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At least 55 records · Page 3

Parallelization and Algorithmic Enhancements of High Resolution IRAS Image Construction

The Infrared Astronomical Satellite caried out a nearly complete survey of the infrared sky, and the survey data are important for the study of many astrophysical phenomena. However, many data sets at other wavelengths have higher resolutions than that of the co-added IRAS maps, and high resolution IRAS images are strongly desired both for their own information content and their usefulness in correlation. The HIRES program was developed by the Infrared Processing and Analysis Center (IPAC) to produce high resolution (approx. 1') images from IRAS data using the Maximum Correlation Method (MCM). We describe the port of HIRES to the Intel Paragon, a massively parallel supercomputer, other software developments for mass production of HIRES images, and the IRAS Galaxy Atlas, a project to map the Galactic plane at 60 and 100(micro)m.

Satellite infrared IRAS IRAS maps IRAS images↗

Data fusion with artificial neural networks (ANN) for classification of earth surface from microwave satellite measurements

A data fusion system with artificial neural networks (ANN) is used for fast and accurate classification of five earth surface conditions and surface changes, based on seven SSMI multichannel microwave satellite measurements. The measurements include brightness temperatures at 19, 22, 37, and 85 GHz at both H and V polarizations (only V at 22 GHz). The seven channel measurements are processed through a convolution computation such that all measurements are located at same grid. Five surface classes including non-scattering surface, precipitation over land, over ocean, snow, and desert are identified from ground-truth observations. The system processes sensory data in three consecutive phases: (1) pre-processing to extract feature vectors and enhance separability among detected classes; (2) preliminary classification of Earth surface patterns using two separate and parallely acting classifiers: back-propagation neural network and binary decision tree classifiers; and (3) data fusion of results from preliminary classifiers to obtain the optimal performance in overall classification. Both the binary decision tree classifier and the fusion processing centers are implemented by neural network architectures. The fusion system configuration is a hierarchical neural network architecture, in which each functional neural net will handle different processing phases in a pipelined fashion. There is a total of around 13,500 samples for this analysis, of which 4 percent are used as the training set and 96 percent as the testing set. After training, this classification system is able to bring up the detection accuracy to 94 percent compared with 88 percent for back-propagation artificial neural networks and 80 percent for binary decision tree classifiers. The neural network data fusion classification is currently under progress to be integrated in an image processing system at NOAA and to be implemented in a prototype of a massively parallel and dynamically reconfigurable Modular Neural Ring (MNR).

Lure, Y. M. Fleming↗

An Innovative Infrastructure with a Universal Geo-Spatiotemporal Data Representation Supporting Cost-Effective Integration of Diverse Earth Science Data

The SpatioTemporal Adaptive Resolution Encoding (STARE) is a unifying scheme encoding geospatial and temporal information for organizing data on scalable computing/storage resources, minimizing expensive data transfers. STARE provides a compact representation that turns set-logic functions into integer operations, e.g. conditional sub-setting, taking into account representative spatiotemporal resolutions of the data in the datasets. STARE geo-spatiotemporally aligns data placements of diverse data on massive parallel resources to maximize performance. Automating important scientific functions (e.g. regridding) and computational functions (e.g. data placement) allows scientists to focus on domain-specific questions instead of expending their efforts and expertise on data processing. With STARE-enabled automation, SciDB (Scientific Database) plus STARE provides a database interface, reducing costly data preparation, increasing the volume and variety of interoperable data, and easing result sharing. Using SciDB plus STARE as part of an integrated analysis infrastructure dramatically eases combining diametrically different datasets.

Rilee, Michael Lee↗

Venus volcanism - Initial analysis from Magellan data

Magellan images confirm that volcanism is widespread and has been fundamentally important in the formation and evolution of the crust of Venus. High-resolution imaging data reveal evidence for intrusion (dike formation and cryptodomes) and extrusion (a wide range of lava flows). Also observed are thousands of small shield volcanoes, larger edifices up to several hundred kilometers in diameter, massive outpourings of lavas, and local pyroclastic deposits. Although most features are consistent with basaltic compositions, a number of large pancake-like domes are morphologically similar to rhyolite-dacite domes on earth. Flows and sinuous channels with lengths of many hundreds of kilometers suggest that extremely high effusion rates or very fluid magmas (perhaps komantiites) may be present. Volcanism is evident in various tectonic settings (coronae, linear extensional and compressional zones, mountain belts, upland rises, highland plateaus, and tesserae). Volcanic resurfacing rates appear to be low (less than 2 cu km/yr) but the significance of dike formation and intrusions, and the mode of crustal formation and loss remain to be established.

