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NASA NTRS2007

GEO Population Estimates using Optical Survey Data

Optical survey data taken using the NASA Michigan Orbital Debris Survey Telescope (MODEST) gives us an opportunity to statistically sample faint object population in the Geosynchronous (GEO) and near-GEO environment. This paper will summarize the MODEST survey work that has been conducted by NASA since 2002, and will outline the techniques employed to arrive at the current population estimates in the GEO environment for dim objects difficult to detect and track using current systems in the Space Surveillance Network (SSN). Some types of orbits have a higher detection rate based on what parts of the GEO belt is being observed, a straightforward statistical technique is used to debias these observations to arrive at an estimate of the total population potentially visible to the telescope. The size and magnitude distributions of these fainter debris objects are markedly different from the catalogued population. GEO debris consists of at least two different populations, one which follows the standard breakup power law and one which has anomalously high Area-to-Mass Ratios (1 to approx. 30 square meters per kilogram; a sheet of paper = approx. 13 square meters per kilogram). The Inter-Agency Space Debris Coordination Committee (IADC) is investigating objects in GEO orbits with anomalously high Area-to-Mass Ratios (AMRs). The ESA Space Debris Telescope discovered this population and has and its properties of inclinations (0 to 30 degrees), changing eccentricities (0 and 0.6), and mean motions (approx. 1 rev), will be presented. The accepted interpretation of this orbital behavior is that solar radiation pressure drives the perturbations causing time varying inclinations and eccentricities. The orbital parameters are unstable for this population and thus difficult to predict. Their dim visual magnitudes and photometric variability make observations a challenge. The IADC has enlisted a series of observatories (participating institutions: University of Michigan/CTIO, Astronomical Institute University of Bern, Boeing LTS / AMOS, Keldysh Institute of Applied Mathematics) at different longitudes. Complete observational coverage over periods of days to months will provide a better understanding of the properties, such as solar radiation pressure effects on orbital elements, size, shape, attitude, color variations, and spectral characteristics. Results from recent observational programs will be summarized, and includes a description of the orbit elements prediction processes, a summary of the metric tracking performance, and some photometric characteristics of this class of debris.

Barker, Edwin S.↗

NASA NTRS1996

O2 A Band Studies for Cloud Detection and Algorithm Improvement

Detection of cloud parameters from space-based spectrometers can employ the vibrational bands of O2 in the (sup b1)Sigma(sub +)(sub g) yields X(sub 3) Sigma(sup -)(sub g) spin-forbidden electronic transition manifold, particularly the Delta nu = 0 A band. The GOME instrument uses the A band in the Initial Cloud Fitting Algorithm (ICFA). The work reported here consists of making substantial improvements in the line-by-line spectral database for the A band, testing whether an additional correction to the line shape function is necessary in order to correctly model the atmospheric transmission in this band, and calculating prototype cloud and ground template spectra for comparison with satellite measurements.

Chance, K. V.↗

NASA NTRS2018

Improving the Performance of the OMPS Limb Profiling Instrument in Monitoring Aerosols in the Post-Pinatubo Stratosphere

The OMPS Limb Profiling (LP) instrument was launched on NOAA's Suomi NPP (SNPP) weather satellite in October 2011. The instrument measures limb-scattered radiation in the ultraviolet, visible and NIR wavelengths with high vertical resolution (~2 km) and relatively dense spatial and temporal sampling (several thousand measurements/day covering the entire sunlit globe). These measurements have very high sensitivity to stratospheric aerosols due to long path of the incoming solar photons through the aerosol layer. However, unlike the recently launched ISS/SAGE III that directly measures extinction of solar/lunar radiation by gases and particles along the line of sight (LOS) of the instrument, information content of OMPS LP measurements is complex. It consists of solar radiation singly scattered and attenuated by aerosols, air, and trace gases along the LOS of the instrument, as well as diffuse upwelling radiation from the lower atmosphere that also gets scattered and attenuated into the LOS. To unscramble this complex signal one needs to have good knowledge of aerosol size distribution (ASD) and their complex refractive index. We will describe our recent efforts in constraining the ASD parameters by analyzing in-situ balloon data from Laramie, Wyoming; aerosol microphysical model data from CARMA; and spectral information provided by OMPS LP. We will also discuss our proposed methodology to reï¬ne this information by adjusting the microphysical properties of the aerosols to make data from various occultation and scattering instruments internally consistent. This is a generalized version of the technique employed by AERONET in which solar extinction data are combined with scattered radiation measured by the almucantar technique to determine aerosol particle shape, complex refractive index and size distribution. We suggest that such closure studies are essential to develop confidence in space-based data to validate aerosol microphysical models, such as CARMA, and aerosol chemistry- transport models, such as GOCART, and for estimating radiative forcing due to stratospheric aerosols in both volcanic and quiescent time periods.

