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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Marine Corps Base Camp Lejeune New River Estuary (NRE) Regions

Critical military training and testing on lands along the nation’s coastal and estuarine shorelines are increasingly placed at risk because of encroachment pressures in surrounding areas, impairments due to other anthropogenic disturbances, and changes in climate and sea level. The U.S. Department of Defense (DoD) intends to enhance and sustain its training and testing assets and also optimize its stewardship of natural resources through the development and application of an ecosystem-based management approach on DoD installations. To accomplish this goal, particularly for installations in estuarine/coastal environments, the Strategic Environmental Research and Development Program (SERDP) launched the Defense Coastal/Estuarine Research Program (DCERP) as a 10-year effort at Marine Corps Base Camp Lejeune (MCBCL) in North Carolina. The results of the second 5 years of the program (DCERP2) are presented in the DCERP2 Final Report.There were four overarching objectives of DCERP2. The first objective was to understand the effects of climate change impacts, including warming temperatures, variability in the hydrological cycle, storm events, and sea level rise on the coastal ecosystems at MCBCL from observations and measurements made over the 10-year program. The second objective was to understand the carbon cycle of the coastal and terrestrial ecosystems at MCBCL through a highly integrated sampling program. The third objective was to develop models, tools, and indicators to evaluate current and projected future ecosystem state changes and translate scientific findings into actionable information for installation managers. The last objective was to recommend adaptive management strategies to sustain ecosystem natural resources within the context of an active military installation.The New River Estuary regions were digitized using desktop GIS and elevation data to determine the watershed boundaries and bathymetry data is determined by the water depth. Geographic representation of box and flow model produced by DCERP aquatic & esturaine module team, includes micro-watershed data. A spatial approximation of the areas defined in the Estuarine Simulation Model developed by Mark Brush.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Mesoscale Cellular Convection Detection and Classification Using Convolutional Neural Networks: Insights From Long-Term Observations at ARM Eastern North Atlantic Site

Marine boundary layer clouds are crucial in Earth's climate system. They frequently manifest as closed or open cell mesoscale cellular convection (MCC). MCC clouds are challenging to represent accurately in current climate models, highlighting the need for detailed observational data sets and in-depth analyses. This study utilizes over 8 years of observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility Eastern North Atlantic (ENA) site at Graciosa Island, Azores, to investigate these clouds. We first apply a convolutional neural network with a U-Net architecture to classify open and closed cells, marking the first application of such an approach for automatically detecting MCC patterns from ground-based radar measurements. This method addresses some observational gaps in satellite data related to low temporal resolution, nighttime challenges, and limited vertical structure capture. The analysis of the MCC cases shows clear differences between closed and open MCCs: Closed MCC clouds are characterized by lower cloud tops and bases, shallower cloud geometrical depth, weaker horizontal wind speeds, stronger atmospheric stability, and a more homogeneous liquid water path than open MCCs. Finally, we demonstrate two potential applications of our radar-based MCC classifications: (a) facilitating the investigation of aerosol-cloud interactions and (b) exploring meteorological factors along with MCC's evolution by integrating satellite imagery and back-trajectory analysis. The identified MCC cases offer a valuable resource for the scientific community to study MCC processes further and improve climate model accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Interface properties and built-in potential profile of a LaCr O 3 / SrTi O 3 superlattice determined by standing-wave excited photoemission spectroscopy

LaCrO 3 (LCO)/SrTiO 3 (STO) heterojunctions are intriguing due to a polar discontinuity along [001], exhibiting two distinct and controllable charged interface structures [(LaO) + /(TiO 2 ) 0 and (SrO) 0 /(CrO 2 ) - ] with induced polarization, and a resulting depth-dependent potential. In this study, we have used soft- and hard-x-ray standing-wave excited photoemission spectroscopy (SW-XPS) to quantitatively determine the elemental depth profile, interface properties, and depth distribution of the polarization-induced built-in potentials. We observe an alternating charged interface configuration: a positively charged (LaO) + /(TiO 2 ) 0 intermediate layer at the LCO top /STO bottom interface and a negatively charged (SrO) 0 /(CrO 2 ) - intermediate layer at the STO top /LCO bottom interface. Using core-level SW data, we have determined the depth distribution of species, including through the interfaces, and these results are in excellent agreement with scanning transmission electron microscopy and electron energy-loss spectroscopy mapping of local structure and composition. SW-XPS also enabled deconvolution of the LCO and STO contributions to the valence-band (VB) spectra. Using a two-step analytical approach involving first SW-induced core-level binding-energy shifts and then VB modeling, the variation in potential across the complete superlattice is determined in detail. As a result, this potential is in excellent agreement with density functional theory models, confirming this method as a generally useful tool for interface studies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2012

