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At least 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Effect of Extinction on Quasar Luminosity Distances Determined from UV and X-Ray Flux Measurements

Abstract In Khadka et al., a sample of X-ray-detected reverberation-mapped quasars was presented and applied for the comparison of cosmological constraints inferred using two well-established relations in active galactic nuclei—the X-ray/UV luminosity ( L X – L UV ) relation and the broad-line region radius–luminosity ( R – L ) relation. L X – L UV and R – L luminosity distances to the same quasars exhibit a distribution of their differences that is generally asymmetric and positively shifted for the six cosmological models we consider. We demonstrate that this behavior can be interpreted qualitatively as arising as a result of the dust extinction of UV/X-ray quasar emission. We show that the extinction always contributes to the nonzero difference between L X – L UV -based and R – L -based luminosity distances and we derive a linear relationship between the X-ray/UV color index E X −UV and the luminosity-distance difference, which also depends on the value of the L X – L UV relation slope. Taking into account the median and the peak values of the luminosity-distance difference distributions, the average X-ray/UV color index falls in the range of E ¯ X − UV = 0.03 – 0.28 mag for the current sample of 58 sources. This amount of extinction is typical for the majority of quasars and can be attributed to the circumnuclear and interstellar media of host galaxies. After applying the standard hard X-ray and far-UV extinction cuts, heavily extincted sources are removed but overall the shift toward positive values persists. The effect of extinction on luminosity distances is more pronounced for the L X – L UV relation since the extinction of UV and X-ray emissions both contribute.

Astronomy & Astrophysics↗
NASA NTRS1990

3-D components of a biological neural network visualized in computer generated imagery. II - Macular neural network organization

Computer-assisted reconstructions of small parts of the macular neural network show how the nerve terminals and receptive fields are organized in 3-dimensional space. This biological neural network is anatomically organized for parallel distributed processing of information. Processing appears to be more complex than in computer-based neural network, because spatiotemporal factors figure into synaptic weighting. Serial reconstruction data show anatomical arrangements which suggest that (1) assemblies of cells analyze and distribute information with inbuilt redundancy, to improve reliability; (2) feedforward/feedback loops provide the capacity for presynaptic modulation of output during processing; (3) constrained randomness in connectivities contributes to adaptability; and (4) local variations in network complexity permit differing analyses of incoming signals to take place simultaneously. The last inference suggests that there may be segregation of information flow to central stations subserving particular functions.

Ross, Muriel D.↗
NASA NTRS1990

Millimetre observations of comets P/Brorsen-Metcalf (1989o) and Austin (1989c1) with the IRAM 30-m radio telescope

Millimeter observations with the IRAM 30 m telescope were conducted in comet P/Brorsen-Metcalf (1989o) on September 1989 and Austin (1989c1) on April and May 1990. The HCN J(1-0) and J(3-2) lines were detected in both comets. The HCN production rate relative to water in P/Brorsen-Metcalf is comparable to that previously measured in comet P/Halley, while that inferred in comet Austin might be smaller by a factor of two. The H2CO(3 sub 12 - 2 sub 11) transition, marginally observed in comet P/Brorsen-Metcalf, was firmly detected in May 1990 in comet Austin. Observations performed at offset positions suggest that the source of H2CO might be distributed. The H2CO abundance is on the order of 0.5 percent that of water for both comets, assuming a scalelength of 10(exp 4) km at 1 AU from the Sun for the distributed source. During the May observing period of comet Austin, two new species were detected for the first time in a comet: hydrogen sulfide (H2S) through its 1(sub 10) - 1(sub 01) ortho line at 169 GHz, and methanol (CH3OH) through J(3-2) delta K = 0 transitions at 145 GHz. Preliminary estimates of their abundances are 1.5 x 10(exp -3) for H2S and 8 x 10(exp -3) for CH3OH.

