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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
NASA NTRS1993

Fourier domain target transformation analysis in the thermal infrared

Remote sensing uses of principal component analysis (PCA) of multispectral images include band selection and optimal color selection for display of information content. PCA has also been used for quantitative determination of mineral types and abundances given end member spectra. The preliminary results of the investigation of target transformation PCA (TTPCA) in the fourier domain to both identify end member spectra in an unknown spectrum, and to then calculate the relative concentrations of these selected end members are presented. Identification of endmember spectra in an unknown sample has previously been performed through bandmatching, expert systems, and binary classifiers. Both bandmatching and expert system techniques require the analyst to select bands or combinations of bands unique to each endmember. Thermal infrared mineral spectra have broad spectral features which vary subtly with composition. This makes identification of unique features difficult. Alternatively, whole spectra can be used in the classification process, in which case there is not need for an expert to identify unique spectra. Use of binary classifiers on whole spectra to identify endmember components has met with some success. These techniques can be used, along with a least squares fit approach on the endmembers identified, to derive compositional information. An alternative to the approach outlined above usese target transformation in conjunction with PCA to both identify and quantify the composition of unknown spectra. Preprocessing of the library and unknown spectra into the fourier domain, and using only a specific number of the components, allows for significant data volume reduction while maintaining a linear relationship in a Beer's Law sense. The approach taken here is to iteratively calculate concentrations, reducing the number of endmember components until only non-negative concentrations remain.

Anderson, D. L.↗
DOE OSTI2015

A new sdO+dM binary with extreme eclipses and reflection effect

We report the discovery of a new totally eclipsing binary (R.A. = 06{sup h}40{sup m}29{sup s}11; decl. = +38°56′52″2; J = 2000.0; R{sub max} = 17.2 mag) with an sdO primary and a strongly irradiated red dwarf companion. It has an orbital period of P{sub orb} = 0.187284394(11) day and an optical eclipse depth in excess of 5 mag. We obtained 2 low-resolution classification spectra with GTC/OSIRIS and 10 medium-resolution spectra with WHT/ISIS to constrain the properties of the binary members. The spectra are dominated by H Balmer and He ii absorption lines from the sdO star, and phase-dependent emission lines from the irradiated companion. A combined spectroscopic and light curve analysis implies a hot subdwarf temperature of T{sub eff}(spec) = 55,000 ± 3000 K, surface gravity of log g (phot) = 6.2 ± 0.04 (cgs), and a He abundance of log(nHe/nH)=−2.24±0.40. The hot sdO star irradiates the red dwarf companion, heating its substellar point to about 22,500 K. Surface parameters for the companion are difficult to constrain from the currently available data: the most remarkable features are the strong H Balmer and C ii-iii lines in emission. Radial velocity estimates are consistent with the sdO+dM classification. The photometric data do not show any indication of sdO pulsations with amplitudes greater than 7 mmag, and Hα-filter images do not provide evidence for the presence of a planetary nebula associated with the sdO star.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1995

Nearly sonic and transsonic convective motions in the solar atmosphere related to the solar wind origin