EBT2 film as a depth-dose measurement tool for radiotherapy beams over a wide range of energies and modalities

Purpose: One of the fundamental parameters used for dose calculation is percentage depth-dose, generally measured employing ionization chambers. There are situations where use of ion chambers for measuring depth-doses is difficult or problematic. In such cases, radiochromic film might be an alternative. The EBT-2 model GAFCHROMIC film was investigated as a potential tool for depth-dose measurement in radiotherapy beams over a broad range of energies and modalities. Methods: Pieces of the EBT-2 model GAFCHROMIC EBT2 film were exposed to x-ray, electron, and proton beams used in radiotherapy. The beams employed for this study included kilovoltage x-rays (75 kVp), {sup 60}Co gamma-rays, megavoltage x-rays (18 MV), electrons (7 and 20 MeV), and pristine Bragg-peak proton beams (126 and 152 MeV). At each beam quality, film response was measured over the dose range of 0.4-8.0 Gy, which corresponds to optical densities ranging from 0.05 to 0.4 measured with a flat-bed document scanner. To assess precision in depth-dose measurements with the EBT-2 model GAFCHROMIC film, uncertainty in measured optical density was investigated with respect to variation in film-to-film and scanner-bed uniformity. Results: For most beams, percentage depth-doses measured with the EBT-2 model GAFCHROMIC film show an excellent agreement with those measured with ion chambers. Some discrepancies are observed in case of (i) kilovoltage x-rays at larger depths due to beam-hardening, and (ii) proton beams around Bragg-peak due to quenching effects. For these beams, an empirical polynomial correction produces better agreement with ion-chamber data. Conclusions: The EBT-2 model GAFCHROMIC film is an excellent secondary dosimeter for measurement of percentage depth-doses for a broad range of beam qualities and modalities used in radiotherapy. It offers an easy and efficient way to measure beam depth-dose data with a high spatial resolution.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2019

Differences in Ice Cloud Optical Depth From CALIPSO and Ground-Based Raman Lidar at the ARM SGP and TWP Sites

Ice cloud column optical depths from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite and ground-based Raman lidars (RLs) at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) and Tropical Western Pacific (TWP) sites are compared for 8 and 4 years, respectively. The cloudy mean ice cloud column optical depths from CALIPSO Version 4 data product with a horizontal resolution of 5 km are 78% (63%) larger than those from the RLs with a resolution of 10 min/30 m at SGP (TWP) for collocated transparent profiles. The main difference at SGP is caused by the lidar ratio that for CALIPSO is related to its treatment of the multiple scattering factor. The main difference at TWP is caused by the averaging resolution. Large differences in the optical depth distribution between the CALIPSO and RL are found for small optical depths at both sites, which are due to optically very thin clouds only detectable by the RLs. The differences in ice cloud column optical depth distributions and their mean values between the CALIPSO and RL can largely be reconciled over both sites after accounting for the averaging resolutions, lidar ratios along with the CALIPSO multiple scattering factor treatment, sensitivity to optically very thin ice clouds, and definition of transparent profiles. This work also examines in detail the lidar ratios that are directly observed by the RLs, which does not support the temperature-dependent parameterizations of ice cloud lidar ratio and multiple scattering factor used in CALIPSO's Version 4 data product.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

