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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

RESOLVED NEAR-INFRARED SPECTROSCOPY OF WISE J104915.57-531906.1AB: A FLUX-REVERSAL BINARY AT THE L DWARF/T DWARF TRANSITION

We report resolved near-infrared spectroscopy and photometry of the recently identified brown dwarf binary WISE J104915.57-531906.1AB, located 2.02 {+-} 0.15 pc from the Sun. Low-resolution spectral data from Magellan/FIRE and IRTF/SpeX reveal strong H{sub 2}O and CO absorption features in the spectra of both components, while the secondary also exhibits weak CH{sub 4} absorption at 1.6 {mu}m and 2.2 {mu}m. Spectral indices and comparison to low-resolution spectral standards indicate component types of L7.5 and T0.5 {+-} 1, the former consistent with the optical classification of the primary. Both sources also have unusually red spectral energy distributions for their spectral types, which we attribute to enhanced condensate opacity (thick clouds). Relative photometry reveals a flux reversal between the J and K bands, with the T dwarf component being brighter in the 0.95-1.3 {mu}m region ({Delta}J = -0.31 {+-} 0.05). As with other L/T transition binaries, this reversal likely reflects the depletion of condensate opacity in the T dwarf, with the contrast enhanced by the thick clouds present in the photosphere of the L dwarf primary. The 1 {mu}m flux from the T dwarf most likely emerges from gaps in its cloud layer, as suggested by the significant optical variability detected from this source by Gillon et al. Component mass measurements of the WISE J1049-5319AB system through astrometric and component radial velocity monitoring may resolve the current debate as to whether the loss of photospheric condensate clouds at the L dwarf/T dwarf boundary is a slow or rapid process, a conceivable endeavor given its proximity, brightness, small separation (3.1 {+-} 0.3 AU), and reasonable orbital period (20-30 yr)

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

A Software Package for Neural Network Applications Development

Original Backprop (Version 1.2) is an MS-DOS package of four stand-alone C-language programs that enable users to develop neural network solutions to a variety of practical problems. Original Backprop generates three-layer, feed-forward (series-coupled) networks which map fixed-length input vectors into fixed length output vectors through an intermediate (hidden) layer of binary threshold units. Version 1.2 can handle up to 200 input vectors at a time, each having up to 128 real-valued components. The first subprogram, TSET, appends a number (up to 16) of classification bits to each input, thus creating a training set of input output pairs. The second subprogram, BACKPROP, creates a trilayer network to do the prescribed mapping and modifies the weights of its connections incrementally until the training set is leaned. The learning algorithm is the 'back-propagating error correction procedures first described by F. Rosenblatt in 1961. The third subprogram, VIEWNET, lets the trained network be examined, tested, and 'pruned' (by the deletion of unnecessary hidden units). The fourth subprogram, DONET, makes a TSR routine by which the finished product of the neural net design-and-training exercise can be consulted under other MS-DOS applications.

Baran, Robert H.↗
DOE OSTI2015

A SEARCH FOR L/T TRANSITION DWARFS WITH PAN-STARRS1 AND WISE. II. L/T TRANSITION ATMOSPHERES AND YOUNG DISCOVERIES

The evolution of brown dwarfs from L to T spectral types is one of the least understood aspects of the ultracool population, partly for lack of a large, well-defined, and well-characterized sample in the L/T transition. To improve the existing census, we have searched ≈28,000 deg{sup 2} using the Pan-STARRS1 and Wide-field Infrared Survey Explorer surveys for L/T transition dwarfs within 25 pc. We present 130 ultracool dwarf discoveries with estimated distances ≈9–130 pc, including 21 that were independently discovered by other authors and 3 that were previously identified as photometric candidates. Seventy-nine of our objects have near-IR spectral types of L6–T4.5, the most L/T transition dwarfs from any search to date, and we have increased the census of L9–T1.5 objects within 25 pc by over 50%. The color distribution of our discoveries provides further evidence for the “L/T gap,” a deficit of objects with (J − K){sub MKO} ≈ 0.0–0.5 mag in the L/T transition, and thus reinforces the idea that the transition from cloudy to clear photospheres occurs rapidly. Among our discoveries are 31 candidate binaries based on their low-resolution spectral features. Two of these candidates are common proper motion companions to nearby main sequence stars; if confirmed as binaries, these would be rare benchmark systems with the potential to stringently test ultracool evolutionary models. Our search also serendipitously identified 23 late-M and L dwarfs with spectroscopic signs of low gravity implying youth, including 10 with vl-g or int-g gravity classifications and another 13 with indications of low gravity whose spectral types or modest spectral signal-to-noise ratio do not allow us to assign formal classifications. Finally, we identify 10 candidate members of nearby young moving groups (YMG) with spectral types L7–T4.5, including three showing spectroscopic signs of low gravity. If confirmed, any of these would be among the coolest known YMG members and would help to determine the effective temperature at which young brown dwarfs cross the L/T transition.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

