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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Emergence of topological and trivial interface states in VSe 2 films coupled to Bi 2 Se 3

Coupling ordinary metals with topological Bi 2 Se 3 can instigate the long-range migration of the spin-polarized Dirac states. Instead, for trivial metallic VSe 2 films on Bi 2 Se 3 , topological and trivial Rashba-type interface states emerge, each strongly localized at the VSe 2 /Bi 2 Se 3 interface. Their rapidly decaying spectral weights are uncovered by thickness-dependent band mappings of VSe 2 films and replicated by a phenomenological first-principles model of the spectral function. In this work, the results are pertinent to spintronic devices requiring spin transmission across metal/topological insulator interfaces.

36 MATERIALS SCIENCE↗
NASA NTRS1981

Spectral characteristics of medium-scale equatorial F region irregularities

The spectral characteristics of equatorial F region irregularities with scale sizes from a few kilometers to several hundred kilometers have been measured using data from the Atmospheric Explorer-E satellite. The spectra admit the expected power law characterization with a mean spectral index near 2. There is, however, a systematic decrease in the spectral index with increasing perturbation strength which has not previously been reported. Nearly simultaneous phase scintillation data from the Wideband satellite were also spectrally analyzed for comparison with the AE-E data. The same systematic decrease of the spectral index with increasing perturbation strength was found in the measured phase spectral indices. A completely unambiguous comparison between the in situ and scintillation deduced turbulence levels cannot be made. However, for realistic propagation model parameters, the spectral characterization of turbulence based on the phase scintillation data is generally consistent with that observed in situ.

Livingston, R. C.↗
NASA NTRS1994

Canopy reflectance modelling of semiarid vegetation

Three different types of remote sensing algorithms for estimating vegetation amount and other land surface biophysical parameters were tested for semiarid environments. These included statistical linear models, the Li-Strahler geometric-optical canopy model, and linear spectral mixture analysis. The two study areas were the National Science Foundation's Jornada Long Term Ecological Research site near Las Cruces, NM, in the northern Chihuahuan desert, and the HAPEX-Sahel site near Niamey, Niger, in West Africa, comprising semiarid rangeland and subtropical crop land. The statistical approach (simple and multiple regression) resulted in high correlations between SPOT satellite spectral reflectance and shrub and grass cover, although these correlations varied with the spatial scale of aggregation of the measurements. The Li-Strahler model produced estimated of shrub size and density for both study sites with large standard errors. In the Jornada, the estimates were accurate enough to be useful for characterizing structural differences among three shrub strata. In Niger, the range of shrub cover and size in short-fallow shrublands is so low that the necessity of spatially distributed estimation of shrub size and density is questionable. Spectral mixture analysis of multiscale, multitemporal, multispectral radiometer data and imagery for Niger showed a positive relationship between fractions of spectral endmembers and surface parameters of interest including soil cover, vegetation cover, and leaf area index.

Franklin, Janet↗
DOE OSTI2026

Benchmarking State-of-the-Art Theory and Empirical Models of Pionless Neutrino-Argon Scattering in GENIE

Neutrino event generators require a delicate balance between theory and empirically-driven models to achieve reliable simulations. GENIE is the most commonly used generator, bridging theory and experiment in modern neutrino physics. Its flexible framework makes it ideal for comparing different models across all aspects of neutrino interactions—from the nuclear ground state and primary vertex to final-state interactions. Recently, GENIE has incorporated several state-of-the-art, theory-driven models, including spectral-function descriptions of the nuclear ground state, axial form factors from first-principles lattice QCD calculations, and the Liège intranuclear cascade model for simulating final-state interactions. Compared to the previous baseline models in GENIE—such as the local Fermi gas, dipole-like axial form factor, and hA final-state interaction model—the new implementations are more physically realistic and incorporate more complete physics, including nuclear de-excitation. This poster presents the implementation of new models in GENIE and their performance in comparisons among these models against recent MicroBooNE cross-section measurements.