LOG-NORMAL DISTRIBUTION OF COSMIC VOIDS IN SIMULATIONS AND MOCKS

Following up on previous studies, we complete here a full analysis of the void size distributions of the Cosmic Void Catalog based on three different simulation and mock catalogs: dark matter (DM), haloes, and galaxies. Based on this analysis, we attempt to answer two questions: Is a three-parameter log-normal distribution a good candidate to satisfy the void size distributions obtained from different types of environments? Is there a direct relation between the shape parameters of the void size distribution and the environmental effects? In an attempt to answer these questions, we find here that all void size distributions of these data samples satisfy the three-parameter log-normal distribution whether the environment is dominated by DM, haloes, or galaxies. In addition, the shape parameters of the three-parameter log-normal void size distribution seem highly affected by environment, particularly existing substructures. Therefore, we show two quantitative relations given by linear equations between the skewness and the maximum tree depth, and between the variance of the void size distribution and the maximum tree depth, directly from the simulated data. In addition to this, we find that the percentage of voids with nonzero central density in the data sets has a critical importance. If the number of voids with nonzero central density reaches ≥3.84% in a simulation/mock sample, then a second population is observed in the void size distributions. This second population emerges as a second peak in the log-normal void size distribution at larger radius.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Quantitatively Monitoring Bubble-Flow at a Seep Site Offshore Oregon: Field Trials and Methodological Advances for Parallel Optical and Hydroacoustical Measurements

Two lander-based devices, the Bubble-Box and GasQuant-II, were used to investigate the spatial and temporal variability and total gas flow rates of a seep area offshore Oregon, United States. The Bubble-Box is a stereo camera–equipped lander that records bubbles inside a rising corridor with 80 Hz, allowing for automated image analyses of bubble size distributions and rising speeds. GasQuant is a hydroacoustic lander using a horizontally oriented multibeam swath to record the backscatter intensity of bubble streams passing the swath plain. The experimental set up at the Astoria Canyon site at a water depth of about 500 m aimed at calibrating the hydroacoustic GasQuant data with the visual Bubble-Box data for a spatial and temporal flow rate quantification of the site. For about 90 h in total, both systems were deployed simultaneously and pressure and temperature data were recorded using a CTD as well. Detailed image analyses show a Gaussian-like bubble size distribution of bubbles with a radius of 0.6–6 mm (mean 2.5 mm, std. dev. 0.25 mm); this is very similar to other measurements reported in the literature. Rising speeds ranged from 15 to 37 cm/s between 1- and 5-mm bubble sizes and are thus, in parts, slightly faster than reported elsewhere. Bubble sizes and calculated flow rates are rather constant over time at the two monitored bubble streams. Flow rates of these individual bubble streams are in the range of 544–1,278 mm 3 /s. One Bubble-Box data set was used to calibrate the acoustic backscatter response of the GasQuant data, enabling us to calculate a flow rate of the ensonified seep area (~1,700 m 2 ) that ranged from 4.98 to 8.33 L/min (5.38 × 10 6 to 9.01 × 10 6 CH 4 mol/year). Such flow rates are common for seep areas of similar size, and as such, this location is classified as a normally active seep area. For deriving these acoustically based flow rates, the detailed data pre-processing considered echogram gridding methods of the swath data and bubble responses at the respective water depth. The described method uses the inverse gas flow quantification approach and gives an in-depth example of the benefits of using acoustic and optical methods in tandem.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Substantial and overlooked greenhouse gas emissions from deep Arctic lake sediment - supporting data and code

This data package contains data, descriptions, and code-based analyses that were used to support conclusions drawn in “Substantial and overlooked greenhouse gas emissions from deep Arctic lake sediment”, by Freitas et al. (2025) (https://doi.org/10.1038/s41561-024-01614-y). The study evaluated greenhouse gas production along a deep sediment core (20 m) taken in 2018 from below Goldstream Lake, a field site approximately 15 km north of Fairbanks, Alaska.The file “ESSDive_NFreitas_2024_flmd.csv” includes an overview of all other csv files in this data package, namely: sediment descriptions (depth and type of sediment), sediment characterizations (bulk density, gravimetric water content, total carbon, etc.), calculated respiration and temperature sensitivity values associated with year-long incubations of the sediment core, and the R code used to process the dataset. Additional details regarding the content of these files and how the calculations were performed are described in the Methods section of this archive. The “data_dictionary_ESSDive_NFreitas_2024_dd.csv” is a data dictionary for all files included in the data package. Each row in the data dictionary represents a column name in a given file. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).Data package updates- August 2024: Title was updated, R code now includes a process for calculating potential production across the whole sediment column, the "sediment_column_production_potentials_ESSDive_NFreitas_2024.csv" is the associated data output file, and the file level metadata and data dictionaries were updated to reflect the contents of the additional csv file.- October 2024: Title was updated, and a statement was added to Step 2 of the Methods that describes that samples were collected (and exported) in a responsible manner and in accordance with relevant permits and local laws.- January 2025: Updated the associated manuscript details in the Abstract (manuscript title, publication date, DOI link) and in the Related References section (full citation).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Microstructures and Rheology of the Earth Upper Mantle Inferred from a Multiscale Approach

