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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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At least 181 records · Page 10

Scattering characteristics of Martin Black at 118 microns

BRDF (bidirectional reflectance distribution function) values for 0.000118 m radiation at different angles of incidence and different scattering angles from the Infrared Astronomical Satellite telescope baffle coated with Martin Black are presented. Data from scatterometer experiments are collected and the BRDF and beta - beta sub 0 (sin theta sub s - sin theta sub 0) values are calculated based on the geometry, the voltage readings, the attenuators in the beam, and the calculated reference levels. A composite curve of forward and backward scattering data for several angles of incidence shows a peak near the specular direction (beta - beta sub 0 = 0), which is the instrument profile reduced by the 20% specular reflection of the Martin Black. The nonspecular part of the reflectivity indicates the slightly specular but largely Lambertian character of the coating. Data for the specular reflectivity as a function of the incidence angle unexpectedly shows a decrease in the specular reflectance with increasing angle of incidence.

Brooks, L. D.↗

AI in Astrophysics: Tackling Domain Shift, Model Robustness and Uncertainty

Artificial Intelligence (AI) is revolutionizing physics research from probing the large-scale structure of the Universe to modeling subatomic interactions and fundamental forces. Yet, a major challenge persists: AI models trained on simulations or old experiment / astronomical survey often perform poorly when applied to new data exposing issues of dataset (domain) shift, model robustness, and uncertainty in predictions. This talk will introduce common challenges in applying AI across domains and present solutions based on domain adaptation a set of techniques designed to improve model generalization under domain shift. We will cover foundational ideas, practical strategies, and current research frontiers in this area. Through examples in astrophysics, we'll explore how domain adaptation can help bridge the gap between synthetic and real-world data, improve trust in model outputs, and advance scientific discovery.

Ciprijanvoic, Aleksandra [Fermilab] (ORCID:0000000↗

A Template-based Approach to the Photometric Classification of SN 1991bg-like Supernovae in the SDSS-II Supernova Survey

The use of SNe Ia to measure cosmological parameters has grown significantly over the past two decades. However, there exists a significant diversity in the SN Ia population that is not well understood. Overluminous SN 1991T-like and subluminous SN 1991bg-like objects are two characteristic examples of peculiar SNe. The identification and classification of such objects is an important step in studying what makes them unique from the remaining SN population. With the upcoming Vera C. Rubin Observatory promising on the order of a million new SNe over a 10 year survey, spectroscopic classifications will be possible for only a small subset of observed targets. As such, photometric classification has become an increasingly important concern in preparing for the next generation of astronomical surveys. Using observations from the Sloan Digital Sky Survey II (SDSS-II) SN Survey, we apply here an empirically based classification technique targeted at the identification of SN 1991bg-like SNe in photometric data sets. By performing dedicated fits to photometric data in the rest-frame redder and bluer bandpasses, we classify 16 previously unidentified 91bg-like SNe. Using SDSS-II host galaxy measurements, we find that these SNe are preferentially found in host galaxies with an older average stellar age than the hosts of normal SNe Ia. We also find that these SNe are found at a further physical distance from the center of their host galaxies. We find no statistically significant bias in host galaxy mass or specific star formation rate for these targets.

Astronomy & Astrophysics↗

Digital array scanned interferometers for astronomy

Investigations are reported of digital array scanned interferometers (DASI) with silicon CCD array detectors to define the operational capabilities of a mapping (polarimetric) spectrometer for astronomical applications based on these instruments. For spectral mapping, spatially resolved spectra using a cylindrical lens to image in the interferometers's redundant coordinate are given. The signal-to-noise characteristics of the Fourier transformed data are demonstrated with regard to the effects of a rectangular sampling function, spectral multiplexing and the pixel-to-pixel variation of the CCD array. These data indicate that DASIs can offer simple, versatile (polarization) mapping spectrometers suitable for spectral mapping observations from the ultraviolet to the infrared of extended sources at variable spatial resolution, particularly where long term stable operation is essential, as for spacecraft instruments.

