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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

SU-D-BRE-07: Neutron Shielding Assessment for a Compact Proton Therapy Vault

Purpose: To perform a neutron shielding assessment of a commercially available compact proton therapy system. Methods: TOPAS (TOol for PArticle Simulation) beta release was used to model beam line components for Mevion S250 proton treatment system the design of which is that the cyclotron is present in the treatment room. Three neutron production sources were taken into account in the simulation. These are the cyclotron, the treatment nozzle and the patient itself, respectively. The cyclotron was modeled as a cylindrical iron target (r =5 cm, length = 8 cm). A water phantom (10 cm ×10 cm ×60 cm) was used to model the patient and various structures (scattering foils, range modulator wheel, applicator and compensator) defaulted in TOPAS were used to model the passive scattering treatment nozzle. Neutron fluences and energy spectra were counted in a spherical scoring geometry per incident proton in 18 angular bins (10 degree each). Fluence to dose conversion factors from ICRU publication 74 were used to acquire neutron ambient dose equivalent H*(10). A point source line of sight model was then used to calculate neutron dose at eight locations beyond shielding barriers. Results: The neutron ambient dose equivalent was calculated at the 8 points of interest around the proton treatment vault. The highest dose was found to be less than 0.781 mSv/year outside south barrier wall. However, the dose is less than 0.05 mSv/year at the control room area of the proton vault. Conclusion: All Points of interest were well under annual dose limits. This suggests that the shielding design of this compact proton therapy system is sufficient for radiation protection purpose. However, it is important to note that the workload and the occupancy factors are direct multipliers for dose calculations beyond the barrier and must be accurately estimated for validation of our results.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2014

CLASH: A census of magnified star-forming galaxies at z ∼ 6-8

We utilize 16 band Hubble Space Telescope (HST) observations of 18 lensing clusters obtained as part of the Cluster Lensing And Supernova survey with Hubble (CLASH) Multi-Cycle Treasury program to search for z ∼ 6-8 galaxies. We report the discovery of 204, 45, and 13 Lyman-break galaxy candidates at z ∼ 6, z ∼ 7, and z ∼ 8, respectively, identified from purely photometric redshift selections. This large sample, representing nearly an order of magnitude increase in the number of magnified star-forming galaxies at z ∼ 6-8 presented to date, is unique in that we have observations in four WFC3/UVIS UV, seven ACS/WFC optical, and all five WFC3/IR broadband filters, which enable very accurate photometric redshift selections. We construct detailed lensing models for 17 of the 18 clusters to estimate object magnifications and to identify two new multiply lensed z ≳ 6 candidates. The median magnifications over the 17 clusters are 4, 4, and 5 for the z ∼ 6, z ∼ 7, and z ∼ 8 samples, respectively, over an average area of 4.5 arcmin{sup 2} per cluster. We compare our observed number counts with expectations based on convolving 'blank' field UV luminosity functions through our cluster lens models and find rough agreement down to ∼27 mag, where we begin to suffer significant incompleteness. In all three redshift bins, we find a higher number density at brighter observed magnitudes than the field predictions, empirically demonstrating for the first time the enhanced efficiency of lensing clusters over field surveys. Our number counts also are in general agreement with the lensed expectations from the cluster models, especially at z ∼ 6, where we have the best statistics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Modelling human myoblasts survival upon xenotransplantation into immunodeficient mouse muscle