LIGHT CURVES OF 32 LARGE TRANSNEPTUNIAN OBJECTS

We present observations of 32 primarily bright, newly discovered Transneptunian objects (TNOs) observable from the Southern Hemisphere during 39 nights of observation with the Irenee du Pont 2.5 m telescope at Las Campanas Observatory. Our dataset includes objects in all dynamical classes, but is weighted toward scattered objects. We find 15 objects for which we can fit periods and amplitudes to the data, and place light curve amplitude upper limits on the other 17 objects. Combining our sample with the larger light curve sample in the literature, we find a 3{sigma} correlation between light curve amplitude and absolute magnitude with fainter objects having larger light curve amplitudes. We looked for correlations between light curve and individual orbital properties, but did not find any statistically significant results. However, if we consider light curve properties with respect to object dynamical classification, we find statistically different distributions between the classical-scattered and classical-resonant populations at the 95.60% and 94.64% level, respectively, with the classical objects having larger amplitude light curves. The significance is 97.05% if the scattered and resonant populations are combined. The properties of binary light curves are largely consistent with the greater TNO population except in the case of tidally locked systems. All the Haumea family objects measured so far have light curve amplitudes and rotation periods {<=}10 hr, suggesting that they are not significantly different from the larger TNO population. We expect multiple factors are influencing object rotations: object size dominates light curve properties except in the case of tidal, or proportionally large collisional interactions with other TNOs, the influence of the latter being different for each TNO sub-population. We also present phase curves and colors for some of our objects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Enabling modern data discovery for atmospheric measurements

The Atmospheric Radiation Measurement (ARM) user facility is a US Department of Energy Office of Science user facility that is managed and operated through a collaborative effort led by nine US Department of Energy national laboratories. The ARM Data Center, located at Oak Ridge National Laboratory, is responsible for the timely collection, processing, and delivery of data products to the scientific community. The ARM Data Center holds more than 11,000 data products, including metadata collected from field campaigns, instruments, value-added products, and principal investigator–contributed data. These data sets are checked for successful transfer (for most data, this transfer is carried out automatically via the network; however, some of the largest data sets and some of the most remote sites require manual shipping of hard disks) and both the data and metadata are processed to a standard format, which is an ARM-standardized structure, via the Network Common Data Form. The Network Common Data Form is a self-describing binary format with many compatible software tools. Once processed, the data are cataloged, stored in the ARM Data Archive, and made discoverable through association with an array of metadata-characterizing information, such as location and measurement classification. These metadata enable powerful search capabilities through the ARM Data Center Data Discovery interface. This paper discusses the workflow of how the new discovery system has been redesigned from user requirements and how the data are distributed to the scientific community.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Tomographic separation of composite spectra - The components of the O-star spectroscopic binary AO Cassiopeiae

The UV photospheric lines of the short-period, double-lined O-star spectroscopic binary AO Cas are analyzed. Archival data from IUE (16 spectra uniformly distributed in orbital phase) were analyzed with a tomography algorithm to produce the separate spectra of the two stars in six spectral regions. The spectral classifications of the primary and secondary, O9.5 III and O8 V, respectively, were estimated through a comparison of UV line ratios with those in spectral standard stars. An intensity ratio of 0.5-0.7 (primary brighter) at 1600 A is compatible with the data.

Bagnuolo, William G., Jr.↗
DOE OSTI2023

CEGANN: CRYSTAL EDGE GRAPH ATTENTION NEURAL NETWORK

SF-22-156 Machine learning (ML) models and applications in materials design and discovery typically involve the use of feature representations or descriptors followed by a learning algorithm that maps them to user desired properties of interest. Most popular mathematical formulation-based descriptors are not unique across atomic environments and suffer from transferability issues across different application domains and/or material classes. The CEGANN code provides a unified interface to facilitate material characterization across materials across multiple scales (from atomic to mesoscale) and diverse classes of materials ranging from metals oxides, non-metals, and even hierarchical materials such as zeolites and semi ordered materials such as mesophases. CEGANN implements a Graph Attention Network (GAT) type convolution architecture. The details of network architecture can be found in the paper https://doi.org/10.48550/arXiv.2207.10168. The software comes with pretrained examples and dataset for the classification of the following representative systems: (1) Structure-level representation such as space group (2) Structural dimensionality (e.g., bulk, 2D, clusters etc.) (3) Grain boundary identification (4) Nucleation and growth of a zeolite polymorph (5) Characterization of binary mesophases and their phase transitions (6) Growth of ice. The code is written in python programming language.