Head, James W.↗

The X-ray spectrum of Abell 665

The X-ray spectrum of the Abell 665 cluster of galaxies has been determined by the Ginga satellite. The spectrum can be well fitted by an isothermal model with kT = 8.26(+0.95; -0.81) keV and metal abundance 0.49 +/- 0.16. Joint analysis with lower energy spectral data from the Einstein Observatory is used to constrain the temperature distribution in the cluster. For a particular form of the polytropic temperature model we find the best fit to be the isothermal case, and we set an upper limit on the polytropic index of 1.35 (99-percent confidence). The virial mass of the cluster has been determined from both the X-ray data and the galaxy velocity dispersion. The mass estimates from the optical and X-ray analyses are fully consistent with each other. Abell 665 is found to be 0.82(+0.41; -0.26) times as massive as Coma if the two clusters are assumed to have the same spatial distribution of virial mass.

Hughes, John P.↗

Tests of a simple data merging algorithm for the GONG project

The GONG (Global Oscillation Network Group) project proposes to reduce the impact of diurnal variations on helioseismic measurements by making long-term observations of solar images from six sites placed around the globe. The sun will be observed nearly constantly for three years, resulting in the acquisition of l+ terabyte of image data. To use the solar network to maximum advantage, the images from the sites must be combined into a single time series to determine mode frequencies, amplitudes, and line widths. Initial versions of combined, i.e., merged, time series were made using a simple weighted average of data from different sites taken simultaneously. In order to accurately assess the impact of the data merge on the helioseismic measurements, a set of artificial solar disk images was made using a standard solar model and containing a well known set of oscillation modes and frequencies. This undegraded data set and data products computed from it were used to judge the relative merits of various data merging schemes. The artificial solar disk images were subjected to various instrumental and atmospheric degradations, dependent on site and time, in order to create a set of images simulating those likely to be taken at the site. The degraded artificial solar disk images for the six observing sites were combined in various ways to form merged time series of images and mode coefficients. Various forms of a weighted average were used, including an equally-weighted average, an average with weights dependent upon air mass and averages with weights dependent on various quality assurance parameters. Both the undegraded solar disk image time series and several time series made up of various combinations of the degraded solar disk images from the six sites were subjected to standard helioseismic measurement processing. This processing consisted of coordinate remapping, detrending, spherical harmonic transformation, computation of power series for the oscillation mode coefficients, and mode frequency identification. Visual and statistical evaluation of the merged data sets themselves and differences between the merged and undegraded data set shows good agreement between the two data sets. Some slight differences in image scale and registration appear between the undegraded data set and the various merged data sets. In the set of power series made from the mode coefficients of the merged data sets, some power leakage is observed into the background and into slightly lower l-value modes, especially at higher l-value mode frequencies. The results of the comparison of time series and mode oscillation frequencies of the undegraded data with those of the data merged using weighted averages indicate that, at least for p-mode solar oscillations, a weighted average of either the detrended remapped images or the mode coefficients gives good determination of the mode frequencies and adequate-to-good determination of the amplitudes and widths of the mode frequency lines. This conclusion is most advantageous to the analysis of the massive amounts of data to be received by the GONG network.