Smith, Wm. Hayden↗

Giant Molecular Clouds and High-Mass Star Formation in the Milky Way

We are conducting an extensive investigation of high-mass (OB) star formation within the dense cores of giant molecular clouds (GMCS) throughout the first Galactic quadrant of the Milky Way using enhanced resolution Infrared Astronomical Satellite (IRAS) images in combination with high-resolution ground-based observations in millimeter wave molecular transitions and radio continuum. As part of this investigation several resolution enhancement algorithms are applied to the IRAS data, including the HIgh RESolution (HIRES) algorithm developed at the IRAS Processing and Analysis Center (IPAC), as well as others ("pixon" image reconstruction). In addition, as part of a related study, we have completed a large survey of the CO emission in the first Galactic quadrant using the 15-element array detector (QUARRY) with the Five College Radio Astronomy Observatory (FCRAO) 14 m antenna, which provides sampling at an angular resolution of 50", comparable to that attained in the reprocessed IRAS data. Both of these data sets are compared with a sample of ultra-compact (UC) H II regions taken from a high-resolution multi-wavelength (6 and 20 cm) radio survey of the Galactic plane using the NRAO Very Large Array (VLA). Selected regions are observed in 1.3 mm continuum, which has proven to be particularly sensitive to the dust column density. Extensive observations of molecular clouds at high resolution in CO, CS and HCN are combined with the reprocessed IRAS high-resolution images to give a more complete picture of the physical conditions and kinematics of high-mass star forming GMCS. Our goals are to study in detail the morphology, structure, and rate of high-mass star formation within GMCs throughout the Galactic disk from the inner edge of the molecular ring to the outer Galaxy.

Source record↗

Automatic Detection and Classification of Radio Galaxy Images by Deep Learning

Abstract Surveys conducted by radio astronomy observatories, such as SKA, MeerKAT, Very Large Array, and ASKAP, have generated massive astronomical images containing radio galaxies (RGs). This generation of massive RG images has imposed strict requirements on the detection and classification of RGs and makes manual classification and detection increasingly difficult, even impossible. Rapid classification and detection of images of different types of RGs help astronomers make full use of the observed astronomical image data for further processing and analysis. The classification of FRI and FRII is relatively easy, and there are more studies and literature on them at present, but FR0 and FRI are similar, so it is difficult to distinguish them. It poses a greater challenge to image processing. At present, deep learning has made breakthrough progress in the field of image analysis and processing and has preliminary applications in astronomical data processing. Compared with classification algorithms that can only classify galaxies, object detection algorithms that can locate and classify RGs simultaneously are preferred. In target detection algorithms, YOLOv5 has outstanding advantages in the classification and positioning of small targets. Therefore, we propose a deep-learning method based on an improved YOLOv5 object detection model that makes full use of multisource data, combining FIRST radio with SDSS optical image data, and realizes the automatic detection of FR0, FRI, and FRII RGs. The innovation of our work is that on the basis of the original YOLOv5 object detection model, we introduce the SE Net attention mechanism, increase the number of preset anchors, adjust the network structure of the feature pyramid, and modify the network structure, thereby allowing our model to demonstrate galaxy classification and position detection effects. Our improved model produces satisfactory results, as evidenced by experiments. Overall, the mean average precision (mAP@0.5) of our improved model on the test set reaches 89.4%, which can determine the position (R.A. and decl.) and automatically detect and classify FR0s, FRIs, and FRIIs. Our work contributes to astronomy because it allows astronomers to locate FR0, FRI, and FRII galaxies in a relatively short time and can be further combined with other astronomically generated data to study the properties of these galaxies. The target detection model can also help astronomers find FR0s, FRIs, and FRIIs in future surveys and build a large-scale star RG catalog. Moreover, our work is also useful for the detection of other types of galaxies.

Astronomy & Astrophysics↗

Celescope catalog of ultraviolet stellar observations

The catalog contains the observational results obtained by the Celescope Experiment during the first 16 months of operation of NASA's Orbiting Astronomical Observatory (OAO-2). It lists the results of the stellar observations, along with selected ground-based information obtained from the available literature. Lunar observations (Ahmad and Deutschman, 1972), as well as other analyses of the data, are being published as separate papers. These data are available in two forms: (1) magnetic tapes and the necessary utility programs for reading and printing the contents of the tapes; and (2) this catalog, transcribed from the magnetic-tape catalog. The magnetic tape version contains not only the compiled results but also the results of the individual observations from which these averaged data were compiled.

Davis, R. J.↗

Distribution of astronomical sources in the second Equatorial Infrared Catalogue

Measurements of infrared (2.7-micron) source positions and flux densities have been derived based on an additional 60.6 hours of satellite observations beyond those considered in the preparation of the Equatorial Infrared Catalogue No. 1 (EIC-1). These data have been processed together with the EIC-1 data to produce EIC-2. The new catalog differs from EIC-1 as follows: there are 1278 sources; there is a larger percentage of unidentified sources; there are increased numbers of sources identified with Two-Micron Sky Survey sources, AFGL sources, AGK3 stars and SAO stars.

Nagy, T. A.↗

The evolution of adopted values for precession

The history of astronomical longitude precession determination is reviewed. Consideration is given to the work of Hipparchus and Ptolemy, the definition of rotation axes, the major 19th-century determinations, and 20th-century studies (using the data of Newcomb; based on PGC, GC, and McCormick/Cape catalogs; using FK3, FK4, and AGK3; involving galaxies; and using the dynamical method). Laser ranging and VLBI are seen as the most promising techniques for future precession measurements. Diagrams, graphs, and tables of numerical data are provided.