CHAN, HENRYT↗
NASA NTRS2018

Black Holes and Neutron Stars in Nearby Galaxies: Insights from NuSTAR

Nearby galaxy surveys have long classified X-ray binaries (XRBs) by the mass category of their donor stars (high-mass and low-mass). The NuSTAR (Nuclear Spectroscopic Telescope Array) observatory, which provides imaging data at E greater than 10 keV (kiloelectronvolts), has enabled the classification of extragalactic XRBs by their compact object type: neutron star (NS) or black hole (BH). We analyzed NuSTAR/Chandra/XMM-Newton observations from a NuSTAR-selected sample of 12 galaxies within 5 Mpc (megaparsecs) having stellar masses (M (sub asterisk)) 10 (sup 7-11) solar masses and star formation rates (SFRs) approximately 0.01-15 solar masses per year. We detected 128 NuSTAR sources to a sensitivity of 10 (sup 38) ergs per second. Using NuSTAR color-intensity and color-color diagrams we classified 43 of these sources as candidate NSs and 47 as candidate BHs. We further subdivide BHs by accretion states (soft, intermediate, and hard) and NSs by weak (Z/Atoll) and strong (accreting pulsar) magnetic field. Using eight normal (Milky Way-type) galaxies in the sample, we confirm the relation between the SFR and galaxy X-ray point source luminosity in the 4-25 and 12-25 keV energy bands. We also constrained galaxy X-ray point source luminosity using the relation L (sub X) equals M (sub asterisk) plus Beta SFR, finding agreement with previous work. The X-ray luminosity function (XLF) of all sources in the 4-25 and 12-25 keV energy bands matches the alpha = 1.6 slope for high-mass XRBs. We find that NS XLFs suggest a decline beginning at the Eddington limit for a 1.4 solar mass NS, whereas the BH fraction shows an approximate monotonic increase in the 4-25 and 12-25 keV energy bands. We calculate the overall ratio of BH to NS to be approximately 1 for 4-25 keV and approximately 2 for 12-25 keV.

Vulic, N.↗
DOE OSTI2018

Automatic optical detection and classification of marine animals around MHK converters using machine vision

Optical systems provide valuable information for evaluating interactions and associations between organisms and MHK energy converters and for capturing potentially rare encounters between marine organisms and MHK device. The deluge of optical data from cabled monitoring packages makes expert review time-consuming and expensive. We propose algorithms and a processing framework to automatically extract events of interest from underwater video. The open-source software framework consists of background subtraction, filtering, feature extraction and hierarchical classification algorithms. This principle classification pipeline was validated on real-world data collected with an experimental underwater monitoring package. An event detection rate of 100% was achieved using robust principal components analysis (RPCA), Fourier feature extraction and a support vector machine (SVM) binary classifier. The detected events were then further classified into more complex classes – algae | invertebrate | vertebrate, one species | multiple species of fish, and interest rank. Greater than 80% accuracy was achieved using a combination of machine learning techniques.

16 TIDAL AND WAVE POWER↗
DOE OSTI2014

Flexible and scalable methods for quantifying stochastic variability in the era of massive time-domain astronomical data sets

We present the use of continuous-time autoregressive moving average (CARMA) models as a method for estimating the variability features of a light curve, and in particular its power spectral density (PSD). CARMA models fully account for irregular sampling and measurement errors, making them valuable for quantifying variability, forecasting and interpolating light curves, and variability-based classification. We show that the PSD of a CARMA model can be expressed as a sum of Lorentzian functions, which makes them extremely flexible and able to model a broad range of PSDs. We present the likelihood function for light curves sampled from CARMA processes, placing them on a statistically rigorous foundation, and we present a Bayesian method to infer the probability distribution of the PSD given the measured light curve. Because calculation of the likelihood function scales linearly with the number of data points, CARMA modeling scales to current and future massive time-domain data sets. We conclude by applying our CARMA modeling approach to light curves for an X-ray binary, two active galactic nuclei, a long-period variable star, and an RR Lyrae star in order to illustrate their use, applicability, and interpretation.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2014