MHD equations are considered for the solar atmosphere. 15 different simplest MHD regimes are indicated for the momentum transport equation depending on the mutual binary interplay between 6 possible and locally dominant terms: non-stationarity and inhomogeneity of the flow, gas pressure, magnetic tensions, viscous and gravity forces. These regimes are delimited by five physically independent dimensionless parameters, for example, Strouhal, sonic Mach, alfvenic Mach, Reynolds and Froude numbers or their combinations. Another partially overlapping classification of the simplest regimes may be introduced based on the energy conservation equation. There are also 15 independent binary combinations between nonstationary and inhomogeneous convective terms, dissipative energy sinks and sources (viscous, heat-conductive, Joule and radiative ones) in the energy equation. More complicated regimes are considered with multiple dominated terms. All these MHD regimes play their important role somewhere in the solar atmosphere complicated by the tensor transport coefficients in the magnetically dominated regions of the upper atmosphere. Nearly sonic and transsonic nonstationary convective motions with ascending and descending flows are observed in the solar chromosphere. the transition region and the lower pans of the solar corona together with related horizontal velocity components. This convection represents a kind of the 'cocoonery' manufacturing nonstationary vortices generated here and partially connected to the photosphere and to the solar wind. The solar wind originates from this powerful transsonic muddle in the solar atmosphere as a tiny fraction of the streamlines which are temporarily getting detached from the 'cocoons; and going to the infinity. The topologically complicated instantaneous 'runaway surface' around the Sun, i.e., the surface which separates outgoing to the infinity streams from other finite flows in the solar atmosphere was not described in the literature and needs additional investigation. We conclude that a simple one-connected smooth and quasistationary 'critical surface' which is often supposed to be placed somewhere in the solar corona (say, at 4 solar radii) in reality does not exist. Observational and theoretical arguments favor instead of this a highly structured, disordered, patched and time-dependent sonic transition surface in the solar atmosphere permanently fluctuating at positional dependent heights starting sometimes from photospheric (and maybe subphotospheric) levels and more frequently from the chromosphenc network up to several solar radii in the solar corona.

Veselovsky, I. S.↗
DOE OSTI2014

X-ray spectral state evolution in IGR J17091–3624 and comparison of its heartbeat oscillation properties with those of GRS 1915+105

In this work, we study the X-ray timing and spectral evolution of the transient low-mass X-ray binary IGR J17091–3624 during the first 66 days of its 2011 outburst. We present results obtained from observations with two instruments, the Rossi X-ray Timing Explorer Proportional Counter Array and SWIFT X-Ray Telescope, between 2011 February 9 and 2011 April 15. Using quasi-periodic oscillation classifications, power density spectrum characteristics, time-lag behavior, and energy spectral properties, we determine source states and their transitions at different times of the outburst. During the first part of the evolution, the source followed trends that are usually observed from transient black hole X-ray binaries (BHXBs). Interestingly, a gradual transition is observed in IGR J17091–3624 from the low-variability soft intermediate state, commonly seen in BHXBs, to a high-variability state with regular, repetitive, and structured pulsations, seen only from GRS 1915+105 (also known as 'ρ' class variability/'heartbeat' oscillations). We study the time evolution of the characteristic timescale, quality factor, and rms amplitude of heartbeat oscillations in IGR J17091–3624. We also present a detailed comparison of the timing and spectral properties of heartbeat oscillations and their evolution in IGR J17091–3624 and GRS 1915+105.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

TRANSIENT X-RAY SOURCE POPULATION IN THE MAGELLANIC-TYPE GALAXY NGC 55

We present the spectral and temporal properties of 15 candidate transient X-ray sources detected in archival XMM-Newton and Chandra observations of the nearby Magellanic-type, SB(s)m galaxy NGC 55. Based on an X-ray color classification scheme, the majority of the sources may be identified as X-ray binaries (XRBs), and six sources are soft, including a likely supernova remnant. We perform a detailed spectral and variability analysis of the data for two bright candidate XRBs. Both sources displayed strong short-term X-ray variability, and their X-ray spectra and hardness ratios are consistent with those of XRBs. These results, combined with their high X-ray luminosities (∼10{sup 38} erg s{sup −1}), strongly suggest that they are black hole (BH) binaries. Seven less luminous sources have spectral properties consistent with those of neutron star or BH XRBs in both normal and high-rate accretion modes, but one of them is the likely counterpart to a background galaxy (because of positional coincidence). From our spectral analysis, we find that the six soft sources are candidate super soft sources (SSSs) with dominant emission in the soft (0.3–2 keV) X-ray band. Archival Hubble Space Telescope optical images for seven sources are available, and the data suggest that most of them are likely to be high-mass XRBs. Our analysis has revealed the heterogeneous nature of the transient population in NGC 55 (six high-mass XRBs, one low-mass XRBs, six SSSs, one active galactic nucleus), helping establish the similarity of the X-ray properties of this galaxy to those of other Magellanic-type galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Decoding Ethiopian Abodes: Towards Classifying Buildings by Occupancy Type Using Footprint Morphology