Williams, W. E.↗

GC31G-1182: Opennex, a Private-Public Partnership in Support of the National Climate Assessment

The NASA Earth Exchange (NEX) is a collaborative computing platform that has been developed with the objective of bringing scientists together with the software tools, massive global datasets, and supercomputing resources necessary to accelerate research in Earth systems science and global change. NEX is funded as an enabling tool for sustaining the national climate assessment. Over the past five years, researchers have used the NEX platform and produced a number of data sets highly relevant to the National Climate Assessment. These include high-resolution climate projections using different downscaling techniques and trends in historical climate from satellite data. To enable a broader community in exploiting the above datasets, the NEX team partnered with public cloud providers to create the OpenNEX platform. OpenNEX provides ready access to NEX data holdings on a number of public cloud platforms along with pertinent analysis tools and workflows in the form of Machine Images and Docker Containers, lectures and tutorials by experts. We will showcase some of the applications of OpenNEX data and tools by the community on Amazon Web Services, Google Cloud and the NEX Sandbox.

datasets↗

A Search for Supernova in Star-Burst Galaxies

The rate at which massive supernovae occur in galaxies can be related directly to the rate of formation of massive stars this rate in turn can be computed from measurements and theoretical models of stellar mss distributions. Other measurements such as chemical composition and the dynamical structure of galaxies can also be used to infer the rate of massive supernovae. Various lines of reasoning using these measurements and theories of star formation have predicted a supernova rate which might be as much as ten times the rate of supernovae that had been observed using optical telescopes. The unseen supernovae were thought to be undetected due to a variety of circumstances, with the primary problem being extinction imposed by dust along the line of observation. This research used new infrared observations of the Infrared Space Observatory (ISO) space craft to explore active galaxies with a technique unhindered by dust extinction. New image processing algorithms for ISO point source analysis and cosmic ray deglitching were developed in order to search through a fairly complete set of the ISO data.

Rank, David M.↗

L-PBF High-Throughput Data Pipeline Approach for Multi-modal Integration

Abstract Metal-based additive manufacturing requires active monitoring solutions for assessing part quality. Multiple sensors and data streams, however, generate large heterogeneous data sets that are impractical for manual assessment and characterization. In this work, an automated pipeline is developed that enables feature extraction from high-speed camera video and multi-modal data analysis. The framework removes the need for manual assessment through the utilization of deep learning techniques and training models in a weakly supervised paradigm. We demonstrate this pipeline’s capability over 700,000 high-speed camera frames. The pipeline successfully extracts melt pool and spatter geometries and links them to corresponding pyrometry, radiography, and processparameter information. 715 individual prints are examined to reveal melt pool areas that exceeds 0.07 mm 2 and pyrometry signal over a threshold (375 pyrometry units) were more likely to have defects. These automated processes enable massive throughput of characterization techniques.

36 MATERIALS SCIENCE↗

Antiproton bounds on dark matter annihilation from a combined analysis using the DRAGON2 code

Abstract Early studies of the AMS-02 antiproton ratio identified a possible excess over the expected astrophysical background that could be fit by the annihilation of a weakly interacting massive particle (WIMP). However, recent efforts have shown that uncertainties in cosmic-ray propagation, the antiproton production cross-section, and correlated systematic uncertainties in the AMS-02 data, may combine to decrease or eliminate the significance of this feature. We produce an advanced analysis using the DRAGON2 code which, for the first time, simultaneously fits the antiproton ratio along with multiple secondary cosmic-ray flux measurements to constrain astrophysical and nuclear uncertainties. Compared to previous work, our analysis benefits from a combination of: (1) recently released AMS-02 antiproton data, (2) updated nuclear fragmentation cross-section fits, (3) a rigorous Bayesian parameter space scan that constrains cosmic-ray propagation parameters.We find no statistically significant preference for a dark matter signal and set strong constraints on WIMP annihilation tobb̅, ruling out annihilation at the thermal cross-section for dark matter masses below ∼ 200 GeV. We do find a positive residual that is consistent with previous work, and can be explained by a ∼ 70 GeV WIMP annihilating below the thermal cross-section. However, our default analysis finds this excess to have a local significance of only 2.8σ, which is decreased to 1.8σwhen the look-elsewhere effect is taken into account.