Cell transplantation has been challenged in several clinical indications of genetic or acquired muscular diseases, but therapeutic success were mitigated. To understand and improve the yields of tissue regeneration, we aimed at modelling the fate of CD56-positive human myoblasts after transplantation. Using immunodeficient severe combined immunodeficiency (SCID) mice as recipients, we assessed the survival, integration and satellite cell niche occupancy of human myoblasts by a triple immunohistochemical labelling of laminin, dystrophin and human lamin A/C. The counts were integrated into a classical mathematical decline equation. After injection, human cells were essentially located in the endomysium, then they disappeared progressively from D0 to D28. The final number of integrated human nuclei was grossly determined at D2 after injection, suggesting that no more efficient fusion between donor myoblasts and host fibers occurs after the resolution of the local damages created by needle insertion. Almost 1% of implanted human cells occupied a satellite-like cell niche. Our mathematical model validated by histological counting provided a reliable quantitative estimate of human myoblast survival and/or incorporation into SCID muscle fibers. Informations brought by histological labelling and this mathematical model are complementary.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Arm and shoulder muscle segmentation in axial MRI with UNet deep learning model

Quantifying individual upper-limb muscle volumes from MRI provides key insight into muscle-specific strength, deficits, and adaptations. Manual delineation is the gold standard but time‑intensive, and the performance of current deep learning approaches, particularly for small or anatomically complex muscles, remains incompletely characterized. We evaluated a state‑of‑the‑art deep learning framework across the entire upper limb and analyzed factors governing segmentation performance, with attention to the forearm. Three previously published MRI datasets (1.5 T, 3D GRE T1‑weighted; total n = 39) spanning young, middle‑aged, and older adults were curated and quality‑checked, including expert manual segmentations for 31 muscles. Following multiclass mask reconstruction, we trained three 3D nnU‑Net multiclass models matched to the muscle subsets present across datasets, using five‑fold cross‑validation and a composite Dice Similarity Coefficient (DSC) + cross entropy loss. Segmentation accuracy was assessed with DSC. Performance varied across muscles (mean DSC = 0.806 ± 0.098), ranging from 0.920 (Deltoid) to 0.461 (Extensor pollicis brevis). In uncertainty‑weighted regressions, muscle volume was positively associated with DSC (R2 = 0.36, p < 0.001), whereas training segmentation count and muscle orientation showed negligible associations (R2 ≤ 0.06). A weighted mixed‑effects model identified volume as the strongest evaluated predictor, explaining 23.9% of variance in DSC; orientation and training count each contributed <1%, leaving 61.5% unexplained. These results indicate that deep learning–based segmentation can accurately quantify muscle volume for many upper‑limb muscles but remains constrained for small, low‑contrast forearm muscles.

Gillespie, Samuel↗
DOE OSTI2013

FAINT SUBMILLIMETER GALAXY COUNTS AT 450 {mu}m

We present the results of SCUBA-2 observations at 450 {mu}m and 850 {mu}m of the field lensed by the massive cluster A370. With a total survey area >100 arcmin{sup 2} and 1{sigma} sensitivities of 3.92 and 0.82 mJy beam{sup -1} at 450 and 850 {mu}m, respectively, we find a secure sample of 20 sources at 450 {mu}m and 26 sources at 850 {mu}m with a signal-to-noise ratio (S/N) > 4. Using the latest lensing model of A370 and Monte Carlo simulations, we derive the number counts at both wavelengths. The 450 {mu}m number counts probe a factor of four deeper than the counts recently obtained from the Herschel Space Telescope at similar wavelengths, and we estimate that {approx}47%-61% of the 450 {mu}m extragalactic background light resolved into individual sources with 450 {mu}m fluxes greater than 4.5 mJy. The faint 450 {mu}m sources in the 4{sigma} sample have positional accuracies of 3 arcsec, while brighter sources (S/N >6{sigma}) are good to 1.4 arcsec. Using a deep radio map (1{sigma} {approx} 6 {mu}Jy) we find that the percentage of submillimeter sources having secure radio counterparts is 85% for 450 {mu}m sources with intrinsic fluxes >6 mJy and 67% for 850 {mu}m sources with intrinsic fluxes >4 mJy. We also find that 67% of the >4{sigma} 450 {mu}m sources are detected at 850 {mu}m, while the recovery rate at 450 {mu}m of >4{sigma} 850 {mu}m sources is 54%. Combined with the source redshifts estimated using millimetric flux ratios, the recovered rate is consistent with the scenario where both 450 {mu}m and 20 cm emission preferentially select lower redshift dusty sources, while 850 {mu}m emission traces a higher fraction of dusty sources at higher redshifts. We identify potential counterparts in various wavelengths from X-ray to mid-infrared and measure the multiwavelength photometry, which we then use to analyze the characteristics of the sources. We find three X-ray counterparts to our robust submillimeter sample (S/N > 5), giving an active galactic nucleus fraction for our 450 (850) {mu}m sample of 3/8 (3/9) or 38% (33%). We also find a correlation between the K{sub s} band and the 850 {mu}m/20 cm flux ratio.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Irradiation of an enriched uranium (NaCl-UCl 3 ) fuel salt capsule, summary of nondestructive post-irradiation examinations, and solidification modeling