Bhartia, P. K.↗

NASA NTRS2012

Accuracy Assessments of Cloud Droplet Size Retrievals from Polarized Reflectance Measurements by the Research Scanning Polarimeter

We present an algorithm for the retrieval of cloud droplet size distribution parameters (effective radius and variance) from the Research Scanning Polarimeter (RSP) measurements. The RSP is an airborne prototype for the Aerosol Polarimetery Sensor (APS), which was on-board of the NASA Glory satellite. This instrument measures both polarized and total reflectance in 9 spectral channels with central wavelengths ranging from 410 to 2260 nm. The cloud droplet size retrievals use the polarized reflectance in the scattering angle range between 135deg and 165deg, where they exhibit the sharply defined structure known as the rain- or cloud-bow. The shape of the rainbow is determined mainly by the single scattering properties of cloud particles. This significantly simplifies both forward modeling and inversions, while also substantially reducing uncertainties caused by the aerosol loading and possible presence of undetected clouds nearby. In this study we present the accuracy evaluation of our algorithm based on the results of sensitivity tests performed using realistic simulated cloud radiation fields.

Rainbow↗

NASA NTRS1994

Blocking reduction of Landsat Thematic Mapper JPEG browse images using optimal PSNR estimated spectra adaptive postfiltering

Two representative sample images of Band 4 of the Landsat Thematic Mapper are compressed with the JPEG algorithm at 8:1, 16:1 and 24:1 Compression Ratios for experimental browsing purposes. We then apply the Optimal PSNR Estimated Spectra Adaptive Postfiltering (ESAP) algorithm to reduce the DCT blocking distortion. ESAP reduces the blocking distortion while preserving most of the image's edge information by adaptively postfiltering the decoded image using the block's spectral information already obtainable from each block's DCT coefficients. The algorithm iteratively applied a one dimensional log-sigmoid weighting function to the separable interpolated local block estimated spectra of the decoded image until it converges to the optimal PSNR with respect to the original using a 2-D steepest ascent search. Convergence is obtained in a few iterations for integer parameters. The optimal logsig parameters are transmitted to the decoder as a negligible byte of overhead data. A unique maxima is guaranteed due to the 2-D asymptotic exponential overshoot shape of the surface generated by the algorithm. ESAP is based on a DFT analysis of the DCT basis functions. It is implemented with pixel-by-pixel spatially adaptive separable FIR postfilters. PSNR objective improvements between 0.4 to 0.8 dB are shown together with their corresponding optimal PSNR adaptive postfiltered images.

Linares, Irving↗

DOE OSTI2025

Comparing Machine Learning and Physics-Based Nanoparticle Geometry Determinations Using Far-Field Spectral Properties

Anisotropic metal nanostructures exhibit polarization-dependent light scattering, a property which has been widely studied and exploited to determine orientations of subwavelength structures using far-field microscopy. Here we explore the use of variational autoencoders (VAEs) to determine the geometries of gold nanorods (NRs) such as in-plane orientation and aspect ratio under linearly polarized dark-field illumination in an optical microscope. We enforce a shared latent space to connect two VAEs trained separately with polarized dark-field scattering spectra and electron microscopy images and achieve image prediction (shape, orientation, and size) of Au NRs using only polarized dark-field scattering spectra. We determine the geometrical parameters of orientational angle and aspect ratio quantitatively via both our dual-VAE and physics-based analysis on the input scattering spectra. We show that orientational angle prediction by dual-VAE performs well with only a small (~300 particle) training set, yielding a mean absolute error (MAE) of 14.4° and a concordance correlation coefficient (CCC) of 0.95. This performance is only marginally worse than the physics-based cos(2?) fitting approach between the scattering intensity and the polarizing angle, which achieves MAE of 8.78° and CCC of 0.99. Aspect ratio determination is also comparable for the dual-VAE and physics-based fitting comparison (MAE of 0.21 vs. 0.23 and CCC of 0.53 vs. 0.68). Here, this dual encoder-decoder architecture effectively exploits the structure-property relationships of plasmonic nanostructures to construct a cross-modal machine learning (ML) approach, providing a pathway to employ ML approaches to address other structure-property relationships in materials science.