Building occupancy classification plays a crucial role in urban planning, disaster management, and population modeling. Traditional methods often require extensive field surveys or detailed datasets, which can be time-consuming, expensive, and may yield incomplete or erroneous data. In this paper, we present a novel approach for classifying buildings as residential or non-residential using only building footprint data. By extracting geometric shape derivatives that characterize building morphology, we developed a high-accuracy classification model employing a combination of unsupervised and supervised learning methods. We utilized open-source data from Open Street Map, aggregating it to create binary labels for buildings based on their respective human use type. Our approach demonstrates the potential for scalability without the need for additional data sources other than building footprints and labels, offering a more efficient solution for building occupancy classification.

Adams, Daniel↗
DOE OSTI2016

MULTI-FILTER LIGHT CURVES OF 29 VERY SHORT PERIOD CANDIDATE CONTACT BINARIES

Light curves of 26 probable contact binary stars are made available, from a list of candidates with the shortest periods known. This is supplemented by sets of light curves of three previously studied systems. Photometry was obtained in the Johnson UBV, Cousins RI system. All stars but one were observed in four wavebands, either UBV R{sub C} or BV(RI){sub C}, depending on brightness. Tentative spectral classifications are given for 23 of the stars. Effective temperatures are derived from infrared and optical photometric indices, and from spectral types. These are generally in good agreement. The multicolor photometry, spectral typing, and estimated effective temperatures can be used to model these systems in detail. A preliminary study, based on Fourier coefficients of the light curves, suggests that all the systems are indeed eclipsing stars, with all but a handful probably in contact configurations.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Identifying and Mapping Agricultural Areas Using Synthetic Aperture Radar Time Series

This study uses Synthetic Aperture Radar (SAR) data to identify active agricultural extent in Mato Grosso, Brazil. Coefficient of variation (CoVar) calculations were applied to year-long time series stacks to identify areas of crop growth. A CoVar threshold value was determined using crop reference layers, then applied to create a crop/non-crop binary map. In the Mato Grosso region, CoVar-based processing resulted in high performance crop classification and allowed for the monitoring of dynamic cropland expansion between 2016 and 2021.

Jordan Bell↗
NASA NTRS1981

Multistage classification of multispectral Earth observational data: The design approach

An algorithm is proposed which predicts the optimal features at every node in a binary tree procedure. The algorithm estimates the probability of error by approximating the area under the likelihood ratio function for two classes and taking into account the number of training samples used in estimating each of these two classes. Some results on feature selection techniques, particularly in the presence of a very limited set of training samples, are presented. Results comparing probabilities of error predicted by the proposed algorithm as a function of dimensionality as compared to experimental observations are shown for aircraft and LANDSAT data. Results are obtained for both real and simulated data. Finally, two binary tree examples which use the algorithm are presented to illustrate the usefulness of the procedure.

Bauer, M. E.↗
NASA NTRS2022

Classifying Unidentified X-Ray Sources in the Chandra Source Catalog Using A Multiwavelength Machine-Learning Approach

The rapid increase in serendipitous X-ray source detections requires the development of novel approaches to efficiently explore the nature of X-ray sources. If even a fraction of these sources could be reliably classified, it would enable population studies for various astrophysical source types on a much larger scale than currently possible. Classification of large numbers of sources from multiple classes characterized by multiple properties (features) must be done automatically and supervised machine learning (ML) seems to provide the only feasible approach. We perform classification of Chandra Source Catalog version 2.0 (CSCv2) sources to explore the potential of the ML approach and identify various biases, limitations, and bottlenecks that present themselves in these kinds of studies. We establish the framework and present a flexible and expandable Python pipeline, which can be used and improved by others. We also release the training data set of 2941 X-ray sources with confidently established classes. In addition to providing probabilistic classifications of 66,369 CSCv2 sources (21% of the entire CSCv2 catalog), we perform several narrower-focused case studies (high-mass X-ray binary candidates and X-ray sources within the extent of the H.E.S.S. TeV sources) to demonstrate some possible applications of our ML approach. We also discuss future possible modifications of the presented pipeline, which are expected to lead to substantial improvements in classification confidences.