Molten salt reactors (MSRs) are gaining attention due to their potential for safe, carbon-free nuclear energy with reduced waste. However, licensing these reactors is hindered by limited experimental data on fueled salts, both pre- and post-irradiation. Here, the novel Molten-salt Research Temperature-controlled Irradiation (MRTI) vehicle was designed to address knowledge gaps in irradiating enriched‑uranium-bearing salts. The MRTI experiment irradiated 13 cm 3 of UCl₃-NaCl (93 % U-235) salt in the Neutron Radiography (NRAD) Reactor, achieving a burnup of 0.196 GWd/MTU over 390 h. Despite a heater failure, the thermocouple data suggested fission heat kept the salt molten. The MRTI assembly was remotely disassembled for nondestructive post-irradiation examination (PIE), which included precision gamma-ray scanning (PGS) and neutron radiography. Radiograph images showed the location of the salt and the solidification pattern. PGS results provided an early indication that activated materials of construction did not increase in relative intensity in the region of the capsule where the salt was in contact with the material of construction. Additionally, PGS data showed the presence of several gamma emitting fission products, such as Nb-95, Zr-95, Ru-103, Ce-141, and La-140, where Ru-103 had the highest counts at the bottom of the capsule. Computational fluid dynamics modeling supported observations of salt solidification patterns and proved to be a valuable tool to inform PIE activities. The MRTI experiment has thus far provided critical data and lessons learned for fuel salt PIE activities, essential for advancing the technical readiness of MSRs.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Development of a New Chelation Model: Bioassay Data Interpretation and Dose Assessment after Plutonium Intake via Wound and Treatment with DTPA

The administration of chelation therapy to treat significant intakes of actinides, such as plutonium, affects the actinide’s normal biokinetics. In particular, it enhances the actinide’s rate of excretion, such that the standard biokinetic models cannot be applied directly to the chelation-affected bioassay data in order to estimate the intake and assess the radiation dose. Here we propose a new chelation model that can be applied to the chelation-affected bioassay data after plutonium intake via wound and treatment with DTPA. In the proposed model, chelation is assumed to occur in the blood, liver, and parts of the skeleton. Ten datasets, consisting of measurements of 14 C-DTPA, 238 Pu, and 239 Pu involving humans given radiolabeled DTPA and humans occupationally exposed to plutonium via wound and treated with chelation therapy, were used for model development. The combined dataset consisted of daily and cumulative excretion (urine and feces), wound counts, measurements of excised tissue, blood, and post-mortem tissue analyses of liver and skeleton. The combined data were simultaneously fit using the chelation model linked with a plutonium systemic model, which was linked to an ad hoc wound model. The proposed chelation model was used for dose assessment of the wound cases used in this study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Current Trends in the Detection of Sociocultural Signatures: Data-Driven Models

