Search NASA⌕ Search

SEARCH · Search NASA

Results for “Model Counting”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14

A Swift Look at SN 2011fe: The Earliest Ultraviolet Observations of a Type Ia Supernova

We present the earliest ultraviolet (UV) observations of the bright Type Ia supernova SN 2011fe/PTF11kly in the nearby galaxy M101 at a distance of only 6.4 Mpc. It was discovered shortly after explosion by the Palomar Transient Factory and first observed by Swift/UVOT about a day after explosion. The early UV light is well-defined, with approx. 20 data points per filter in the 5 days after explosion. With these early UV observations, we extend the near-UV template of SNe Ia to earlier times for comparison with observations at low and high redshift and report fits from semiempirical models of the explosion. We find the early UV count rates to be well fit by the superposition of two parabolic curves. Finally, we use the early UV flux measurements to examine a possible shock interaction with a non-degenerate companion. We find that even a solar mass companion at a distance of a few solar radii is unlikely at more than 95% confidence.

Oates, Samantha↗

Observed Correlation Between Local Topography and Passive Neutron Measurements from the Dynamic Albedo of Neutrons (DAN) Instrument on the Mars Science Laboratory (MSL) Rover

The Dynamic Albedo of Neutrons (DAN) instrument on the Mars Science Laboratory Curiosity rover primarily measures neutrons that have undergone interactions with rocks and materials in the rover's local environment. As the rover ascends Aeolis Mons, it may encounter more extreme local topography (e.g., cliffs, gullies, canyons). We present three parts of the rover's traverse in which local topography, expressed as the average local relief relative to the rover, is moderately to strongly correlated with an increase in passive thermal neutron count rates. These increases in count rates are consistent with results from radiation transport models of the instrument's performance near simulated topographic features. Additional DAN measurements in areas of high average local relief (>0.25 m) within 5 m of the instrument could bolster this correlation. DAN's sensitivity to topography in its passive mode could be utilized as a new measurement capability and has implications for the operation of future landed missions carrying neutron spectrometers (e.g., VIPER, MoonRanger, Lunar-VISE).

Steven D Dibb↗

Photon-Counting Interferometry to Detect Geontropic Space-Time Fluctuations with GQuEST

The gravity from the quantum entanglement of space-time (GQuEST) experiment uses tabletop-scale Michelson laser interferometers to probe for fluctuations in space-time. We present a practicable interferometer design featuring a novel photon-counting readout method that provides unprecedented sensitivity, as it is not subject to the interferometric standard quantum limit. We evaluate the potential of this design to measure space-time fluctuations motivated by recent “geontropic” quantum gravity models. The accelerated accrual of Fisher information offered by the photon-counting readout enables GQuEST to detect the predicted quantum gravity phenomena within measurement times at least 100 times shorter than equivalent conventional interferometers. The GQuEST design, thus, enables a fast and sensitive search for signatures of quantum gravity in a laboratory-scale experiment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Large-angle cosmic microwave background anisotropies in an open universe

If the universe is open, scales larger than the curvature scale may be probed by observation of large-angle fluctuations in the cosmic microwave background (CMB). We consider primordial adiabatic perturbations and discuss power spectra that are power laws in volume, wavelength, and eigenvalue of the Laplace operator. Such spectra may have arisen if, for example, the universe underwent a period of `frustated' inflation. The resulting large-angle anisotropies of the CMB are computed. The amplitude generally increases as Omega is decreased but decreases as h is increased. Interestingly enough, for all three Ansaetze, anisotropies on angular scales larger than the curvature scale are suppressed relative to the anisotropies on scales smaller than the curvature scale, but cosmic variance makes discrimination between various models difficult. Models with 0.2 approximately less than Omega h approximately less than 0.3 appear compatible with CMB fluctuations detected by Cosmic Background Explorer Satellite (COBE) and the Tenerife experiment and with the amplitude and spectrum of fluctuations of galaxy counts in the APM, CfA, and 1.2 Jy IRAS surveys. COBE normalization for these models yields sigma(sub 8) approximately = 0.5 - 0.7. Models with smaller values of Omega h when normalized to COBE require bias factors in excess of 2 to be compatible with the observed galaxy counts on the 8/h Mpc scale. Requiring that the age of the universe exceed 10 Gyr implies that Omega approximately greater than 0.25, while requiring that from the last-scattering term in the Sachs-Wolfe formula, large-angle anisotropies come primarily from the decay of potential fluctuations at z approximately less than 1/Omega. Thus, if the universe is open, COBE has been detecting temperature fluctuations produced at moderate redshift rather than at z approximately 1300.