Colom, P.↗
NASA NTRS1992

Inference in fuzzy rule bases with conflicting evidence

Inference based on fuzzy 'If ... then' rules has played a very important role since when Zadeh proposed the Compositional Rule of Inference and, especially, since the first successful application presented by Mamdani. From the mid-1980's when the 'fuzzy boom' started in Japan, numerous industrial applications appeared, all using simplified techniques because of the high levels of computational complexity. Another feature is that antecedents in the rules are distributed densely in the input space, so the conclusion can be calculated by some weighted combination of the consequents of the matching (fired) rules. The CRI works in the following way: If R is a rule and A* is an observation, the conclusion is computed by B* = R o A* (o stands for the max-min composition). Algorithms implementing this idea directly have an exponential time complexity (maybe the problem is NP-hard) as the rules are relations in X x Y, a k1 x k2 dimensional space, if X is k1, Y is k2 dimensional. The simplified techniques usually decompose the relation into k1 projections in X(sub i) and measure in some way the degree of similarity between observation and antecedent by some parameter of the overlapping. These parameters are aggregated to a single value in (0,1) which is applied as a resulting weight for the given rule. The projections of rules in dimensions Y(sub i) are weighted by these aggregated values and then they are combined in order to obtain a resulting conclusion separately in every dimension. This method is unapplicable with sparse bases as there is no guarantee that an arbitrary observation matches with any of the antecedents. Then, the degree of similarity is 0 and all consequents are weighted by 0. Some considerations for such a situation are summarized in the next sections.

Koczy, Laszlo T.↗
NASA NTRS1992

Polarization and the envelopes of B(e) supergiants in the Magellanic Clouds

We report optical linear polarization observations of nine B(e) supergiants in the Magellanic Clouds. Several of them have large intrinsic polarizations. The data are consistent with nonspherically symmetric envelopes, around the B(e) stars, that possess a range of intrinsic polarizations. Comparison of the polarimetric data with the viewing aspect, inferred from the spectroscopy of the individual objects, agrees with this interpretation. The polarization correlates best with the infrared excess due to dust, suggesting the latter as the cause of most of the polarization. We cannot find, using the available data, a statistically significant difference between the polarization distributions of Galactic and Magellanic B(e) stars. Comparison of our data with previous polarimetric data, recovered from the literature for four stars, seems to indicate that the envelopes are stable.

Magalhaes, A. M.↗
NASA NTRS2011

What Turns Galaxies Off? the Different Morphologies of Star-Forming and Quiescent Galaxies Since z Approximates 2 from CANDELS

We use HST/WFC3 imaging from the CANDELS multicyc1e treasury survey, in conjunction with the Sloan Digital Sky Survey, to explore the evolution of galactic structure for galaxies with stellar masses > 3 x 10(exp 10) Solar Mass from Z= 2.2 to the present epoch, a time span of 10 Gyr. We explore the relationship between rest-frame optical color, stellar mass, star formation activity and the structural parameters of galaxies as determined from parametric fits to the surface brightness profiles of galaxies. We confirm the dramatic evolution from z= 2.2 to the present day in the number density of non-star-forming galaxies above 3 x 10(exp 10) Solar Mass reported by other authors. We find that the vast majority of these quiescent systems have concentrated light profiles, as parameterized by the Sersic index, and the population of concentrated galaxies grows similarly rapidly. We examine the joint distribution of star formation activity, Sersic index, stellar mass, mass divided by radius (a proxy for velocity dispersion), and stellar surface density. Quiescence correlates poorly with stellar mass at all z < 2.2 (given the approx < 0.2 dex scatter between halo mass and stellar mass at z approximates 0 inferred by More et al, this argues against halo mass being the only factor determining quiescence). Quiescence correlates better with Sersic index, 'velocity dispersion' and stellar surface density, where Sersic index correlates the best (increasingly so at lower redshift). Yet, there is significant scatter between quiescence and galaxy structure: while the vast majority of quiescent galaxies have prominent bulges, many of them have significant disks, and a number of bulge-dominated galaxies have significant star formation. Noting the rarity of quiescent galaxies without prominent bulges, we argue that a prominent bulge (and, perhaps by association, a supermassive black hole) is a necessary but not sufficient condition for quenching star formation on galactic scales over the last 10 Gyr; such a result is qualitatively consistent with the expectations of the AGN feedback paradigm.

Bell, Eric F.↗
NASA NTRS2017

Near Earth Asteroid Characterization for Threat Assessment

Physical characteristics of NEAs are an essential input to modeling behavior during atmospheric entry and to assess the risk of impact but determining these properties requires a non-trivial investment of time and resources. The characteristics relevant to these models include size, density, strength and ablation coefficient. Some of these characteristics cannot be directly measured, but rather must be inferred from related measurements of asteroids and/or meteorites. Furthermore, for the majority of NEAs, only the basic measurements exist so often properties must be inferred from statistics of the population of more completely characterized objects. The Asteroid Threat Assessment Project at NASA Ames Research Center has developed a probabilistic asteroid impact risk (PAIR) model in order to assess the risk of asteroid impact. Our PAIR model and its use to develop probability distributions of impact risk are discussed in other contributions to PDC 2017 (e.g., Mathias et al.). Here we utilize PAIR to investigate which NEA characteristics are important for assessing the impact threat by investigating how changes in these characteristics alter the damage predicted by PAIR. We will also provide an assessment of the current state of knowledge of the NEA characteristics of importance for asteroid threat assessment. The relative importance of different properties as identified using PAIR will be combined with our assessment of the current state of knowledge to identify potential high impact investigations. In addition, we will discuss an ongoing effort to collate the existing measurements of NEA properties of interest to the planetary defense community into a readily accessible database.