Liu, Liang [Fermilab] (ORCID:000000026753925X)↗
DOE OSTI2026

Benchmarking State-of-the-Art Theory and Empirical Models of Pionless Neutrino-Argon Scattering in GENIE

Neutrino event generators require a delicate balance between theory and empirically-driven models to achieve reliable simulations. GENIE is the most commonly used generator, bridging theory and experiment in modern neutrino physics. Its flexible framework makes it ideal for comparing different models across all aspects of neutrino interactions—from the nuclear ground state and primary vertex to final-state interactions. Recently, GENIE has incorporated several state-of-the-art, theory-driven models, including spectral-function descriptions of the nuclear ground state, axial form factors from first-principles lattice QCD calculations, and the Liège intranuclear cascade model for simulating final-state interactions. Compared to the previous baseline models in GENIE—such as the local Fermi gas, dipole-like axial form factor, and hA final-state interaction model—the new implementations are more physically realistic and incorporate more complete physics, including nuclear de-excitation. This poster presents the implementation of new models in GENIE and their performance in comparisons among these models against recent MicroBooNE cross-section measurements.

Liu, Liang [Fermilab] (ORCID:000000026753925X)↗
DOE OSTI2025

One-shot gas detection with transformer paired neural networks in Mako collected longwave infrared hyperspectral imagery

To date, careful data treatment workflows and statistical detectors are used to perform hyperspectral image (HSI) detection of any gas contained in a spectral library, which is often expanded with physics models to incorporate different spectral characteristics. In general, surrounding evidence or known gas-release parameters are used to provide confidence in or confirm detection capability, respectively. This makes quantifying detection performance difficult as it is nearly impossible to develop an absolute ground truth for gas target pixel presence in collected HSI. Consequently, developing and comparing new detection methods, especially machine learning (ML)-based methods, is susceptible to subjectivity in derived detection map quality. Here, in this work, we demonstrate the first use of transformer-based paired neural networks (PNNs) for one-shot gas target detection for multiple gases while providing quantitative classification and detection metrics for their use on labeled data. Terabytes of training data are generated from a database of long-wave infrared HSI obtained from historical Mako sensor campaigns over Los Angeles. By incorporating labels, singular signature representations, and a model development pipeline, we can tune and select PNNs to detect multiple gas targets that are not seen in training on a quantitative basis. We additionally assess our test set detections using interpretability techniques widely employed with ML-based predictors, but less common with detection methods relying on learned latent spaces.

Hyperspectral imaging↗
NASA NTRS2000

BOREAS TE-18 GeoSail Canopy Reflectance Model

The SAIL (Scattering from Arbitrarily Inclined Leaves) model was combined with the Jasinski geo metric model to simulate canopy spectral reflectance and absorption of photosynthetically active radiation for discontinuous canopies. This model is called the GeoSail model. Tree shapes are described by cylinders or cones distributed over a plane. Spectral reflectance and transmittance of trees are calculated from the SAIL model to determine the reflectance of the three components used in the geometric model: illuminated canopy, illuminated background, shadowed canopy, and shadowed background. The model code is Fortran. sample input and output data are provided in ASCII text files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC).

Hall, Forrest G.↗
NASA NTRS2021

Aerosol Absorption in Global Models From AeroCom Phase III

Aerosol-induced absorption of shortwave radiation can modify the climate through local atmospheric heating, which affects lapse rates, precipitation, and cloud formation. Presently, the total amount of aerosol absorption is poorly constrained, and the main absorbing aerosol species (black carbon (BC), organic aerosols (OA), and mineral dust) are diversely quantified in global climate models. As part of the third phase of the Aerosol Comparisons between Observations and Models (AeroCom) intercomparison initiative (AeroCom phase III), we here document the distribution and magnitude of aerosol absorption in current global aerosol models and quantify the sources of intermodel spread, highlighting the difficulties of attributing absorption to different species. In total, 15 models have provided total present-day absorption at 550 nm (using year 2010 emissions), 11 of which have provided absorption per absorbing species. The multi-model global annual mean total absorption aerosol optical depth (AAOD) is 0.0054 (0.0020 to 0.0098; 550 nm), with the range given as the minimum and maximum model values. This is 28 % higher compared to the 0.0042 (0.0021 to 0.0076) multi-model mean in AeroCom phase II (using year 2000 emissions), but the difference is within 1 standard deviation, which, in this study, is 0.0023 (0.0019 in Phase II). Of the summed component AAOD, 60 % (range 36 %–84 %) is estimated to be due to BC, 31 % (12 %–49 %) is due to dust, and 11 % (0 %–24 %) is due to OA; however, the components are not independent in terms of their absorbing efficiency. In models with internal mixtures of absorbing aerosols, a major challenge is the lack of a common and simple method to attribute absorption to the different absorbing species. Therefore, when possible, the models with internally mixed aerosols in the present study have performed simulations using the same method for estimating absorption due to BC, OA, and dust, namely by removing it and comparing runs with and without the absorbing species. We discuss the challenges of attributing absorption to different species; we compare burden, refractive indices, and density; and we contrast models with internal mixing to models with external mixing. The model mean BC mass absorption coefficient (MAC) value is 10.1 (3.1 to 17.7) m 2 g −1 (550 nm), and the model mean BC AAOD is 0.0030 (0.0007 to 0.0077). The difference in lifetime (and burden) in the models explains as much of the BC AAOD spread as the difference in BC MAC values. The difference in the spectral dependency between the models is striking. Several models have an absorption Ångstrøm exponent (AAE) close to 1, which likely is too low given current knowledge of spectral aerosol optical properties. Most models do not account for brown carbon and underestimate the spectral dependency for OA.