Astronomy & Astrophysics↗

Software Development to Assist in the Processing and Analysis of Data Obtained Using Fiber Bragg Grating Interrogation Systems

A fiber Bragg grating is a portion of a core of a fiber optic strand that has been treated to affect the way light travels through the strand. Light within a certain narrow range of wavelengths will be reflected along the fiber by the grating, while light outside that range will pass through the grating mostly undisturbed. Since the range of wavelengths that can penetrate the grating depends on the grating itself as well as temperature and mechanical strain, fiber Bragg gratings can be used as temperature and strain sensors. This capability, along with the light-weight nature of the fiber optic strands in which the gratings reside, make fiber optic sensors an ideal candidate for flight testing and monitoring in which temperature and wing strain are factors. The purpose of this project is to research the availability of software capable of processing massive amounts of data in both real-time and post-flight settings, and to produce software segments that can be integrated to assist in the task as well.

Hicks, Rebecca↗

Image segmentation by iterative parallel region growing and splitting

The spatially constrained clustering (SCC) iterative parallel region-growing technique is applied to image analysis. The SCC algorithm is implemented on the massively parallel processor at NASA Goddard. Most previous region-growing approaches have the drawback that the segmentation produced depends on the order in which portions of the image are processed. The ideal solution to this problem (merging only the single most similar pair of spatially adjacent regions in the image in each iteration) becomes impractical except for very small images, even on a massively parallel computer. The SCC algorithm overcomes these problems by performing, in parallel, the best merge within each of a set of local, possibly overlapping, subimages. A region-splitting stage is also incorporated into the algorithm, but experiments show that region splitting generally does not improve segmentation results. The SCC algorithm has been tested on various imagery data, and test results for a Landsat TM image are summarized.

Tilton, James C.↗

A distributed analysis and visualization system for model and observational data

The objective of this proposal is to develop an integrated and distributed analysis and display software system which can be applied to all areas of the Earth System Science to study numerical model and earth observational data from storm to global scale. This system will be designed to be easy to use, portable, flexible and easily extensible and to adhere to current and emerging standards whenever possible. It will provide an environment for visualization of the massive amounts of data generated from satellites and other observational field measurements and from model simulations during or after their execution. Two- and three-dimensional animation will also be provided. This system will be based on a widely used software package from NASA called GEMPAK and prototype software for three dimensional interactive displays built at NCSA. The underlying foundation of the system will be a set of software libraries which can be distributed across a UNIX based supercomputer and workstations.

Wilhelmson, Robert↗

A distributed analysis and visualization system for model and observational data

The objective of this proposal is to develop an integrated and distributed analysis and display software system which can be applied to all areas of the Earth System Science to study numerical model and earth observational data from storm to global scale. This system will be designed to be easy to use, portable, flexible and easily extensible and designed to adhere to current and emerging standards whenever possible. It will provide an environment for visualization of the massive amounts of data generated from satellites and other observational field measurements and from model simulations during or after their execution. Two- and three-dimensional animation will also be provided. This system will be based on a widely used software package from NASA called GEMPAK and prototype software for three-dimensional interactive displays built at NCSA. The underlying foundation of the system will be a set of software libraries which can be distributed across a UNIX based supercomputer and workstations.

Wilhelmson, Robert↗

Observation of 𝑊⁢𝑍⁢𝛾 production and constraints on new physics scenarios in proton-proton collisions at $\sqrt{s}$ =13 TeV

A measurement of the 𝑊⁢𝑍⁢𝛾 triboson production cross section is presented. The analysis is based on a data sample of proton-proton collisions at a center-of-mass energy of $\sqrt{s}$ =13 TeV recorded with the CMS detector at the LHC, corresponding to an integrated luminosity of 138 fb −1 . The analysis focuses on the final state with three charged leptons, ℓ ± ⁢𝜈⁢ℓ + ⁢ℓ − , where ℓ = 𝑒 or 𝜇, accompanied by an additional photon. The observed (expected) significance of the 𝑊⁢𝑍⁢𝛾 signal is 5.4 (3.8) standard deviations. The cross section is measured in a fiducial region, where events with an ℓ originating from a tau lepton decay are excluded, to be 5.48 ± 1.11 fb, which is compatible with the prediction of 3.69 ± 0.24 fb at next-to-leading order in quantum chromodynamics. Exclusion limits are set on anomalous quartic gauge couplings and on the production cross sections of massive axionlike particles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The High-Energy Emission from HD 93129A Near Periastron