Asteroid characterization↗
NASA NTRS2007

Toward the characterization of upper tropospheric clouds using Atmospheric Infrared Sounder and Microwave Limb Sounder observations

We estimate the accuracy of cloud top altitude (Z) retrievals from the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) observing suite (ZA) on board the Earth Observing System Aqua platform. We compare ZA with coincident measurements of Z derived from the micropulse lidar and millimeter wave cloud radar at the Atmospheric Radiation Measurement (ARM) program sites of Nauru and Manus islands (ZARM) and the inferred Z from vertically resolved Microwave Limb Sounder (MLS) ice water content (IWC) retrievals. The mean difference in ZA minus ZARM plus or minus one standard deviation ranges from −2.2 to 1.6 km ± 1.0 to 4.2 km for all cases of AIRS effective cloud fraction (f A) > 0.15 at Manus Island using the cloud radar only. The range of mean values results from using different approaches to determine ZARM, day/night differences, and the magnitude of f A; the variation about the mean decreases for increasing values of f A. Analysis of ZARM from the micropulse lidar at Nauru Island for cases restricted to 0.05 ≤ f A ≤ 0.15 indicates a statistically significant improvement in ZA − ZARM over the cloud radar-derived values at Manus Island. In these cases the ZA − ZARM difference is −1.1 to 2.1 km ± 3.0 to 4.5 km. These results imply that the operational ZA is quantitatively useful for constraining cirrus altitude despite the nominal 45 km horizontal resolution. Mean differences of cloud top pressure (PCLD) inferred from coincident AIRS and MLS ice water content (IWC) retrievals depend upon the method of defining AIRS PCLD (as with the ARM comparisons) over the MLS spatial scale, the peak altitude and maximum value of MLS IWC, and f A. AIRS and MLS yield similar vertical frequency distributions when comparisons are limited to f A > 0.1 and IWC > 1.0 mg m−3. Therefore the agreement depends upon the opacity of the cloud, with decreased agreement for optically tenuous clouds. Further, the mean difference and standard deviation of AIRS and MLS PCLD are highly dependent on the MLS tangent altitude. For MLS tangent altitudes greater than 146 hPa, the strength of the limb technique, the disagreement becomes statistically significant. This implies that AIRS and MLS “agree” in a statistical sense at lower tangent altitudes and “disagree” at higher tangent altitudes. These results provide important insights on upper tropospheric cloudiness as observed by nadir-viewing AIRS and limb-viewing MLS.

Wu, Dong L.↗
NASA NTRSDate not supplied

Small-Sample Estimator Decisions – Certainly Uncertain in Human Spaceflight at NASA

Within statistics when estimating means, we rely heavily on the Central Limit Theorem (CLT) to aid in our inference, however in cases where the CLT does not apply we begin to be strongly limited in our choices. If a violation to the CLT comes in the form of small samples and unknown population variance, yet we maintain the assumption of normality, the use of t-distributions is perfectly valid. We explore cases where population normality is not assumed, where sample sizes are small, and where some actionable estimate of the central tendency of a distribution is needed such as for spaceflight operational decisions. Here we identify different scenarios based on measures taken from spaceflight, characterizing performance of estimators of central tendency within our set of simulations. We examine bias and variability of standard estimators of central tendency as they apply to varying small sample sizes and varying population distributions. Further work in this area is needed to develop a framework or set of guidelines for individuals set in these situations. Even with limited information, decisions need to be made.