Kamionkowski, Marc↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗

Role of Temperature, Humidity and Rainfall on Influenza Transmission in Guatemala, El Salvador and Panama

Worldwide, seasonal influenza causes about 500,000 deaths and 5 million severe illnesses per year. The environmental drivers of influenza transmission are poorly understood especially in the tropics. We aimed to identify meteorological factors for influenza transmission in tropical Central America. We gathered laboratory-confirmed influenza case-counts by week from Guatemala City, San Salvador Department (El Salvador) and Panama Province from 2006 to 2010. The average total cases per year were: 390 (Guatemala), 99 (San Salvador) and 129 (Panama). Meteorological factors including daily air temperature, rainfall, relative and absolute humidity (RH, AH) were obtained from ground stations, NASA satellites and land models. For these factors, we computed weekly averages and their deviation from the 5-yr means. We assessed the relationship between the number of influenza case-counts and the meteorological factors, including effects lagged by 1 to 4 weeks, using Poisson regression for each site. Our results showed influenza in San Salvador would increase by 1 case within a week of every 1 day with RH>75% (Relative Risk (RR)= 1.32, p=.001) and every 1C increase in minimum temperature (RR=1.29, p=.007) but it would decrease by 1 case for every 1mm-above mean weekly rainfall (RR=0.93,p<.001) (model pseudo-R2=0.55). Within 2 weeks, influenza in Panama was increased by 1 case for every 1% increase in RH (RR=1.04, p=.003), and it was increased by 2 cases for every 1C increase of minimum temperature (RR=2.01, p<.001) (model pseudo-R2=0.4). Influenza counts in Guatemala had 1 case increase for every 1C increase in minimum temperature in the previous week (RR=1.21, p<.001), and for every 1mm/day-above normal increase of rainfall rate (RR=1.03, p=.03) (model pseudo-R2=0.54). Our findings that cases increase with temperature and humidity differ from some temperate-zone studies. But they indicate that climate parameters such as humidity and temperature could be predictive of influenza activity and should be incorporated into country-specific influenza transmission models

Soebiyanto, Radina P.↗

Imaging the sun in hard x rays using Fourier telescopes

For several years, solar flares have been observed with a variety of instruments confirming that tremendous amounts of energy are locally stored in the solar magnetic field and then rapidly released during the life of the flare. In concert with observations, theorists have attempted to describe the means by which these energetic events occur and evolve. Two competing theories have emerged and have stood the test of time. One theory describes the flare in terms of nonthermal, electron beam injection into a thick target while the other uses a thermal approach. Both theories provide results which are reasonably consistent with current observations; but to date, none have been able to provide conclusive evidence as to the validity of either model. Imaging on short time scales (1 s) and/or small size scales (1 arc s) should give definitive answers to these questions. In order to test whether a realistic telescope can indeed discriminate between models, we construct model sources based upon the thermal and the nonthermal models and calculate the emission as a function of time and energy in the range from 10 to 100 keV. In addition, we construct model telescopes representing both the spatial modulation collimator (SMC) and the rotating modulation collimator (RMC) techniques of observation using random photon counting statistics. With these two types of telescopes we numerically simulate the instrument response to the above two model flares to see if there are distinct x-ray signatures which may be discernable. We find that theoretical descriptions of the primary models of solar flares do indeed predict different hard x-ray signatures for 1 sec time scales and at 1-5 arc sec spatial resolution. However, these distinguishing signatures can best be observed early in the impulsive phase and from a position perpendicular to the plane of the loop. Furthermore, we find that Fourier telescopes with reasonable and currently attainable design characteristics can image these signatures and that the same sensitive areas and short temporal integration times relative to source evolution (i.e., 1 s), the RMC and the SMC will both provide about the same performance.