Dark-field scattering↗

DOE OSTI2022

Constraining the local pulsar population with the cosmic-ray positron fraction

Observations of the TeV halos associated with nearby pulsars indicate that these objects inject significant fluxes of very high-energy electron-positrons pairs into the interstellar medium (ISM), thereby likely providing the dominant contribution to the cosmic-ray positron flux. In this paper, we use the cosmic-ray positron fraction as measured by the AMS-02 Collaboration to constrain the characteristics of the local pulsar population. For reasonable model parameters, we find that we can obtain good agreement with the measured positron fraction up to energies of E e ~ 300 GeV. At higher energies, the positron fraction is dominated by a small number of pulsars, making it difficult to reliably predict the shape of the expected positron fraction. The low-energy positron spectrum supports the conclusion that pulsars typically transfer approximately η ~ 5–20% of their total spindown power into the production of very high-energy electron-positron pairs, producing a spectrum of such particles with a hard spectral index, α ~ 1.5–1.7. Such pulsars typically spindown on a timescale on the order of τ ~ 10 4 years. Our best fits were obtained for models in which the radio and gamma-ray beams from pulsars are detectable to 28% and 62% of surrounding observers, respectively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2015

Progress Towards Improved Analysis of TES X-ray Data Using Principal Component Analysis

The traditional method of applying a digital optimal filter to measure X-ray pulses from transition-edge sensor (TES) devices does not achieve the best energy resolution when the signals have a highly non-linear response to energy, or the noise is non-stationary during the pulse. We present an implementation of a method to analyze X-ray data from TESs, which is based upon principal component analysis (PCA). Our method separates the X-ray signal pulse into orthogonal components that have the largest variance. We typically recover pulse height, arrival time, differences in pulse shape, and the variation of pulse height with detector temperature. These components can then be combined to form a representation of pulse energy. An added value of this method is that by reporting information on more descriptive parameters (as opposed to a single number representing energy), we generate a much more complete picture of the pulse received. Here we report on progress in developing this technique for future implementation on X-ray telescopes. We used an 55Fe source to characterize Mo/Au TESs. On the same dataset, the PCA method recovers a spectral resolution that is better by a factor of two than achievable with digital optimal filters.

Low-temperature detectors A[center dot] Transition↗

DOE OSTI2021

How Snow Aggregate Ellipsoid Shape and Orientation Variability Affects Fall Speed and Self-Aggregation Rates

Snow aggregate shapes and orientations have long been known to exhibit substantial variability. Despite this observed variability, most weather and climate prediction models use fixed power-law functions that deterministically map particle size to mass and fall speed. As such, integrated quantities like precipitation and self-aggregation rates currently ignore nonlinear effects resulting from variation in shape and orientation for aggregates of the same size. This study therefore develops an analytic framework that couples an empirically based bivariate distribution of ellipsoid shapes to classical hydrodynamic theory so as to capture an appropriate dispersion of masses, projected areas, and fall speeds for an assumed size distribution. For a fixed aggregate size, shape variations produce approximately ±0.13 m s -1 standard deviation of fall speed which increases the mass flux fall speed dispersion by more than 100% over traditional microphysics models. This increased fall speed dispersion results predominantly from shape-induced mass dispersion whereas orientation and drag dispersion play a lesser role. Shape variations can increase mass- and reflectivity-weighted fall speeds by up to 60% of traditional models whereas self-aggregation rates can increase by a factor of 100 for very small slope parameters. This implies that aggregate shape variations effectively forestall the theorized onset of fall speed distribution narrowing and subsequent quenching of the aggregation process. As a result, it is likely that secondary ice formation is necessary to prevent an ever decreasing slope parameter. The mathematical theory presented in this study is used to develop simple correction factors for snow forecast and climate models.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1982

The photospheric velocity field of Procyon

Balloon-borne Ultraviolet Stellar Spectrometer observations of the profiles of two well observed spectral lines in the ultraviolet spectrum of Alpha CMI (Procyon; F5IV-V) are analyzed with a Fourier transform method in order to determine values of various parameters of the velocity field of the upper photosphere. A microturbulent line-of-sight velocity component of 0.9 + or - 0.4 km/s, a macroturbulent velocity component of 5.3 + or - 0.2 km/s, and a rotational velocity component of 10.0 + or - 1.2 km/s were determined. In these calculations a single-moded sinusoidal isotropic macroturbulent velocity function was assumed. The result appears to be sensitive to the assumed shape of the macroturbulence function.