The harvesting of behavioral data and their analysis through evidence-based reasoning enable the detection of sociocultural signatures in their context to support situation awareness and decision making. Harvested data are used as training materials from which to infer computational models of sociocultural behaviors or calibrate parameters for such models. Harvested data also serve as evidence input that the models use to provide insights about observed and future behaviors for targets of interest. The harvested data is often the result of assembling diverse data types and aggregating them into a form suitable for analysis. Data need to be analyzed to bring out the categories of content that are relevant to the domain being addressed in order to train or run a model. If, for example, we are modeling the intent of a group to engage in violent behavior using messages that the group has broadcasted, then these messages need to be processed to extract and measure indicators of violent intent. The extracted indicators and the associated measurements (e.g. rates or counts of occurrence) can then be used to train/calibrate and run computational models that assess the propensity for violence expressed in the source message. Ubiquitous access to the Internet, mobile telephony and technologies such as digital photography and digital video have enabled social media application platforms such as Facebook, YouTube, and Twitter that are altering the nature of human social interaction. The fast increasing pace of online social interaction introduces new challenges and opportunities for gathering sociocultural data. Challenges include the development of harvesting and processing techniques tailored to new data environments and formats (e.g. Twitter, Facebook), the integration of social media content with traditional media content, and the protection of personal privacy. As these and other challenges are addressed, a new wealth of behavioral data and data analysis methods becomes available that are shaping social computing as a strongly data-driven experimental discipline with an increasingly stronger impact on the decision-making process of groups and individuals alike. In this chapter, we review current advances and trends in the detection of sociocultural signatures. Specific embodiments of the issues discussed are provided with respect to the assessment of violent intent and sociopolitical contention. We begin by reviewing current approaches to the detection of sociocultural signatures in these domains. Next, we turn to the review of novel data harvesting methods for social media content. Finally, we discuss the application of sociocultural models to social media content, and conclude by commenting on current challenges and future developments.

Sanfilippo, Antonio P.↗
DOE OSTI2026

Carbon fiber design improvements based on economic models

Circular fiber geometries are predominant in commercial carbon fiber material systems, but the use of this fiber shape has numerous limitations. Circular geometries have continuous symmetry, which is helpful for various processing considerations, but also have the largest possible maximum diffusion thickness for a given fiber area. This characteristic means that circular carbon fibers always have the highest material processing cost and lowest production throughput compared to any other fiber shape with the same area and tow count. To quantify material cost and other benefits for non-circular carbon fiber geometries, process models for polyacrylonitrile based carbon fiber production are developed in relationship to the carbon fiber shape, size, and tow count. For a given fiber shape, precursor production costs are shown to favor maximizing fiber size while conversion costs are minimized by the smallest fiber size. These competing cost trends result in a numerically optimal fiber size for a given shape and tow count, while both cost components are decreased by increasing tow count. Cost–performance tradeoffs for three lobe fiber geometries are studied by supplementing the cost trends with a numerical failure model to predict compressive strength for discrete shape variants. The shape selection is shown to be more sensitive to variations in cost than compressive strength while suboptimal shape designs can improve manufacturing robustness and achievable fiber volume fractions. Finally, an optimal three lobe carbon fiber is identified that balances the set of considerations while reducing costs and embodied energy and increasing production throughput compared to a commercial carbon fiber.

Carbon fiber↗
NASA NTRSDate not supplied

Graph Convolutional Network-Strengthened Topic Modeling for Scientific Papers

Machine learning has been woven into statistics to modernize topic modeling over textual documents written in natural language, and scientific paper search and recommendation can consequently offer higher accuracy instead of counting on traditional keyword-based search. However, topic distribution of a paper resulted from existing topic modeling techniques only relies on the statistics of words contained in the paper itself. We argue that community users’ views of a paper may also provide insights at the time of recommendation. For example, if a paper on fake image detection has been cited heavily by machine learning papers, such a feature should be absorbed in the embedding of this paper, so that it can be recommended for future query on machine learning. In this paper, we present a Graph Convolutional Network-strengthened Topic Modeling (GCN-TM) method, which employs GCN technique to refine topic modeling of scientific papers. A citation-oriented knowledge graph is constructed, and topic modeling is mapped to feature embedding of the comprising papers. On top of its own topics carried in its content, each paper learns topics from its neighbors and revise its embedding accordingly. Our empirical studies over real-life scientific literature has proved the necessity and effectiveness of our proposed approach.