Central Tendency↗
DOE OSTI2024

Integrated analysis of X-ray diffraction patterns and pair distribution functions for machine-learned phase identification

Abstract To bolster the accuracy of existing methods for automated phase identification from X-ray diffraction (XRD) patterns, we introduce a machine learning approach that uses a dual representation whereby XRD patterns are augmented with simulated pair distribution functions (PDFs). A convolutional neural network is trained directly on XRD patterns calculated using physics-informed data augmentation, which accounts for experimental artifacts such as lattice strain and crystallographic texture. A second network is trained on PDFs generated via Fourier transform of the augmented XRD patterns. At inference, these networks classify unknown samples by aggregating their predictions in a confidence-weighted sum. We show that such an integrated approach to phase identification provides enhanced accuracy by leveraging the benefits of each model’s input representation. Whereas networks trained on XRD patterns provide a reciprocal space representation and can effectively distinguish large diffraction peaks in multi-phase samples, networks trained on PDFs provide a real space representation and perform better when peaks with low intensity become important. These findings underscore the importance of using diverse input representations for machine learning models in materials science and point to new avenues for automating multi-modal characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The primordial matter power spectrum on sub-galactic scales

The primordial matter power spectrum quantifies fluctuations in the distribution of dark matter immediately following inflation. Over cosmic time, overdense regions of the primordial density field grow and collapse into dark matter haloes, whose abundance and density profiles retain memory of the initial conditions. By analysing the image magnifications in 11 strongly lensed and quadruply imaged quasars, we infer the abundance and concentrations of low-mass haloes, and cast the measurement in terms of the amplitude of the primordial matter power spectrum. We anchor the power spectrum on large scales, isolating the effect of small-scale deviations from the Lambda cold dark matter (ΛCDM) prediction. Assuming an analytic model for the power spectrum and accounting for several sources of potential systematic uncertainty, including three different models for the halo mass function, we obtain correlated inferences of $\log _{10}\left(P / P_{\Lambda \rm {CDM}}\right)$, the power spectrum amplitude relative to the predictions of the concordance cosmological model, of $0.0_{-0.4}^{+0.5}$, $0.1_{-0.6}^{+0.7}$, and $0.2_{-0.9}^{+1.0}$ at k = 10, 25, and 50 $\rm {Mpc^{-1}}$ at $68 {{\ \rm per\ cent}}$ confidence, consistent with CDM and single-field slow-roll inflation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Learning Global Proliferation Expertise Evolution Using AI-Driven Analytics and Public Information

Detecting and anticipating global proliferation expertise and capability evolution from unstructured, noisy, and incomplete public data streams is a highly desired, but extremely challenging task. Here, in this article, we present our pioneering data-driven approach to support the non-proliferation mission to detect and explain the evolution of proliferation expertise and capability development globally from terabytes of publicly available information (PAI), focusing on our knowledge extraction pipeline and descriptive analytics. We first discuss how we fuse nine open-source data streams, including multilingual data, to convert 4 TB of unstructured data to structured knowledge and encode dynamically evolving proliferation expertise representations—content and context graphs. For this, we rely on natural language processing (NLP) and deep learning (DL) models to perform information extraction, topic modeling, and distributed text representation (aka embedding) learning. We then present interactive, usable, and explainable descriptive analytics to refine domain knowledge and present it in a human-understandable form. Finally, we introduce future work avenues that will leverage our dynamic knowledge representations and descriptive analytics to enable predictive and prescriptive inferences to achieve real-time domain understanding and contextual reasoning about global proliferation expertise and capability evolution.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
NASA NTRS1978

Coronal gas in the Galaxy. II - A statistical analysis of O VI absorptions

This paper deals with general inferences about the low-density phase of interstellar gas having temperatures well above 200,000 K (the 'coronal gas') which can be drawn from O VI absorption data for 72 stars. Attention is given to the behavior of radial velocities, possible evidence for circumstellar O VI, the space distribution of the O VI gas, crowding of normal interstellar gas, and temperature distributions for the coronal gas. A model is adopted in which the coronal gas is contained within randomly distributed and nonoverlapping parcels, each with a size, pressure, and internal temperature distribution that do not vary markedly from one unit to the next. It is shown that the one-dimensional velocity dispersion for O VI regions (26 km/s) is substantially higher than the value for ordinary interstellar clouds (6.4 km/s).

Jenkins, E. B.↗
NASA NTRS1980

Microstructure of the interplanetary magnetic field near 4 and 5 AU

Interplanetary magnetic field fluctuations near 4 and 5 AU are investigated on the basis of Pioneer 10 and 11 vector magnetic field measurements in order to identify extant wave modes and propagation directions as functions of frequency in the range 0.00004 to 0.009 Hz. Analysis of the approximately 500 spectral matrices as functions of frequency obtained from each spacecraft indicates the distributions of maximum variance directions to be peaked along the normal to the plane of the minimum variance direction and the mean magnetic field, as would be expected for a planar, small-amplitude Alfven wave with a minimum variance direction close to the wave vector. It is thus inferred that single small-amplitude Alfven waves are occasionally present in the temporal and frequency bands analyzed, however waves with wave vectors not well approximated by the minimum variance direction, Alfven wave ensembles, finite-amplitude waves and nonplanar fluctuations may also be present. Observations are also noted to suggest the predominance of the Alfven mode over the fast and slow modes, however do not support theoretical models of outward propagating plane Alfven waves of solar origin.