De Jager, C.↗

NASA NTRS1994

Generalized Comptonization models and application to the recent high-energy observations

The theory of spectral formation in thermal X-ray sources, where the effects of Comptonization and Klein-Nishina corrections are important, is presented. Analytical expressions are obtained for the produced spectrum as a function of such input parameters as the plasma temperature, the optical depth of the plasma cloud and the injected soft photon spectrum. The analytical theory developed here takes into account the dependence of the scattering opacity on the photon energy. It is shown that the plasma temperature as well as the asymptotic rate of photon escape from the plasma cloud determine the shape of the upscattered hard tail in the emergent spectra, even in the case of very small optical depths. The escape distributions of photons are given for any optical depth of the plasma cloud and their asymptotic dependence for very small and large optical depths are examined. It is shown that this new generalized approach can fit spectra for a large variety of hard X-ray sources and determine the plasma temperature in the region of main energy release in Cyg X-1 and the Seyfert galaxy NGC 4151.

Titarchuk, Lev↗

NASA NTRS1983

X-ray sensor development for magnetospheric research

The ARPA-301 data on the P78-1 satellite provide information on the long-term X-ray environment; specifically, the distributions in total X-ray intensities and energy spectral parameters and the spatial extents of the X-ray sources. The average X-ray intensity near noontime was found to decrease with increasing local time whereas the opposite trend occurs around midnight. At both of these local times, the average flux increases with increasing level of geomagnetic activity. The distributions in flux are also considered for given local time intervals and these span a large dynamic range. The temporal correlation between the X-ray flux in different local time sectors is found to decrease with increasing difference in local time. The average spectral shapes do not depend significantly upon local time or geomagnetic activity.

Imhof, W. L.↗

DOE OSTI2021

Investigation of Delayed Neutron Sensitivities for Several ICSBEP Benchmarks using MCNP

The effective delayed neutron (β$_{eff}$) is a very important parameter for reactor and criticality applications. This parameter is equal to the difference in reactivity between delayed critical ($k_{eff}$ = 1, which requires both prompt and delayed neutrons to achieve criticality) and prompt critical ($k_p$ = 1, which requires only prompt neutrons to achieve criticality). This is often referred to as the delayed critical "window" (the region of criticality between delayed and prompt critical). β$_{eff}$ is a reactor kinetics parameters and depends on the nuclides in the system that undergo fission as well as the spectral characteristics of the system. Measurements of β$_{eff}$ have been performed for many criticality experiments. The EUCLID (Experiments Underpinned by Computational Learning for Improvements in nuclear Data) project at Los Alamos National Laboratory (LANL) aims to constrain nuclear data by using a suite of measurement types beyond $k_{eff}$. Our team has recently investigated the use of pulsed spheres for nuclear data validation. Several other measurement methods are also of interest, including β$_{eff}$ (investigated here) and reactivity coefficients (investigated in a separate work at this same meeting). One focus of our work is to determine if other methods are complimentary to the critical experiments already utilized for nuclear data validation. This is important because if a method has similar sensitivities then it will not be particularly useful for nuclear data validation as it will provide the same information as the critical experiments already being used. Here "similar" could refer to several characteristics, one being the shape of a sensitivity profile over energy. In the future, these methods will be utilized (with both existing and new experiments) in machine learning algorithms for nuclear validation, similar to what is currently done for criticality experiments. In order to use a measurement type for nuclear validation, it is necessary to obtain cross-section sensitivities for that parameter. This work looks at one approach to estimate β$_{eff}$ sensitivities by utilizing $k_{eff}$ sensitivities within Monte Carlo N-Particle ® Code Version 6.2. This is applied to several criticality benchmarks. Results are compared and the benefits and limitations of this approach are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1980

Determination of the complex refractive index and size distribution of atmospheric particulates from bistatic-monostatic lidar and solar radiometer measurements

A method is presented for inferring both the size distribution and the complex refractive index of atmospheric particulates from combined bistatic-monostatic lidar and solar radiometer observations. The basic input measurements are spectral optical depths at several visible and near-infrared wavelengths as obtained with a solar radiometer and backscatter and angular scatter coefficients as obtained from a biostatic-monostatic lidar. The spectral optical depth measurements obtained from the radiometer are mathematically inverted to infer a columnar particulate size distribution. Advantage is taken of the fact that the shape of the size distribution obtained by inverting the particulate optical depth is relatively insensitive to the particle refractive index assumed in the inversion. Bistatic-monostatic angular scatter and backscatter lidar data are then processed to extract an optimum value for the particle refractive index subject to the constraint that the shape of the particulate size distribution be the same as that inferred from the solar radiometer data. Specifically, the scattering parameters obtained from the bistatic-monostatic lidar data are compared with corresponding theoretical computations made for various assumed refractive index values. That value which yields best agreement, in a weighted least squares sense, is selected as the optimal refractive index estimate. The results of this procedure applied to a set of simulated measurements as well as to measurements collected on two separate days are presented and discussed.