Lieske, J. H.↗

Solar-A Prelaunch Mission Operation Report (MOR)

The Solar-A mission is a Japanese-led program with the participation of the United States and the United Kingdom. The Japanese Institute of Space and Astronautical Science (ISAS) is providing the Solar-A spacecraft, two of the four science instruments, the launch vehicle and launch support, and the principal ground station with Operational Control Center. NASA is providing a science instrument, the Soft X-ray Telescope (SXT)and tracking support using the Deep Space Network (DSN) ground stations. The United Kingdom s Science and Engineering Research Council (SERC) provides the Bragg Crystal Spectrometer. The Solar-A mission will study solar flares using a cluster of instruments on a satellite in a 600 km altitude, 31 degree inclination circular orbit. The emphasis of the mission is on imaging and spectroscopy of hard and soft X-rays. The principal instruments are a pair of X-ray imaging instruments, one for the hard X-ray range and one for the soft X-ray range. The Hard X-Ray Telescope (HXT), provided by ISAS, operates in the energy range of 10-100 keV and uses an array of modulation collimators to record Fourier transform images of the non-thermal and hot plasmas that are formed during the early phases of a flare. These images are thought to be intimately associated with the sites of primary energy release. The Soft X-Ray Telescope (SXT), jointly provided by NASA and ISAS, operates in the wavelength range of 3-50 Angstroms and uses a grazing incidence mirror to form direct images of the lower temperature (but still very hot) plasmas that form as the solar atmosphere responds to the injection of energy. The SXT instrument is a joint development effort between the Lockheed Palo Alto Research Laboratory and the National Astronomical Observatory of Japan. The U.S. effort also involves Stanford University, the University of California at Berkeley and the University of Hawaii, who provide support in the areas of theory, data analysis and interpretation, and ground-based observations. The hard and soft X-ray telescopes both have an alignment sensor, operating in the visual region of the spectrum, to provide co-alignment information.

Source record↗

Application of the SIT vidicon to astronomical measurements.

Review of the results of a detailed investigation of the properties and merits of silicon target (SIT) vidicon photometry, compared to previous photoelectric and photographic photometry, in astronomy applications. Following a description of the SIT-vidicon based photometry system and of its operating procedures, the data reduction methods are examined, and some of the results obtained are discussed.

Westphal, J. A.↗

Imagery with a Si:Bi 16 x 16 array

A description of the design and performance of an imaging spectrometer intended for operation in the 7 to 14 micron wavelength range is presented. It is based upon a 16 by 16 element Si:Bi hybrid array, a circular variable filter wheel, and a microcomputer data acquisition system. The spatial-spectral photometric performances were evaluated in the laboratory as well as field tested at astronomical observatories. The performance characteristics of the system are presented as well as laboratory and astronomical images.

Goebel, J. H.↗

Instrument Remote Control via the Astronomical Instrument Markup Language

The Instrument Remote Control (IRC) project ongoing at NASA's Goddard Space Flight Center's (GSFC) Information Systems Center (ISC) supports NASA's mission by defining an adaptive intranet-based framework that provides robust interactive and distributed control and monitoring of remote instruments. An astronomical IRC architecture that combines the platform-independent processing capabilities of Java with the power of Extensible Markup Language (XML) to express hierarchical data in an equally platform-independent, as well as human readable manner, has been developed. This architecture is implemented using a variety of XML support tools and Application Programming Interfaces (API) written in Java. IRC will enable trusted astronomers from around the world to easily access infrared instruments (e.g., telescopes, cameras, and spectrometers) located in remote, inhospitable environments, such as the South Pole, a high Chilean mountaintop, or an airborne observatory aboard a Boeing 747. Using IRC's frameworks, an astronomer or other scientist can easily define the type of onboard instrument, control the instrument remotely, and return monitoring data all through the intranet. The Astronomical Instrument Markup Language (AIML) is the first implementation of the more general Instrument Markup Language (IML). The key aspects of our approach to instrument description and control applies to many domains, from medical instruments to machine assembly lines. The concepts behind AIML apply equally well to the description and control of instruments in general. IRC enables us to apply our techniques to several instruments, preferably from different observatories.