We conducted an observational campaign towards one of the most massive and luminous colliding wind binaries in the Galaxy, HD 93129A, close to its periastron passage in 2018. During this time the source was predicted to be in its maximum of high-energy emission. Here we present our data analysis from the X-ray satellites Chandra and NuSTAR and the γ-ray satellite AGILE. High-energy emission coincident with HD 93129A was detected in the X-ray band up to 18 keV, whereas in the γ-ray band only upper limits were obtained. We interpret the derived fluxes using a non-thermal radiative model for the wind-collision region. We establish a conservative upper limit for the fraction of the wind kinetic power that is converted into relativistic electron acceleration, f(NT,e) < 0.02. In addition, we set a lower limit for the magnetic field in the wind-collision region as BWCR > 0.3 G. We also argue a putative interpretation of the emission from which we estimate f(NT,e) ≈ 0.006 and B(WCR) ≈ 0.5 G. We conclude that multi-wavelength, dedicated observing campaigns during carefully selected epochs are a powerful tool for characterising the relativistic particle content and magnetic field intensity in colliding wind binaries.

S del Palacio↗

Bayesian Analysis of the Power Spectrum of the Cosmic Microwave Background

There is a wealth of cosmological information encoded in the spatial power spectrum of temperature anisotropies of the cosmic microwave background. The sky, when viewed in the microwave, is very uniform, with a nearly perfect blackbody spectrum at 2.7 degrees. Very small amplitude brightness fluctuations (to one part in a million!!) trace small density perturbations in the early universe (roughly 300,000 years after the Big Bang), which later grow through gravitational instability to the large-scale structure seen in redshift surveys... In this talk, I will discuss a Bayesian formulation of this problem; discuss a Gibbs sampling approach to numerically sampling from the Bayesian posterior, and the application of this approach to the first-year data from the Wilkinson Microwave Anisotropy Probe. I will also comment on recent algorithmic developments for this approach to be tractable for the even more massive data set to be returned from the Planck satellite.

Bayesian inference↗

Noble metals in mid-ocean ridge volcanism: A significant fractionation of gold with respect to platinum group metals

Hydrothermal precipitates, black smoker particulate, and massive sulphide dredge samples from the Explorer Ridge on the Juan de Fuca Plate and the TAG hydrothermal area on the Mid-Atlantic Ridge were analyzed for selected noble metals including Au, Ir and Pd by radiochemical neutron activation analysis. The preliminary results indicate that gold contents may reach the ppm range although values in the neighborhood of 100 to 200 ppb are more typical. The platinum group elements (PGE) represented by Ir and Pd are typically less than 0.02 ppb and less than 2 ppb respectively. These abundances represent a significant enrichment of gold relative to the PGE in comparison with average noble metal abundances in mid-ocean ridge basalts (MORB). A partial explanation of this distinctive fractionation can be found in the concepts of sulfur-saturation of basic magma in mid-ocean ridge (MOR) settings, and the origin of MOR hydrothermal fluids. Experimental and petrological data suggest that MORBs are sulfur-saturated at the time of magma generation and that an immiscible sulfide component remains in the mantle residue. Hence, MORBs are noble metal-poor, particularly with respect to PGE. Consequently, black smoker fluids can be expected to reflect the low Ir and Pd contents of the rock column. The average Au content of MORB is 1.3 ppb, and so the rock column is not significantly enriched in Au. The generation of fluids which precipitate solids with 200 ppb Au is apparently dependent on highly efficient fluid chemistry to mobilize Au from the rock column, high Au solubility in seawater hydrothermal fluids and efficient precipitation mechanisms to coprecipitate Au on Fe, Zn and Cu sulfides. Significant differences in these parameters appear to be the ultimate cause of the strong Au-PGE fractionation in the MOR setting. It does not appear from the current data base that MOR hydrothermal fluids are significant contributors to the Ir enrichment seen in Cretaceous-Tertiary boundary sediments.

Crocket, James H.↗