dynamics by evaluating the source terms from the governing plume equations. Our results support neglecting diffusive and viscous effects but emphasise the importance of the mean pressure gradient, even in the self-similar regime. Two coefficients need to be modelled: the well-known entrainment coefficient and the lesser-known momentum correction coefficient, which is a correction required for the momentum equation to account for self-similar and slender approximations. The momentum correction coefficient is found to be approximately constant and slightly greater than the assumed value of 1. The standard entrainment coefficient models perform well up to a local Richardson number three times the asymptotic value but overpredict entrainment for larger Richardson numbers. We propose a correction using the known finite limit of entrainment at infinite Richardson number.

Meehan, Michael Alexander [Sandia National Laborat↗

Reproducibility of Radiokrypton in Deep Desert Aquifers: Insights from a Decade of Research

Great technical advances have been achieved since the first atom-trap trace analysis (ATTA) -based radiokrypton application in Egypt, where 1 Myr old groundwater was discovered. Beyond advances in ATTA measurement capabilities, including reduction in sample size, analysis duration, and analytical uncertainty, major progress has been achieved over the past two decades in the sample collection and preparation techniques. These advances paved the expansion of ATTA-based noble gas applications to many other aquifers worldwide, illuminating the nature and flow pattern of deep groundwater systems. While the potential of this new analytical technique for old groundwater dating is well recognized, another important aspect yet to be examined is the reproducibility of radiokrypton in aquifers over time, i.e., how representative is a discrete groundwater sample, collected at a specific time and location, for the natural groundwater system? The likelihood of a negative answer is increased by flow-field disturbance in aquifers following massive groundwater abstraction. Here, in this work, we present repeated 81 Kr sampling and measurements in twenty-one sites over Israel, mostly of deep (up to 1 km) wells tapping confined aquifers in the arid to hyperarid Negev desert. The results demonstrate that radiokrypton measurements are indeed reproducible, even in cases where samples were collected as long as nine years apart and from highly productive (∼1 Mm 3 /yr order) pumping wells. Furthermore, many of the repeated measurements in this study (17 out of the 21 sites) were conducted with different ATTA Instruments in two different laboratories using slightly different sampling, preparation, and analysis techniques, yet with an overall good agreement. The consistency in the ATTA-based 81 Kr-dating results over time highlights the robustness of this state-of-the-art technique as a tool to unravel groundwater flow patterns and encourages further applications to many other yet-to-be-explored deep aquifers.

atom-trap trace analysis↗

Integrative mapping reveals molecular features underlying the mechanism of nucleocytoplasmic transport

Nuclear pore complexes (NPCs) enable rapid, selective, and robust nucleocytoplasmic transport. To explain how transport emerges from the system components and their interactions, we used experimental data and theoretical information to construct an integrative Brownian dynamics model of transport through an NPC, coupled to a kinetic model of transport in the cell. The model recapitulates key aspects of transport for a wide range of molecular cargoes, including preribosomes and viral capsids. Our model quantifies how flexible phenylalanine-glycine (FG) repeat proteins create an entropic barrier to passive diffusion and how this barrier is selectively lowered in facilitated diffusion by the many transient interactions of nuclear transport receptors with the FG repeats. Selective transport is enhanced by “fuzzy” multivalent interactions, redundant FG repeat mass, coupling to the energy-dependent RanGTP concentration gradient, and exponential dependence of transport kinetics on the transport barrier. Our model will facilitate rational modulation of the NPC and its artificial mimics.

Raveh, Barak [School of Computer Science and Engin↗

Dark photon constraints from CMB temperature anisotropies

The resonant conversion, within the inter-galactic medium, of regular photons into dark photons amplifies the anisotropy observed in the CMB, thereby imposing stringent constraints on the existence of light dark photons. In this study, we investigate the impact of light dark photons, with masses in the range 3 × 10$^{-15}$ eV < mA' < 3 × 10$^{-12}$ eV on the power spectrum of temperature anisotropies within the cosmic microwave background (CMB) radiation utilizing the state-of-the-art large-volume FLAMINGO cosmological simulations. Our results show that using full Planck data, one can expect the existing constraints on the dark photon mixing parameter in this mass range to improve by an order of magnitude.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

FLAMINGO: combining kinetic SZ effect and galaxy–galaxy lensing measurements to gauge the impact of feedback on large-scale structure

Energetic feedback processes associated with accreting supermassive black holes can expel gas from massive haloes and significantly alter various measures of clustering on $\sim$Mpc scales, potentially biasing the values of cosmological parameters inferred from analyses of large-scale structure (LSS) if not modelled accurately. Here, we use the state-of-the-art FLAMINGO suite of cosmological hydrodynamical simulations to gauge the impact of feedback on large-scale structure by comparing to Planck + ACT stacking measurements of the kinetic Sunyaev–Zel’dovich (kSZ) effect of SDSS BOSS galaxies. We make careful like-with-like comparisons to the observations, aided by high precision KiDS and DES galaxy–galaxy lensing measurements of the BOSS galaxies to inform the selection of the simulated galaxies. In qualitative agreement with several recent studies using dark matter only simulations corrected for baryonic effects, we find that the kSZ effect measurements prefer stronger feedback than predicted by simulations which have been calibrated to reproduce the gas fractions of low redshift X-ray-selected groups and clusters. We find that the increased feedback can help to reduce the so-called $S_8$ tension between the observed and CMB-predicted clustering on small scales as probed by cosmic shear (although at the expense of agreement with the X-ray group measurements). However, the increased feedback is only marginally effective at reducing the reported offsets between the predicted and observed clustering as probed by the thermal SZ (tSZ) effect power spectrum and tSZ effect – weak lensing cross-spectrum, both of which are sensitive to higher halo masses than cosmic shear.

79 ASTRONOMY AND ASTROPHYSICS↗