The strongly anisotropic rheology of olivine polycrystals, associated to their microstructure, constitutes a key feature affecting the dynamics of the Earth's upper mantle. High pressure deformation experiments carried out on olivine single crystals under synchrotron radiation, together with estimations of lattice friction based on first-principle calculations, show a transition from easy [100] to easy [001] slips as pressure and temperature (thus depth) increases. We input these data at the slip system level into the second-order extension of the self-consistent scheme to assess microstructure evolution along a typical flow pattern beneath an oceanic spreading center.

58 GEOSCIENCES↗
DOE OSTI2012

Atom probe tomography characterisation of a laser diode structure grown by molecular beam epitaxy

Atom probe tomography (APT) has been used to achieve three-dimensional characterization of a III-nitride laser diode (LD) structure grown by molecular beam epitaxy (MBE). Four APT data sets have been obtained, with fields of view up to 400 nm in depth and 120 nm in diameter. These data sets contain material from the InGaN quantum well (QW) active region, as well as the surrounding p- and n-doped waveguide and cladding layers, enabling comprehensive study of the structure and composition of the LD structure. Two regions of the same sample, with different average indium contents (18% and 16%) in the QW region, were studied. The APT data are shown to provide easy access to the p-type dopant levels, and the composition of a thin AlGaN barrier layer. Next, the distribution of indium within the InGaN QW was analyzed, to assess any possible inhomogeneity of the distribution of indium (''indium clustering''). No evidence for a statistically significant deviation from a random distribution was found, indicating that these MBE-grown InGaN QWs do not require indium clusters for carrier localization. However, the APT data show steps in the QW interfaces, leading to well-width fluctuations, which may act to localize carriers. Additionally, the unexpected presence of a small amount (x = 0.005) of indium in a layer grown intentionally as GaN was revealed. Finally, the same statistical method applied to the QW was used to show that the indium distribution within a thick InGaN waveguide layer in the n-doped region did not show any deviation from randomness.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Cosmological preference for a negative neutrino mass

The most precise determination of the sum of neutrino masses from cosmological data, derived from analysis of the cosmic microwave background (CMB) and baryon acoustic acoustic oscillations (BAO) from the Dark Energy Spectroscopic Instrument (DESI), favors a value below the minimum inferred from neutrino flavor oscillation experiments. We explore which data is most responsible of this puzzling aspect of the current constraints on neutrino mass and whether it is related to other anomalies in cosmology. We demonstrate conclusively that the preference for negative neutrino masses is a consequence of larger than expected lensing of the CMB in both the two- and four-point lensing statistics. Furthermore, we show that this preference is robust to changes in likelihoods of the BAO and CMB optical depth analyses given the available data. We then show that this excess clustering is not easily explained by changes to the expansion history and is likely distinct from the preference for for dynamical dark energy in DESI BAO data. Finally, we discuss how future data may impact these results, including an analysis of Planck CMB with mock DESI 5-year data. Here, we conclude that the negative neutrino mass preference is likely to persist even as more cosmological data is collected in the near future.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Strategies for Flood Resilience and Grid Investment Among Iowa's Electric Distribution Utilities

Flooding poses a growing threat to Iowa's electric distribution system, yet utilities face significant data and modeling challenges in planning effective resilience investments. This report provides a foundational assessment of how distribution utilities in Iowa, investor-owned, municipal, and cooperative, approach resilience planning, with a focus on flood risk. It combines hazard characterization, review of state and utility practices, and application of NLR's Energy Resilience Analysis for Distribution Systems (ERAD) and Capacity Expansion Decision Support for Distribution Networks (CADET) tools. Using FEMA floodplains, Iowa Flood Center depth grids, and utility infrastructure data, the analysis quantifies asset exposure, simulates outage risks, and evaluates resilience strategies such as pole hardening, undergrounding, and substation protection. Results indicate that while feeder-level upgrades provide incremental benefits, the most significant reductions in outage risk are achieved through targeted substation interventions. The report highlights key data gaps, such as limited elevation data and fragility functions, and underscores the need for probability-weighted investment frameworks to address both frequent and catastrophic flood events. These insights aim to support utilities, state agencies, and federal partners in prioritizing resilience investments that safeguard Iowa's electric grid against future flooding.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Kinetic and temperature sensitivity properties of soil exoenzymes through the soil profile down to one-meter depth at a temperate coniferous forest (Blodgett, CA)