Jia Zhang↗
DOE OSTI2019

Validation of Geant4’s G4NRF module against nuclear resonance fluorescence data from 238 U and 27 Al

G4NRF (Jordan and Warren, 2007; Vavrek et al., 2018a,b) is a simulation module for modeling nuclear resonance fluorescence (NRF) interactions in the Geant4 framework (Allison et al., 2016). In this work, we validate G4NRF against both absolute and relative measurements of three NRF interactions near 2.2 MeV in 238 U and 27 Al using the transmission NRF data from the experiments described in Jayson et al. (2018). Agreement between the absolute NRF count rates observed in the data and predicted by extensive Geant4+G4NRF modeling validate the combined Geant4+G4NRF to approximately 15–20% in the 238 U NRF transitions and 10% in 27 Al, for an average 14% discrepancy across the entire study. The difference between simulation and experiment in relative NRF rates, as expressed as ratios of count rates in various NRF lines, is found at the level of ≲3%, and is statistically identical to zero. Finally, inverting the analysis, approximate values of the absolute level widths and branching ratios for 238 U and 27 Al are also obtained.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

A novel method for modeling the neutron time of flight (nTOF) detector response in current mode to inertial confinement fusion experiments.

There are several machines in this country that produce short bursts of neutrons for various applications. A few examples are the Z machine, operated by Sandia National Laboratories in Albuquerque, NM ; the OMEGA Laser Facility at the University of Rochester in Rochester, NY ; and the National Ignition Facility (NIF) operated by the Department of Energy at Lawrence Livermore National Laboratory in Livermore, California . They all incorporate neutron time of flight (nTOF) detectors which measure neutron yield, and the shapes of the waveforms from these detectors contain germane information about the plasma conditions that produce the neutrons. However, the signals can also be %E2%80%9Cclouded%E2%80%9D by a certain fraction of neutrons that scatter off structural components and also arrive at the detectors, thereby making analysis of the plasma conditions more difficult. These detectors operate in current mode - i.e., they have no discrimination, and all the photomultiplier anode charges are integrated rather than counted individually as they are in single event counting. Up to now, there has not been a method for modeling an nTOF detector operating in current mode. MCNP PoliMi was developed in 2002 to simulate neutron and gamma ray detection in a plastic scintillator, which produces a collision data output table about each neutron and photon interaction occurring within the scintillator; however, the post processing code which accompanies MCNP PoliMi assumes a detector operating in single event counting mode and not current mode. Therefore, the idea for this work had been born: could a new post processing code be written to simulate an nTOF detector operating in current mode? And if so, could this process be used to address such issues as the impact of neutron scattering on the primary signal? Also, could it possibly even identify sources of scattering (i.e., structural materials) that could be removed or modified to produce %E2%80%9Ccleaner%E2%80%9D neutron signals? This process was first developed and then applied to the axial neutron time of flight detectors at the Z Facility mentioned above. First, MCNP PoliMi was used to model relevant portions of the facility between the source and the detector locations. To obtain useful statistics, variance reduction was utilized. Then, the resulting collision output table produced by MCNP PoliMi was further analyzed by a MATLAB postprocessing code. This converted the energy deposited by neutron and photon interactions in the plastic scintillator (i.e., nTOF detector) into light output, in units of MeVee%D1%84 (electron equivalent) vs time. The time response of the detector was then folded into the signal via another MATLAB code. The simulated response was then compared with experimental data and shown to be in good agreement. To address the issue of neutron scattering, an %E2%80%9CIdeal Case,%E2%80%9D (i.e., a plastic scintillator was placed at the same distance from the source for each detector location) with no structural components in the problem. This was done to produce as %E2%80%9Cpure%E2%80%9D a neutron signal as possible. The simulated waveform from this %E2%80%9CIdeal Case%E2%80%9D was then compared with the simulated data from the %E2%80%9CFull Scale%E2%80%9D geometry (i.e., the detector at the same location, but with all the structural materials now included). The %E2%80%9CIdeal Case%E2%80%9D was subtracted from the %E2%80%9CFull Scale%E2%80%9D geometry case, and this was determined to be the contribution due to scattering. The time response was deconvolved out of the empirical data, and the contribution due to scattering was then subtracted out of it. A transformation was then made from dN/dt to dN/dE to obtain neutron spectra at two different detector locations.