Reagan, J. A.↗

NASA NTRS2018

Semiclassical Calculations of Stark Broadening Parameters of He I Lines Revisited

Stark broadening parameters for spectral lines of He I lines, calculated using numerically improved semiclassical formalism of Griem are reported and favorably compared with the original results of Griem. The comparison with other sets of data is carried out and results presented also. In addition, new Stark broadening parameters are available now in extended electron temperature range from 2500 K to 80000 K.

Physics↗

NASA NTRS1987

Correlation between spectral state and quasi-periodic oscillation parameters in GX 5-1

In a series of seven Exosat observations, the bimodal spectral behavior and the quasi-periodic oscillation (QPO)/red noise properties of GX 5-1 show a strict correlation. In one of the two spectral states (characterized by a 'horizontal branch' in the hardness-intensity diagram), strong 20-40 Hz QPO and red noise below about 60 Hz were always present. In the other ('normal branch'), no QPO between 6 and 60 Hz or red noise above 1 Hz were detected, but there was an indication for weak QPO near 5 Hz. In both states 'very low frequency noise' (VLFN) is detected below 0.1 Hz which has a power-law shape and and which extends down to the lowest observed frequencies (0.0001 Hz). The VLFN is probably not directly related to the QPO. The results are compared to those on Sco X-1 and Cyg X-2 and it is concluded that, although all three sources show bimodal spectral and QPO/red noise behavior, there is a qualitative difference between GX 5-1 and Cyg X-2 on one hand and Sco X-1 on the other.

Van Der Klis, M.↗

DOE OSTI2023

Precision cosmology with primordial GW backgrounds in presence of astrophysical foregrounds

The era of Gravitational-Wave (GW) astronomy will grant the detection of the astrophysical GW background from unresolved mergers of binary black holes, and the prospect of probing the presence of primordial GW backgrounds. In particular, the low-frequency tail of the GW spectrum for causally-generated primordial signals (like a phase transition) offers an excellent opportunity to measure unambiguously cosmological parameters as the equation of state of the universe, or free-streaming particles at epochs well before recombination. We discuss whether this programme is jeopardised by the uncertainties on the astrophysical GW foregrounds that coexist with a primordial background. We detail the motivated assumptions under which the astrophysical foregrounds can be assumed to be known in shape, and only uncertain in their normalisation. In this case, the sensitivity to a primordial signal can be computed by a simple and numerically agile procedure, where the optimal filter function subtracts the components of the astrophysical foreground that are close in spectral shape to the signal. We show that the degradation of the sensitivity to the signal in presence of astrophysical foregrounds is limited to a factor of a few, and only around the frequencies where the signal is closer to the foregrounds. Our results highlight the importance of modelling the contributions of eccentric or intermediate-mass black hole binaries to the GW background, to consolidate the prospects to perform precision cosmology with primordial GW backgrounds.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2013

TPSAS-NF1676L-16299-DND

As part of the American Recovery and Reinvestment Act (ARRA) of 2009, the DOE ARM program deployed a new ground-‐based Arctic High Spectral Resolution Lidar (AHSRL) at the North Slope of Alaska (NSA) site. This lidar, which is based on the AHSRL that was part of the NOAA’s SEARCH (Study of Environmental Arctic Change) contribution to the Canadian Network for the Detection of Atmospheric Change (CANDAC) facility at Eureka, Nunavut Territory, is an autonomous lidar that provides calibrated profiles of particulate (i.e. aerosol and cloud) backscatter cross section, optical thickness and circular depolarization at 532 nm. The AHSRL provides measurements of both intensive and extensive particulate properties. The intensive parameters depend only on the nature of the particles (size, composition, shape), not on the quantity or concentration. Here we show examples of the AHSRL data during both clear and cloudy conditions to show how these measurements can be used to depict aerosols and clouds over the NSA.

Marian Clayton↗