Sall, Ken↗

Scalable and Energy-Efficient Methods for Interactive Exploration of Scientific Data

The main scientific contributions of this project are the following novel concepts for multidimensional arrays: shape-based similarity join (SIGMOD 2016), incremental view maintenance (SIGMOD 2017), user-defined stencil functions (HPDC 2017), and distributed caching for in-situ processing (SSDBM 2018). Building on our collaboration with the astrophysics group at LBNL, we applied these techniques to the data generated in the Palomar Transient Factory (PTF) astronomical survey. They played a pivotal role in the first-ever observation of a neutron star merger, which produces gravitational waves and turns out to be the origin of heavy elements, including gold. This has lead to a Science magazine article that has received extensive media coverage on ACM TechNews, Slashdot, FiveThirtyEight, and Quanta Magazine, among others. Additionally, two other articles detailing related aspects of the same discovery have been published in the Astrophysical Journal Letters journal. These publications have more than 3,000 citations according to Google Scholar (as of February 2022). This cross-disciplinary collaboration provided very good opportunities to apply database techniques to real-life scientific problems. The fact that they facilitated major discoveries in astrophysics proves the importance of our research. In addition to the work on multidimensional array databases, this project has also developed stochastic gradient descent (SGD) optimization algorithms for training large scale machine learning models, methods for querying in-situ data, and a database query optimizer based on sketch synopses.

79 ASTRONOMY AND ASTROPHYSICS↗

Automatic Search of Cataclysmic Variables Based on LightGBM in LAMOST-DR7

The search for special and rare celestial objects has always played an important role in astronomy. Cataclysmic Variables (CVs) are special and rare binary systems with accretion disks. Most CVs are in the quiescent period, and their spectra have the emission lines of Balmer series, HeI, and HeII. A few CVs in the outburst period have the absorption lines of Balmer series. Owing to the scarcity of numbers, expanding the spectral data of CVs is of positive significance for studying the formation of accretion disks and the evolution of binary star system models. At present, the research for astronomical spectra has entered the era of Big Data. The Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST) has produced more than tens of millions of spectral data. the latest released LAMOST-DR7 includes 10.6 million low-resolution spectral data in 4926 sky regions, providing ideal data support for searching CV candidates. To process and analyze the massive amounts of spectral data, this study employed the Light Gradient Boosting Machine (LightGBM) algorithm, which is based on the ensemble tree model to automatically conduct the search in LAMOST-DR7. Finally, 225 CV candidates were found and four new CV candidates were verified by SIMBAD and published catalogs. This study also built the Gradient Boosting Decision Tree (GBDT), Adaptive Boosting (AdaBoost), and eXtreme Gradient Boosting (XGBoost) models and used Accuracy, Precision, Recall, the F1-score, and the ROC curve to compare the four models comprehensively. Experimental results showed that LightGBM is more efficient. The search for CVs based on LightGBM not only enriches the existing CV spectral library, but also provides a reference for the data mining of other rare celestial objects in massive spectral data.

79 ASTRONOMY AND ASTROPHYSICS↗

Shift Happens: Building Robust AI Models with Domain Adaptation

Artificial Intelligence (AI) is revolutionizing physics research—from probing the large-scale structure of the Universe to modeling subatomic interactions and fundamental forces. Yet, a major challenge persists: AI models trained on simulations or old experiment / astronomical survey often perform poorly when applied to new data—exposing issues of dataset (domain) shift, model robustness, and uncertainty in predictions. This summer school session will introduce students to common challenges in applying AI across domains and present solutions based on domain adaptation—a set of techniques designed to improve model generalization under domain shift. We will cover foundational ideas, practical strategies, and current research frontiers in this area. Through examples in astrophysics, we'll explore how domain adaptation can help bridge the gap between synthetic and real-world data, improve trust in model outputs, and advance scientific discovery. The concepts discussed are broadly applicable across physics and other scientific disciplines, making this a valuable topic for anyone interested in building robust, transferable AI models for science.

Ciprijanovic, A. [Fermilab] (ORCID:000000031281719↗

Photometric imaging near infrared spectrometer

A description of the design and performance of an imaging spectrometer intended for operation in the seven to fourteen micrometer wavelength range is presented. It is based upon a sixteen by sixteen element Si:Bi hybrid array, a circular variable filter wheel, and a microcomputer data acquisition system. The spatial-spectral photometric performances have been evaluated in the laboratory as well as field tested at astronomical observatories. The performance characteristics of the system are presented as well as laboratory and astronomical images.

Goebel, J. H.↗

Development of a data reduction expert assistant

This report documents the development and deployment of the Data Reduction Expert Assistant (DRACO). The system was successfully applied to two astronomical research projects. The first was the removal of cosmic ray artifacts from Hubble Space Telescope (HST) Wide Field Planetary Camera data. The second was the reduction and calibration of low-dispersion CCD spectra taken from a ground-based telescope. This has validated our basic approach and demonstrated the applicability of this technology. This work has been made available to the scientific community in two ways. First, we have published the work in the scientific literature and presented papers at relevant conferences. Secondly, we have made the entire system (including documentation and source code) available to the community via the World Wide Web.

Miller, Glenn E.↗