Aerosol absorption↗
NASA NTRS1986

Multiple-scale turbulence model in confined swirling jet predictions

A recently developed multiple-scale turbulence model which attempts to circumvent the deficiencies of earlier models by taking nonequilibrium spectral energy transfer into account is presented. The model's validity is tested by predicting the confined swirling coaxial jet flow in a sudden expansion. It is noted that, in order to account for anisotropic turbulence, a full Reynolds stress model is required.

Chen, C. P.↗
NASA NTRS1992

The gravitational wave contribution to cosmic microwave background anisotropies and the amplitude of mass fluctuations from COBE results

A stochastic background of primordial gravitational waves may substantially contribute, via the Sachs-Wolfe effect, to the large-scale cosmic microwave background (CMB) anisotropies recently detected by COBE. This implies a bias in any resulting determination of the primordial amplitude of density fluctuations. We consider the constraints imposed on n is less than 1 ('tilted') power-law fluctuation spectra, taking into account the contribution from both scalar and tensor waves, as predicted by power-law inflation. The gravitational wave contribution to CMB anisotropies generally reduces the required rms level of mass fluctuation, thereby increasing the linear bias parameter, even in models where the spectral index is close to the Harrison-Zel'dovich value n = 1. This 'gravitational wave bias' helps to reconcile the predictions of CDM models with observations on pairwise galaxy velocity dispersion on small scales.

Lucchin, Francesco↗
NASA NTRS1996

Improved passive microwave sounding of the atmosphere

The effort this year focused primarily on 118-GHz transmittance experiments. The data analyzed here was collected with the Microwave Temperature Sounder (MTS) radiometer package during the CAMEX deployment of 1993 with the aim of validating current models of atmospheric microwave absorption in the O2 bands near 54 and 118 GHz. Particular attention has been paid to data collected during four flights when the MTS scanned zenith while profiles of downwelling radiances were collected through ascents and descents. These radiances, in conjunction with radiosonde temperature data, permit the retrieval of band-averaged absorption profiles for each channel. The Millimeter-wave Propagation Model (MPM92) provides theoretical expressions for the absorption of microwaves by oxygen and water vapor and accounts for the interference of pressure-broadened spectral lines'. This model is a good fit to laboratory measurements at temperatures ranging from 279-327 K, but it has been suggested that extrapolation to the conditions of the atmospheric tropopause may result in underestimation of absorption by as much as 15 percent. Preliminary results of the analysis of MTS data appear to be in general agreement with the predictions of the MPM model to within the accuracy of the measurements, which through the coldest parts of the atmosphere ranges from less than plus or minus 5 percent in the most opaque channels to greater than plus or minus 10 percent in the most transparent channels. At those altitudes where each channel is most sensitive to changes in absorption, there is some indication that the modeled absorption may be biased low relative to the observations. Accurate instrument calibration provided challenges, particularly when observed radiances were as much as 260 K below the temperatures of the cold calibration load.