Nelson, Alan J.↗
DOE OSTI2026

Historic climate, cosmogenic 10Be, denudation-rate, and geospatial datasets from the Pikes Peak region, Colorado, USA

This data package contains geographic information system (GIS) layers and tabular datasets associated with the study of elevation-dependent denudation rates on Pikes Peak in the Front Range of the Rocky Mountains, Colorado, USA. The package includes GIS layers used to produce the study-area map, including sample locations, sample watershed boundaries, the Pikes Peak batholith, Pleistocene glacier extent, weather station locations, and elevation and hillshade rasters, together with comma-separated value (CSV) tables and matching CSV data dictionaries. These mapped layers provide the geographic framework for interpreting denudation patterns across the Pikes Peak region and for relating sample locations to watershed geometry, bedrock setting, glacial history, and nearby climate stations. The first group of tables reports climate and geospatial context for the study area. These files include station-based temperature and precipitation data used to characterize elevational gradients in mean annual climate and monthly climate seasonality, sample locations, denudation-rate and topographic metrics, fixed frost-cracking model parameters, frost-cracking intensity and precipitation-frequency metrics, and stream-power inversion results. Together, these data provide the basis for evaluating how denudation varies with elevation, climate, and landscape form across sampled catchments on Pikes Peak. The second group of tables reports cosmogenic nuclide and erosion-model results used in the denudation analysis. Included files contain accelerator mass spectrometry (AMS) measurements for in situ-produced cosmogenic beryllium-10 (10Be), including sample identifiers, measured 10Be:9Be ratios, analytical uncertainties, carrier mass, quartz mass, blank corrections, blank-group statistics, and calculated 10Be concentrations and uncertainties. Additional tables summarize stream-power-law inversion results for sampled catchments, including optimized model parameters, predicted erosion rates, residual metrics, channel-pixel counts, and convergence status, as well as regression equations and summary statistics used to evaluate relationships among elevation, climate, frost cracking, precipitation forcing, and denudation rate. The package contains GIS files, comma-separated value files (.csv), Microsoft Excel files (.xlsx), CSV data dictionaries, a file-level metadata table, and a readme text file.

10Be cosmogenic nuclides↗
DOE OSTI2023

Understanding and Improving Energy Efficiency of Regional Mobility Systems Leveraging System-Level Data

Increased congestion required urban Americans to travel 6.8 billion hours more and purchase 3.1 billion gallons of fuel for a congestion cost of $\$$153 billion, according to the 2019 Urban Mobility Report. How to effectively manage the regional mobility system and improve the energy efficiency presents a big challenge to public agencies. Recent years have witnessed massive multi-jurisdictional multi-modal system-level data from various sources, which provides an unprecedented opportunity to improve the mobility system and its energy efficiency. However, implications of system-level data for mobility and energy efficiency are unclear. Those system-level data sets are siloed, spatially and temporally sparse, biased, not unified, and lacking of insights for system management. Consequently, there is a real need to acquire, fuse, mine and learn from multi-source system-level data to prepare public agencies to deal more effectively with large-scale energy efficiency modeling, management and planning. This project proposes to intensively review inexpensive, replicable and openly-accessible data from multi-modal systems, develop a data-driven system-level modeling framework enabled and validated by data, identify the energy inefficiencies of mobility systems from infrastructure, vehicles, passenger systems, and quantify the benefits of system-level strategies to improve mobility/energy efficiency. In addition, this research develops models to effectively estimate energy consumption and emissions from various types of vehicles on the roadway networks, with high granularity and high fidelity. Traditional models often heavily rely on aggregated infrastructure or vehicle/passenger data, for example, the census survey, land-use, and traffic counts of one or several classes, which may lead to research gaps considering the emerging vehicle technologies. Those models do not contain individual vehicular information. We propose an integrated data-driven method that combines multiple network modeling components, featuring the utilization of state-wide vehicle registration data. The additional vehicle registration data improve the model performance, and produce high-resolution vehicle-specific estimates of emissions and network performance metrics. Two case studies on the Pittsburgh and Philadelphia regional network show that the proposed method can efficiently and effectively estimate the emissions of a large-scale network, and provide valuable information for evaluating common management strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Analytical Modeling of Cache Behavior for Affine Programs