Hui Yang↗
DOE OSTI2024

DMTN-221: Periodicity Analysis in Alert Production

The baselined timeseries features to be computed in Alert Production include a Lomb-Scargle periodogram ran on two classes of variable systems: RR Lyrae and Eclipsing Binaries. Based on a simulated LSST-like cadence light curves taken from the Extended LSST Astronomical Time-series Classification Challenge (ELAsTiCC) we perform an end-to-end test to characterize the periodicity recovery on the Alert Production multi-band light curves. In both variable classes, we found that a single-band Lomb-Scargle implementation yields to a low fraction of recovered periods, with a significant preference on the simple periodic phenomena such as RR Lyrae. We also investigated the results from a multi-band Lomb-Scargle and found an increased fraction of recovered periodicities above 15% for the eclipsing binaries, and over 80$\%$ for the RR Lyrae stars. Our findings suggest that a multi-band Lomb-Scargle should be implemented for searching periodic phenomena through AP. We also asses the computational and scientific performance of several configurations on simulated alert data and find that our current configuration scales linearly with the number of detections while assuming an heuristic frequency grid.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Compressing deep neural networks on FPGAs to binary and ternary precision with hls4ml

We present the implementation of binary and ternary neural networks in the hls4ml library, designed to automatically convert deep neural network models to digital circuits with FPGA firmware. Starting from benchmark models trained with floating point precision, we investigate different strategies to reduce the network's resource consumption by reducing the numerical precision of the network parameters to binary or ternary. We discuss the trade-off between model accuracy and resource consumption. In addition, we show how to balance between latency and accuracy by retaining full precision on a selected subset of network components. As an example, we consider two multiclass classification tasks: handwritten digit recognition with the MNIST data set and jet identification with simulated proton-proton collisions at the CERN Large Hadron Collider. The binary and ternary implementation has similar performance to the higher precision implementation while using drastically fewer FPGA resources.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Faint X-ray binaries and their optical counterparts in M31

X-ray binaries (XRBs) are probes of both star formation and stellar mass, but more importantly remain one of the only direct tracers of the compact object population. To investigate the XRB population in M31, we utilized all 121 publicly available observations of M31 totalling over 1 Ms from Chandra's ACIS instrument. We studied 83 star clusters in the bulge using the year 1 star cluster catalogue from the Panchromatic Hubble Andromeda Treasury Survey. We found 15 unique star clusters that matched to 17 X-ray point sources within 1'' (3.8 pc). This population is composed predominantly of globular cluster low-mass XRBs, with one previously unidentified star cluster X-ray source. Star clusters that were brighter and more compact preferentially hosted an X-ray source. Specifically, logistic regression showed that the F475W magnitude was the most important predictor followed by the effective radius, while color (F475W–F814W) was not statistically significant. We also completed a matching analysis of 1566 H II regions and found 10 unique matches to 9 X-ray point sources within 3'' (11 pc). The H II regions hosting X-ray point sources were on average more compact than unmatched H II regions, but logistic regression concluded that neither the radius nor Hα luminosity was a significant predictor. Four matches have no previous classification and thus are high-mass XRB candidates. A stacking analysis of both star clusters and H II regions resulted in non-detections, giving typical upper limits of ≈10{sup 32} erg s{sup –1}, which probes the quiescent XRB regime.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1979

Southern RS CVn systems - Candidate list

A list of 43 candidate RS CVn binary systems in the far southern hemisphere of the sky (south of -40 deg declination) is presented. The candidate systems were selected from the first two volumes of the Michigan Spectral Catalog (1975, 1978), which provides MK classifications for southern HD stars and identifies any unusual characteristics noted for individual stellar spectra. The selection criteria used were: (1) the occurrence of Ca II H and K emission; (2) known or suspected binary nature; (3) regular light variations of zero to one magnitude; and (4) spectral type between F0 and K2 and luminosity less than bright giant (II).