This dataset contains data on kinetic and temperature sensitivity parameters of the exoenzymes β-glucosidase (BG), leucine/leucyl aminopeptidase (LAP) and acid phosphatase (AP) across a soil profile down to 90 cm depth at Blodgett forest, CA, USA. These data were generated to determine if kinetic and thermal properties of microbial exoenzymes involved in organic matter decomposition varied with soil depth, following variation in soil properties and microbial communities, as part of the study: Alves et al. (2021). Kinetic Properties of Microbial Exoenzymes Vary with Soil Depth but Have Similar Temperature Sensitivities Through the Soil Profile. Frontiers in Microbiology 12:3618. https://doi.org/10.3389/fmicb.2021.735282. This research was performed within the framework of the TES Belowground Biogeochemistry SFA project, in particular association with a long-term field warming experiment of the whole soil profile at Blodgett forest. Samples for this work were collected from locations representative of the field experimental plots. Potential enzyme activity rates were measured using laboratory fluorometric assays with soils collected at 0-10, 10-20, 30-40, 50-60, 60-70 and 80-90 cm deep in biological triplicates (i.e., three soil cores collected at different representative locations). Assays with each soil were conducted over a gradient of eight substrate concentrations per enzyme, and incubated at 4, 10, 16, 25, 35 or 50°C. Enzyme Michaelis-Menten kinetics were modeled over the eight substrate concentrations at each temperature, and the temperature sensitivity of the kinetic parameters was modeled over the six temperatures using linear Arrhenius/Q10 and non-linear Macromolecular Rate Theory (MMRT) models. The dataset includes the fully processed enzyme activity rate data used to model Michaelis-Menten kinetics, calculated kinetic and temperature sensitivity parameters, and basic soil and microbial biomass chemistry for each sample. All data is provided for each individual biological replicate, and kinetic and temperature sensitivity parameters are also provided as means of the biological replicates. The dataset also includes all raw measurement data and code used to parse, combine and perform the analyses described by Alves et al. (2021). For file descriptions, see the file-level metadata files: “enzymes_dataProcessed_flmd.xlsx” (processed data); “enzymes_dataRaw_flmd.xlsx” (compressed raw data and metadata); and “enzymes_code_flmd.xlsx” (compressed code). The experimental design, list of parameters measured, soil and microbial biomass chemistry data, and means of biological replicates for kinetic and temperature sensitivity parameters are also provided as human-readable tables in file “enzymeTraits_design_results_tables.xlsx”.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Soybean Roots Grown under Heat Stress Show Global Changes in Their Transcriptional and Proteomic Profiles

Heat stress is likely to be a key factor in the negative impact of climate change on crop production. Heat stress significantly influences the functions of roots, which provide support, water, and nutrients to other plant organs. Likewise, roots play an important role in the establishment of symbiotic associations with different microorganisms. Despite the physiological relevance of roots, few studies have examined their response to heat stress. Here in this study, we performed genome-wide transcriptomic and proteomic analyses on isolated root hairs, which are a single, epidermal cell type, and compared their response to stripped roots. On average, we identified 1849 and 3091 genes differentially regulated in root hairs and stripped roots, respectively, in response to heat stress. Our gene regulatory module analysis identified 10 key modules that might control the majority of the transcriptional response to heat stress. We also conducted proteomic analysis on membrane fractions isolated from root hairs and compared these responses to stripped roots. These experiments identified a variety of proteins whose expression changed within 3 h of application of heat stress. Most of these proteins were predicted to play a significant role in thermo-tolerance, as well as in chromatin remodeling and post-transcriptional regulation. In conclusion, the data presented represent an in-depth analysis of the heat stress response of a single cell type in soybean.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Probabilistic Programming for Transportable Source Characterization and Uncertainty Quantification of the North Korean Nuclear Tests 2006–2017