Campbell, J. W.↗

A very deep IRAS survey at l(II) = 97 deg, b(II) = +30 deg

A deep far-infrared survey is presented using over 1000 scans made of a 4 to 6 sq. deg. field at the north ecliptic pole by the IRAS. Point sources from this survey are up to 100 times fainter than the IRAS point source catalog at 12 and 25 micrometers, and up to 10 times fainter at 60 and 100 micrometers. The 12 and 25 micrometer maps are instrumental noise-limited, and the 60 and 100 micrometer maps are confusion noise-limited. The majority of the 12 micrometer point sources are stars within the Milky Way. The 25 micrometer sources are composed almost equally of stars and galaxies. About 80% of the 60 micrometer sources correspond to galaxies on Palomar Observatory Sky Survey (POSS) enlargements. The remaining 20% are probably galaxies below the POSS detection limit. The differential source counts are presented and compared with what is predicted by the Bahcall and Soneira Standard Galaxy Model using the B-V-12 micrometer colors of stars without circumstellar dust shells given by Waters, Cote and Aumann. The 60 micrometer source counts are inconsistent with those predicted for a uniformly distributed, nonevolving universe. The implications are briefly discussed.

Hacking, Perry↗

Source counts in the chronometric cosmology

The chronometric cosmology (a static, homogeneous, and hence nonevolving model proposed by Segal) is unable to explain the steep number versus flux law N(S) for quasars or extragalactic radio sources. The explanation given by Segal to explain the steep N(S) laws gives at best a small increase over a Euclidean N(S) proportional to S exp-1.5, and requires that the source spectral index be close to but greater than zero to create the effect. For typical radio spectral indices of roughly 0.75, the chronometric model cannot give a quantitative fit to the excess number of 1-3 Jy sources that the standard cosmology attributes to evolution. Thus the chronometric model can explain a steep N(S) law only for flat spectrum sources, while the observations show the steepest N(S) law for steep spectrum sources. Furthermore, the observed N(S) law for ultraviolet excess quasars is steeper than the steepest possible chronometric prediction.

Wright, Edward L.↗

Cluster evolution as a probe of primordial density fluctuations

Although COBE's detection of large angle microwave background anisotropies fixes the amplitude of density fluctuations on length scales k exp -1 approximately = (300-6000) h(exp -1)Mpc, what is crucial for the level of large scale clustering is the amplitude of density fluctuations on scales (5-50) h(exp -1)Mpc. The level of dynamical clustering is usually parameterized by the size of the mass fluctuations in 8 h exp -1 Mpc spheres, sigma sub 8. For the cold dark matter model, COBE gives sigma sub 8 approximately = 1, while models with extra large scale power give sigma sub 8 approximately = 1/2. The most massive clusters of galaxies (greater than or approximately = 10 exp 15 solar mass) form from rare 'peak patches' found in the initial mass density distribution. Their abundance as a function of redshift is a sensitive probe of the wave number band k(exp -1) approx. (3-8) h(exp -1)Mpc, hence of sigma sub 8, and so cluster evolution can discriminate among models allowed by the COBE results. We use our Hierarchical Peaks Method, which accurately reproduces the results of P3M N-body simulations, to calculate the evolution of cluster x-ray flux counts, luminosity, and temperature functions as a function of sigma sub 8 for CDM models and those with more large scale power. We find that the EMSS and Edge et al. cluster samples support sigma sub 8 in the range from approx. 0.6-0.9, and that models with more large scale power (and hence flatter fluctuation spectra in the cluster regime) fit the x-ray bright end better.

Bond, J. Richard↗

The Plasma Environment at Mercury

Mercury is the least explored terrestrial planet, and the one subjected to the highest flux of solar radiation in the heliosphere. Its highly dynamic, miniature magnetosphere contains ions from the exosphere and solar wind, and at times may allow solar wind ions to directly impact the planet's surface. Together these features create a plasma environment that shares many features with, but is nonetheless very different from, that of Earth. The first in situ measurements of plasma ions in the Mercury space environment were made only recently, by the Fast Imaging Plasma Spectrometer (FIPS) during the MESSENGER spacecraft's three flybys of the planet in 2008-2009 as the probe was en route to insertion into orbit about Mercury earlier this year. Here. we present analysis of flyby and early orbital mission data with novel techniques that address the particular challenges inherent in these measurements. First. spacecraft structures and sensor orientation limit the FIPS field of view and allow only partial sampling of velocity distribution functions. We use a software model of FIPS sampling in velocity space to explore these effects and recover bulk parameters under certain assumptions. Second, the low densities found in the Mercury magnetosphere result in a relatively low signal-to-noise ratio for many ions. To address this issue, we apply a kernel density spread function to guide removal of background counts according to a background-signature probability map. We then assign individual counts to particular ion species with a time-of-flight forward model, taking into account energy losses in the carbon foil and other physical behavior of ions within the instrument. Using these methods, we have derived bulk plasma properties and heavy ion composition and evaluated them in the context of the Mercury magnetosphere.

Raines, James M.↗