Staelin, D. H.↗
NASA NTRS2001

Spectroscopic Determination of the Physical Conditions in Hot, Optically Thin Sources

This annual report covers the period from Oct 1, 2000 to Sep 30, 2001. The Astrophysics Plasma Emission Code and Database (APEC/APED), developed in part under this grant, have been upgraded to Version 1.1 and are now beginning to be used outside our research group in applications to X-ray spectral data from Chandra and XMM-Newton. These models represent the best theoretical data currently available and are reasonably complete below about 30 angstroms. Stellar coronae are being used to benchmark the atomic data in APED as part of the Emission Line Project. Initial results suggest that the models for most of the strongest lines are in good agreement with the observations, including the H-like and He-like emission from dominant elements and the Fe L shell emission, both near 1 keV and in the extreme ultraviolet near 100 eV. At this point in time, we define 'good agreement' at the level of accuracy expected from the atomic physics, approximately 20-30%. In order to benchmark the spectral models beyond the canonical theoretical accuracy, we are working closely with the Chandra gratings calibration group to ensure that we are using the optimal calibration, primarily effective areas and line response functions.

Brickhouse, N.↗
NASA NTRSDate not supplied

Towards an Optimal Estimation Retrieval of Cirrus Cloud Optical and Microphysical Properties Using Hyperspectral Shortwave Instruments and A Fast Radiative Transfer Algorithm

Cirrus cloud retrieval products (here, cloud optical depth, effective particle size, and cloud top height) are important inputs into numerical weather and climate models. Uncertainties in such retrieval products, as a matter of course, propagate downstream, impacting model calculations. Improvements in high-quality global cirrus cloud optical and microphysical data products from satellite observations are needed to understand and reduce retrieval uncertainties. Hyperspectral shortwave instruments produce high-resolution and information-dense spectra, thus offering the opportunity to reduce uncertainties in retrieval products. We are in the process of developing a retrieval that uses the very fast Principal Component Radiative Transfer Model in the solar spectral region (PCRTM-Solar) in the forward model calculations. This retrieval will use measured reflectances from the NASA Earth Surface Mineral Dust Source Investigation (EMIT) and the forthcoming Climate Absolute Radiance and Refractivity Observatory Pathfinder (CLARREO-Pathfinder) instruments. In this manuscript we present progress towards a reference retrieval employing a widely used, verified, accurate, yet computationally slower radiative transfer modeling technique. The reference retrieval, while too slow for using the complete hyperspectral measurement, will allow us to study the behavior of retrieval products and help us verify results from our in-development fast retrieval. Both retrievals will use the optimal estimation retrieval framework. In this manuscript we present results from an uncertainty analysis considering three uncertainty sources for a cirrus cloud retrieval in the form of error covariance matrices: reflectance uncertainty due to water vapor, the reflectance uncertainty due to ice crystal scattering assumptions, and the instrument measurement uncertainty. Results show that the uncertainty due to habit selection is the largest, while that due to water vapor is at most 0.6% relative to channel reflectance. As a first step, the retrieval is being designed for single layer ice clouds over open ocean water.

Cirrus cloud↗
DOE OSTI2022

A framework for feasibility-level validation of high-resolution wave hindcast models

The value of long-term wave hindcasts for investigating wave climates, wave energy resources, and extreme wave conditions has motivated research developing, calibrating and validating wave hindcast models. Past hindcast model validation studies examined the accuracy in modeling bulk wave parameters of overall sea states without considering the dependency of the model's skill within different sea states. In the present study, a framework for wave hindcast model validation is developed by examining the model accuracy for the most frequently occurring sea states, sea states contributing the most energy to total wave power, sea states associated with hurricane events, and those with the largest model error. Here, validations using bulk wave parameters and frequency-directional spectra at these key sea states and extreme wave conditions based on univariate and bivariate-contour methods provide insights to improve model accuracy, identifying the model's strong and weak points, and pathways for improvement, e.g., modeling wave-current interactions and adjusting wind data. This study adds to a growing body of research demonstrating that a carefully calibrated and verified spectral wave hindcast model can be used to estimate key wave energy parameters over a wide range of wave energy climates, as well as their spatial, temporal, frequency, directional, and probabilistic distributions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