Symbiotic Stars in X-rays

Until recently, symbiotic binary systems in which a white dwarf accretes from a red giant were thought to be mainly a soft X-ray population. Here we describe the detection with the X-ray Telescope (XRT) on the Swift satellite of 9 white dwarf symbiotics that were not previously known to be X-ray sources and one that was previously detected as a supersoft X-ray source. The 9 new X-ray detections were the result of a survey of 41 symbiotic stars, and they increase the number of symbiotic stars known to be X-ray sources by approximately 30%. Swift/XRT detected all of the new X-ray sources at energies greater than 2 keV. Their X-ray spectra are consistent with thermal emission and fall naturally into three distinct groups. The first group contains those sources with a single, highly absorbed hard component, which we identify as probably coming from an accretion-disk boundary layer. The second group is composed of those sources with a single, soft X-ray spectral component, which likely arises in a region where low-velocity shocks produce X-ray emission, i.e. a colliding-wind region. The third group consists of those sources with both hard and soft X-ray spectral components. We also find that unlike in the optical, where rapid, stochastic brightness variations from the accretion disk typically are not seen, detectable UV flickering is a common property of symbiotic stars. Supporting our physical interpretation of the two X-ray spectral components, simultaneous Swift UV photometry shows that symbiotic stars with harder X-ray emission tend to have stronger UV flickering, which is usually associated with accretion through a disk. To place these new observations in the context of previous work on X-ray emission from symbiotic stars, we modified and extended the alpha/beta/gamma classification scheme for symbiotic-star X-ray spectra that was introduced by Muerset et al. based upon observations with the ROSAT satellite, to include a new sigma classification for sources with hard X-ray emission from the innermost accretion region. Since we have identified the elusive accretion component in the emission from a sample of symbiotic stars, our results have implications for the understanding of wind-fed mass transfer in wide binaries, and the accretion rate in one class of candidate progenitors of type Ia supernovae.

stars↗
DOE OSTI2020

Software classification using phylogenetic techniques

Software, such as malware, may be classified using phylogenetic techniques. An evolutionary history of a representative set of software programs may be reconstructed to generate a reference phylogeny. Dynamic traces of the representative software programs may be obtained. The dynamic traces may include time-ordered sequences of execution commands extracted from running software binaries. Metrics may be developed using the dynamic traces. One or more unknown software programs may then be classified against the reference phylogeny using the metrics developed using the dynamic traces of the representative set of software programs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Creating ground truth for nanocrystal morphology: a fully automated pipeline for unbiased transmission electron microscopy analysis

Control over colloidal nanocrystal morphology (size, size distribution, and shape) is important for tailoring the functionality of individual nanocrystals and their ensemble behavior. Despite this, traditional methods to quantify nanocrystal morphology are laborious. New developments in automated morphology classification will accelerate these analyses but the assessment of machine learning models is limited by human accuracy for ground truth, causing even unsupervised machine learning models to have inherent bias. Herein, we introduce synthetic image rendering to solve the ground truth problem of nanocrystal morphology classification. By simulating 2D images of nanocrystal shapes via a function of high-dimensional parameter space, we trained a convolutional neural network to link unique morphologies to their simulated parameters, defining nanocrystal morphology quantitatively rather than qualitatively. An automated pipeline then processes, quantitatively defines, and classifies nanocrystal morphology from experimental transmission electron microscopy (TEM) images. Using improved computer vision techniques, 42,650 nanocrystals were identified, assessed, and labeled with quantitative parameters, offering a 600-fold improvement in efficiency over best-practice manual measurements. Further, a classification algorithm was trained with a prediction accuracy of 99.5%, which can successfully analyze a range of concave, convex, and irregular nanocrystal shapes. The resulting pipeline was applied to differentiating two syntheses of nominally cuboidal CsPbBr 3 nanocrystals and uniquely classifying binary nickel sulfide nanocrystal phase based on morphology. This pipeline provides a simple, efficient, and unbiased method to quantify nanocrystal morphology and represents a practical route to construct large datasets with an absolute ground truth for training unbiased morphology-based machine learning algorithms.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS1981

X-ray and optical observations of HD 155638 - A remarkably active cool star

X-ray and optical observations of the 8.5-mag star HD 155638 are reported which reveal a remarkably active chromosphere and corona for the star. The object was first observed in soft X-rays with the HEAO 1 A2 low-energy detectors, and later reobserved with the HEAO 2 IPC. X-ray fluxes of about 2 x 10 to the -11th and 3 x 10 to the -12th ergs/sq cm per sec were obtained on the two occasions, indicative of source variability over the 2.5-year period between observations. SIT spectrographs taken in July-August 1980 show evidence of Ca II H and K core emission reversals and filled-in H alpha, while spectra taken in March and July 1981 show evidence of asymmetry and variability in the Ca II reversals. The spectral data are consistent with a G8 IV-V classification, from which is inferred a distance of 35-120 pc, and an X-ray luminosity from 4 x 10 to the 29th to 4 x 10 to the 31st ergs/sec. An absence of emission lines characteristic of mass transfer in binary systems indicates the X-rays to be coronal in origin. The properties of the star are noted to be similar to those of the RS CVn binaries.