Modern optimizing compiler design integrates program transformation strategies aimed at reducing data movement to/from main memory by exploiting the data cache hierarchy. But in reality, the effect of these transformations on the actual cache miss count is ignored in compilers due to the lack of precise compile-time models of misses for hierarchical caches. The current state of practice for cache miss analysis is based on accurate simulation. However, simulation requires time proportional to the dataset/problem size as well as the number of distinct cache configurations of interest to be evaluated. This paper takes a fundamentally different approach, made possible by focusing on polyhedral programs with static control flow: instead of relying on costly simulation, this paper develops the first closed-form solution for exact modeling of misses in a set-associative cache hierarchy. It enabling simulation-less selection of program transformations at compile-time to optimize cache misses. A push-button tool implementing the approach is developed and used for extensive validation of the complete framework.

affine programs, cache modeling, set associativity↗
NASA NTRS1991

Statistics of gravitational lenses - The uncertainties

The assumptions in the analysis of gravitational lensing statistics are examined. Special emphasis is given to the uncertainties in the theoretical predictions. It is shown that a simple redshift cutoff model, which may result from galaxy evolution, can significantly reduce the lensing probability and explain the large mean separation of images in observed gravitational lenses. This effect may affect the constraint on the contribution of the cosmological constant to producing a flat universe from the number counts of the observed lenses. For the Omega(0) = 1 (filled beam) model, the lensing probability of early-type galaxies with finite core radii is reduced roughly by a factor of 2 for high-redshift quasars as compared with the corresponding singular isothermal sphere model. The finite core radius effect is about 20 percent for a lambda-dominated flat universe. It is also shown that the most recent galaxy luminosity function gives lensing probabilities that are smaller than previously estimated roughly by a factor of 3.

Mao, Shude↗
DOE OSTI2026

Quantum utility in simulating the real-time dynamics of the Fermi–Hubbard model using superconducting quantum computers

The Fermi–Hubbard model is a fundamental model in condensed matter physics that describes strongly correlated electrons. On the other hand, quantum computers are emerging as powerful tools for exploring the complex dynamics of these quantum many-body systems. In this work, we demonstrate the quantum simulation of the one-dimensional Fermi–Hubbard model using IBM's superconducting quantum computers, employing over 100 qubits. We introduce a first-order Trotterization scheme and extend it to an optimized second-order Trotterization for the time evolution in the Fermi–Hubbard model, specifically tailored for the limited qubit connectivity of quantum architectures, such as IBM's platforms. Notably, both Trotterization approaches are scalable and maintain a constant circuit depth at each Trotter step, regardless of the qubit count, enabling us to precisely investigate the relaxation dynamics in the Fermi–Hubbard model by measuring the expectation value of the Néel observable (staggered magnetization) for time-evolved quantum states. Lastly, our successful measurement of expectation values in such large-scale quantum many-body systems, especially at longer time scales with larger entanglement, highlights the quantum utility of superconducting quantum platforms over conventional classical approximation methods.

97 MATHEMATICS AND COMPUTING↗