Here, we introduce a transportable technique to determine the yield and depth of burial (DOB) from seismic source spectra of underground nuclear explosions. We demonstrate this technique on the six declared North Korean nuclear tests. This approach derives source spectra in absolute units from regional phase (Pg) amplitudes by correcting the observations for geometric spreading, attenuation, and site amplification. We couple the source spectra and explosion source models with a probabilistic programming framework that integrates deep learning techniques and Bayesian modeling. This approach permits the exchange of information across various data categories to quantify both the data and model uncertainty. This technique stands out as an innovative use of broad‐area propagation models, making it transportable across various geologic settings. This method proves to be effective in scenarios with diverse and/or limited observational data, even when the source depth is unknown. We present new independent estimates of absolute yield and DOB that are consistent with the prior assessments, underscoring the potential of this method in enhancing transportable nuclear explosion monitoring capabilities.

58 GEOSCIENCES↗
DOE OSTI2017

Constraints on the Optical Depth of Galaxy Groups and Clusters

Future data from galaxy redshift surveys, combined with high-resolutions maps of the cosmic microwave background, will enable measurements of the pairwise kinematic Sunyaev–Zel’dovich (kSZ) signal with unprecedented statistical significance. This signal probes the matter-velocity correlation function, scaled by the average optical depth (τ) of the galaxy groups and clusters in the sample, and is thus of fundamental importance for cosmology. However, in order to translate pairwise kSZ measurements into cosmological constraints, external constraints on τ are necessary. In this work, we present a new model for the intracluster medium, which takes into account star formation, feedback, non-thermal pressure, and gas cooling. Our semi-analytic model is computationally efficient and can reproduce results of recent hydrodynamical simulations of galaxy cluster formation. We calibrate the free parameters in the model using recent X-ray measurements of gas density profiles of clusters, and gas masses of groups and clusters. Our observationally calibrated model predicts the average τ{sub 500} (i.e., the integrated τ within a disk of size R {sub 500}) to better than 6% modeling uncertainty (at 95% confidence level). If the remaining uncertainties associated with other astrophysical uncertainties and X-ray selection effects can be better understood, our model for the optical depth should break the degeneracy between optical depth and cluster velocity in the analysis of future pairwise kSZ measurements and improve cosmological constraints with the combination of upcoming galaxy and CMB surveys, including the nature of dark energy, modified gravity, and neutrino mass.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Empirical performance bounds for quantum approximate optimization

The quantum approximate optimization algorithm (QAOA) has been put forth as a method for near-term quantum computers to solve optimization problems. However, assessments of QAOA performance have mostly focused on small structured problem instances while performance on more general instances is less clear. Here, we numerically simulate QAOA pure state dynamics for every instance of MaxCut on non-isomorphic unweighted graphs with nine or fewer vertices with depth parameters p ≤ 3. We find the approximation ratios and optimized circuit parameters concentrate across graphs of a given size and empirically show increases in concentration as graph size increases. The parameter concentration leads to two median-angle heuristics that overcome difficulties in QAOA parameter optimization and obtain mean approximation ratios within 3% and 0.2% of the optimal. We also analyze the probability to measure an optimal solution and find increasing variations between graphs as depth increases, in stark contrast to the approximation ratios which concentrate as depth increases. Furthermore, the resulting benchmark data set gives empirical bounds for on-going experimental realizations and lays groundwork for theoretical extensions to greater problem sizes and depths where QAOA may prove important for practically relevant problems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Quantifying Dynamic Water Storage in Unsaturated Bedrock with Borehole Nuclear Magnetic Resonance

Quantifying the volume of water that is stored in the subsurface is critical to studies of water availability to ecosystems, slope stability, and water-rock interactions. In a variety of settings, water is stored in fractured and weathered bedrock as rock moisture. However, few techniques are available to measure rock moisture in unsaturated rock, making direct estimates of water storage dynamics difficult to obtain. Here, we use borehole nuclear magnetic resonance (NMR) at two sites in seasonally dry California to quantify dynamic rock moisture storage. Additionally, we show strong agreement between NMR estimates of dynamic storage and estimates derived from neutron logging and mass balance techniques. The depths of dynamic storage are up to 9 m and likely reflect the depth extent of root water uptake. To our knowledge, these data are the first to quantify the volume and depths of dynamic water storage in the bedrock vadose zone via NMR.

58 GEOSCIENCES↗