Stern, R. A.↗
NASA NTRS1972

The absolute magnitudes and spectral types of the stars in the gamma Velorum system.

The ratio of the visual luminosities of the O and WC components of the binary system gamma (2) Vel has been derived by comparison of the emission-line strengths in the spectrum with those in the spectrum of a single WC8 star, HD 192103. The result is 1.4 mag, with the O star being brighter; the classification of the O star was found to be 09 I, so that the classification of gamma (2) Vel is WC8+09 I.

Conti, P. S.↗
NASA NTRS1994

Low mass companions to nearby stars: Spectral classification and its relation to the stellar/substellar break

The relationship between mass and spectral class for main-sequence stars has never been obtained for dwarfs cooler than M6; currently, the true nature of objects classified as M7, M8, M9, or later (be they stellar or substellar) is not known. In this paper, spectral types for the components in five low mass binary systems are estimated based on previously published infrared speckle measurements, red/infrared photometry, and parallax data, together with newly acquired high signal-to-noise composite spectra of the systems and revised magnitude difference relations for M dwarfs. For two of these binaries, the secondary has a smaller mass (less than 0.09 solar mass) than any object having a dynamically measured mass and a known spectral type, thus extending the spectral class/mass relation to lower masses than has previously been possible. Data from the higher mass components (0.09 solar mass less than M less than 0.40 solar mass) are consistent with earlier results; the two lowest mass objects -- though having mass errors which could place them on either side of the M dwarf/brown dwarf dividing line (Mass is about 0.08 solar mass) -- are found to have spectral types no cooler than M6.5 V. An extrapolation of the updated spectral class/mass relation to the hydrogen-burning limit suggests that objects of type M7 and later may be substellar. Direct confirmation of this awaits the discovery of a close, very late-type binary for which dynamical masses can be measured.

Kirkpatrick, J. Davy↗
NASA NTRS1990

Remote Detection and Mapping of Supergene Iron Oxides in the Cripple Creek Mining District, Colorado

The Geophysical and Environmental Research Imaging Spectrometer (GERIS) was flown over the Cripple Creek mining district in south-central Colorado to improve the geological understanding of the district. As part of the study, an airborne mapping technique was developed for the discrimination of the ferric iron minerals hematite, goethite, and jarosite, minerals often important indicators of the distribution of economic mineralization. A software technique was developed which uses the binary encoding of spectral slopes to identify the mineral hematite from the group goethite/jarosite. Mixtures of hematite and goethite can also be detected with GERIS data. The study included district-wide field mapping and spectral measurements to evaluate the accuracy of the image classifications. The ARC/INFO geographic information system (GIS) was a useful tool which allowed quantitative comparison of the field mapping and GERIS image data sets. The study results demonstrate the ability to discriminate individual iron minerals using imaging spectroscopy, and the development of a rapid mapping technique useful in the reconnaissance stage of minerals exploration.

Taranik, D. L.↗
DOE OSTI2023

Ultracool dwarfs candidates based on 6 yr of the Dark Energy Survey data

ABSTRACT We present a sample of 19 583 ultracool dwarf candidates brighter than z ≤23 selected from the Dark Energy Survey DR2 coadd data matched to VHS DR6, VIKING DR5, and AllWISE covering ∼ 480 deg2. The ultracool candidates were first pre-selected based on their (i–z), (z–Y), and (Y–J) colours. They were further classified using a method that compares their optical, near-infrared, and mid-infrared colours against templates of M, L, and T dwarfs. 14 099 objects are presented as new L and T candidates and the remaining objects are from the literature, including 5342 candidates from our previous work. Using this new and deeper sample of ultracool dwarf candidates we also present: 20 new candidate members to nearby young moving groups and associations, variable candidate sources and four new wide binary systems composed of two ultracool dwarfs. Finally, we also show the spectra of 12 new ultracool dwarfs discovered by our group and presented here for the first time. These spectroscopically confirmed objects are a sanity check of our selection of ultracool dwarfs and photometric classification method.

79 ASTRONOMY AND ASTROPHYSICS↗