Weiler, E. J.↗
DOE OSTI2025

Scaling laws in jet classification

We demonstrate the emergence of scaling laws in the benchmark top versus QCD jet classification problem in collider physics. Six distinct physically-motivated classifiers exhibit power-law scaling of the binary cross-entropy test loss as a function of training set size, with distinct power law indices. This result highlights the importance of comparing classifiers as a function of dataset size rather than for a fixed training set, as the optimal classifier may change considerably as the dataset is scaled up. We speculate on the interpretation of our results in terms of previous models of scaling laws observed in natural language and image datasets.

Batson, Joshua↗
NASA NTRS1983

The optical counterparts of compact galactic X-ray sources

Ninety-six optical identifications of X-ray sources presumed to be compact objects are presented and discussed. X-ray and optical classifications of the sources are considered, and the several types of systems are discussed. These include neutron star binaries with massive and low-mass stellar components, neutron stars in supernova remnants, cataclysmic variables, and 'isolated' hot white dwarfs. The information that can be derived from optical observations of neutron-star systems with low-mass optical companions is emphasized.

Bradt, H. V. D.↗
NASA NTRS2004

Automated Classification of ROSAT Sources Using Heterogeneous Multiwavelength Source Catalogs

We describe an on-line system for automated classification of X-ray sources, ClassX, and present preliminary results of classification of the three major catalogs of ROSAT sources, RASS BSC, RASS FSC, and WGACAT, into six class categories: stars, white dwarfs, X-ray binaries, galaxies, AGNs, and clusters of galaxies. ClassX is based on a machine learning technology. It represents a system of classifiers, each classifier consisting of a considerable number of oblique decision trees. These trees are built as the classifier is 'trained' to recognize various classes of objects using a training sample of sources of known object types. Each source is characterized by a preselected set of parameters, or attributes; the same set is then used as the classifier conducts classification of sources of unknown identity. The ClassX pipeline features an automatic search for X-ray source counterparts among heterogeneous data sets in on-line data archives using Virtual Observatory protocols; it retrieves from those archives all the attributes required by the selected classifier and inputs them to the classifier. The user input to ClassX is typically a file with target coordinates, optionally complemented with target IDs. The output contains the class name, attributes, and class probabilities for all classified targets. We discuss ways to characterize and assess the classifier quality and performance and present the respective validation procedures. Based on both internal and external validation, we conclude that the ClassX classifiers yield reasonable and reliable classifications for ROSAT sources and have the potential to broaden class representation significantly for rare object types.

McGlynn, Thomas↗
NASA NTRS1993

Classifying multispectral data by neural networks

Several energy functions for synthesizing neural networks are tested on 2-D synthetic data and on Landsat-4 Thematic Mapper data. These new energy functions, designed specifically for minimizing misclassification error, in some cases yield significant improvements in classification accuracy over the standard least mean squares energy function. In addition to operating on networks with one output unit per class, a new energy function is tested for binary encoded outputs, which result in smaller network sizes. The Thematic Mapper data (four bands were used) is classified on a single pixel basis, to provide a starting benchmark against which further improvements will be measured. Improvements are underway to make use of both subpixel and superpixel (i.e. contextual or neighborhood) information in tile processing. For single pixel classification, the best neural network result is 78.7 percent, compared with 71.7 percent for a classical nearest neighbor classifier. The 78.7 percent result also improves on several earlier neural network results on this data.

Telfer, Brian A.↗