Non-Detection of L-Band Line Emission from the Exoplanet HD 189733b

We attempt to confirm bright non-local thermodynamic equilibrium (non-LTE) emission from the exoplanet HD 189733b at 3.25 microns, as recently reported by Swain et al. based on observations at low spectral resolving power (lambda/delta lambda approximately equals 30). Non-LTE emission lines from gas in an exoplanet atmosphere will not be significantly broadened by collisions, so the measured emission intensity per resolution element must be substantially brighter when observed at high spectral resolving power. We observed the planet before, during, and after a secondary eclipse event at a resolving power lambda/delta lambda equals 27,000 using the NIRSPEC spectrometer on the Keck II telescope. Our spectra cover a spectral window near the peak found by Swain et al., and we compare emission cases that could account for the magnitude and wavelength dependence of the Swain et al. result with our final spectral residuals. To model the expected line emission, we use a general non-equilibrium formulation to synthesize emission features from all plausible molecules that emit in this spectral region. In every case, we detect no line emission to a high degree of confidence. After considering possible explanations for the Swain et at., results and the disparity with our own data, we conclude that an astrophysical source for the putative non-LTE emission is unlikely. We note that the wavelength dependence of the signal seen by Swain et al. closely matches the 2(sub 1/2) band of water vapor at 300 K, and we suggest that an imperfect correction for telluric water is the source of the feature claimed by Swain et al.

Mandell, Avi M.↗
NASA NTRS1991

Far-infrared and submillimeter-wavelength observations of star-forming dense cores. I - Spectra

Far-infrared and submillimeter photometry of 10 low-mass star formation regions containing embedded IRAS sources is presented. These new observations define the peak of the spectral energy distributions of these objects and provide more precise estimates of their bolometric luminosities. Two new sources, L1527 and L483, are among the reddest known low-mass objects, with spectral energy distribution peaks at 100-200 microns and extremely steep IRAS slopes. These cold sources have spectra which are similar to blackbodies of 30-40 K but have significant excess emission on the Wien side. Models of the spectral energy distributions using a spherically symmetric core structure indicate that these sources have visual extinctions greater than 1000 mag. However, models with these large extinctions predict too little near-infrared emission. A nonspherically symmetric distribution of circumstellar material may play a role in the generation of the extra near-infrared emission.

Ladd, E. F.↗
NASA NTRSDate not supplied

A Machine Learning Framework for Error Compensation in Radiative Transfer Calculations

Radiative heat transfer influences the amount of heat flux transferred to the surface of the hypersonic vehicle, which is essential to evaluate the performance of thermal protection systems. The radiative heat flux is found to be computationally prohibitive while accounting for the variation in spatial, angular, and spectral domains. A new methodology has been recently developed to alleviate the cost of computation in the spectral domain by constructing flow-agnostic reduced-order models (ROMs). The developed spectral ROM databases provide grouping strategies that account for non-equilibrium absorption and emission as well as interaction between disparate species due to spectral overlap in associated radiative processes. However, the developed ROMs need to be optimized for a specific combination of interacting gas species and would need to re-calibrated in case individual species are added/omitted. In this work, we use various machine learning (ML) techniques to approximate the radiative intensities determined by a ROM optimized for a specific gas mixture. The ML model relies on the ROM databases developed for a single species which ignores any spectral overlap. Thus, radiation evaluation starts with a simple summation of radiative intensities predicted using these non-calibrated ROMs for the contributing species. The ML framework then provides a correction to account for the interplay in the frequency, i.e., emission of photons by one species and absorption by another, and yields mixture-specific radiation fields. Once trained on the individual ROM databases, the ML framework offers instantaneous corrections that serves as a time/cost effective alternative to the optimization of ROMs for a specific gas mixture. The ML framework is trained on both the high fidelity and ROM evaluated line of sight (LOS) data from Orion, Stardust, and FIRE II cases to obtain a general purpose correction model for earth re-entry scenarios when radiation contributions from both atomic nitrogen and atomic oxygen are considered. A geometric length scale parameter is used in the training process to account for errors introduced in the ROM databases as a consequence of high optical thickness. The efficacy of the ML framework is underscored through extensive analysis of train and test errors with respect to all the re-entry scenarios. The applicability of such an ML framework was further corroborated by embedding it in a state-of-the-art US3D - NERO system for determining the radiative heat flux transferred to the hypersonic vehicle surface.

Radiation↗