Parker, G. D.↗
NASA NTRS1984

Application of Fabry-perot Spectrometers for Measurement of Upper Atmosphere Temperatures and Winds

The mechanisms giving rise to certain airglow and auroral emissions and their height distribution are briefly surveyed. The basic principles of operation of scanning Fabry-Perot spectrometers are outlined in order to illustrate the calibration and use of such instruments to measure Doppler broadening and shift of atomic emission lines in the spectrum of the airglow and aurora and hence to infer atmospheric temperatures and wind velocities. Technical details of some specific instruments are given. Brief mention is made of the use of wide angle Michelson interferometers for the same application. Emphasis is given to the future importance of imaging Fabry-Perot spectrometers to permit the detailed mapping of temperature and wind velocity, especially in the auroral regions.

F Jacka↗
NASA NTRS1985

Approximate supernova remnant dynamics with cosmic ray production

Supernova explosions are the most violent and energetic events in the galaxy and have long been considered probably sources of Cosmic Rays. Recent shock acceleration models treating the Cosmic Rays (CR's) as test particles nb a prescribed Supernova Remnant (SNR) evolution, indeed indicate an approximate power law momentum distribution f sub source (p) approximation p(-a) for the particles ultimately injected into the Interstellar Medium (ISM). This spectrum extends almost to the momentum p = 1 million GeV/c, where the break in the observed spectrum occurs. The calculated power law index approximately less than 4.2 agrees with that inferred for the galactic CR sources. The absolute CR intensity can however not be well determined in such a test particle approximation.

Voelk, H. J.↗
NASA NTRS1986

Penetration of sunlight into a canopy - Explicit models based on vertical and horizontal leaf projections

The projections of leaf areas onto a horizontal plane and onto a vertical plane are examined for their utility in characterizing canopies for sunlight penetration (direct beam only) models. These projections exactly specify the penetration if the projections on the principal plane of the normals to the top surfaces of the leaves are in the same quadrant as the sun. Inferring the total leaf area from these projections (and therefore the penetration as a function of the total leaf area) is possible only with a large uncertainty (up to + or - 32 percent) because the projections are a specific measure of the total leaf area only if the leaf angle distribution is known. It is expected that this uncertainty could be reduced to more acceptable levels by making an approximate assessment of whether the zenith angle distribution is that of an extremophile canopy.

Otterman, J.↗
NASA NTRS1993

Nitrates in SNCs: Implications for the nitrogen cycle on Mars

Nitrogen is the second most abundant constituent of the Martian atmosphere, after CO2, present at a level of ca. 2.7 percent. Several authors have hypothesized that earlier in the planet's history, nitrogen was more abundant, but has been removed by processes such as exospheric loss from the atmosphere. However, an alternative sink for atmospheric nitrogen is the regolith; model calculations have predicted that, via the formation of NOx, HNO2 and HNO3 in the lower layers of the Martian atmosphere, the regolith might trap nitrite and nitrate anions, leading to the build-up of involatile nitrates. Integrated over 4.5 x 10(exp 9) yr, such a mechanism would contribute the equivalent of a layer of nitrates up to 0.3 cm thick distributed across the Martian surface. Features in thermal emission spectra of the surface of Mars have been interpreted tentatively as emanating from various anions (carbonates, bicarbonates, sulphates, etc.), and the presence of nitrates has also been addressed as a possibility. The identification of carbonates in SCN meteorites has allowed inferences to be drawn concerning the composition and evolution of the Martian atmosphere in terms of its carbon isotope systematics; if nitrites, nitrates, or other nitrogen-bearing salts could be isolated from SNC's, similar conclusions might be possible for an analogous nitrogen cycle. Nitrates are unstable, being readily soluble in water, and decomposed at temperatures between 50 C and 600 C, depending on composition. Any nitrates present in SNC's might be removed during ejection from the planet's surface, passage to Earth, or during the sample's terrestrial history, by weathering etc. The same might have been said for carbonates, but pockets of shock-produced glass (lithology C) from within the EET A79001 shergottite and bulk samples of other SNC contain this mineral, which did apparently survive. Nitrates occurring within the glassy melt pockets of lithology C in EET A79001 might likewise be protected. Lithology C glass was therefore selected for nitrate analysis, first by non-destructive infra red spectroscopy, and then by stepped combustion.

Grady, Monica M.↗