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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Quantum graph learning and algorithms applied in quantum computer sciences and image classification

Graph and network theory play a fundamental role in quantum computer sciences, including quantum information and computation. Random graphs and complex network theory are pivotal in predicting novel quantum phenomena, where entangled links are represented by edges. Quantum algorithms have been developed to enhance solutions for various network problems, giving rise to quantum graph computing and quantum graph learning (QGL). Here, in this review, we explore graph theory and graph learning methods as powerful tools for quantum computers to generate efficient solutions to problems beyond the reach of classical systems. We delve into the development of quantum complex network theory and its applications in quantum computation, materials discovery, and research. We also discuss quantum machine learning (QML) methodologies for effective image classification using qubits, quantum gates, and quantum circuits. Additionally, the paper addresses the challenges of QGL and algorithms, emphasizing the steps needed to develop flexible QGL solvers. This review presents a comprehensive overview of the fields of QGL and QML, highlights recent advancements, and identifies opportunities for future research.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRSDate not supplied

Using X-Ray Computed Tomography to Image Apollo Drive Tube 73002

The Apollo missions collected 382 kg of rock, regolith, and core samples from six locations on the Moon. Although most Apollo samples are well characterized, several types of samples remain wholly or largely unstudied since their return: unopened and/or sealed drive tube samples, samples frozen upon return, and samples stored in a He-purged environment. NASA selected nine teams to participate in the Apollo Next Generation Sample Analysis (ANGSA) Program to study representative samples from each of these categories. The first sample studied as part of the ANGSA program is drive tube 73002, a 4 cm diameter unopened (but unsealed) drive tube collected on a landslide deposit near Lara Crater at the Apollo 17 landing site. It was part of a ~60 cm long double drive tube, and the bottom half of the tube (73001)was sealed under vacuum on the Moon (and will be studied next). As part of the preliminary examination of sample 73002, the entire drive tube was imaged with a high resolution X-ray Computed Tomography (XCT) scan prior to opening and dissecting the sample. Additionally, >50 XCT scans have been made of “large” clasts (>4 mm) removed from the core as part of the ongoing dissection process. Here we will present both the whole drive tube XCT data showing the overall structure of sample 73002 prior to dissection, as well as XCT scans of individual clasts that reveal the types and abundance of different lithologies present within the drive tube. We will also discuss the utility of the scans as part of the curation and preliminary examination process, as well as the potential for future science returns from the XCT scans.

Ryan A Zeigler↗
NASA NTRSDate not supplied

Using X-Ray Computed Tomography to Image Apollo Drive Tube 73002

The Apollo missions collected 382 kg of rock, regolith, and core samples from six locations on the nearside of the Moon. Today, just over 84% by mass of the Apollo collection remains in pristine condition within the curation facility at Johnson Space Center. Most Apollo samples have been well characterized, however there are several types of samples that have remained wholly or largely unstudied since their return, and/or that have been curated under special conditions. These sample types are: (1) unopened samples sealed under vacuum on the Moon; (2) unopened (but unsealed) drive tubes; (3) Apollo 17 samples frozen shortly after their return; and (4) Apollo 15 samples opened and stored in a helium atmosphere since their return. NASA solicited proposals for the Apollo Next Generation Sample Analysis Program (ANGSA), and 9 teams were selected to study: (1) unsealed, unopened drive tube 73002; (2) sealed, unopened drive tube 73001 (paired with 73002); and (3) a subset of the frozen and He-purged samples [1]. The first sample opened as part of the ANGSA program was drive tube 73002. This was originally a ~30 cm long, 4 cm diameter drive tube collected on a landslide deposit near Lara Crater at the Apollo 17 landing site. It was part of a ~60 cm long double drive tube collected, and the bottom half of the tube (73001) was sealed under vacuum on the Moon [2]. Prior to opening sample 73002, the sample was imaged with a high resolution X-ray Computed Tomography (XCT) scan of the entire tube. Additional XCT scans have been made of “large” clasts removed from the core as part of the dissection process [3]. Here we present the whole tube and close-up XCT data from 73002, and talk about the utility of the scans as part of the curation process, including the potential for future science returns from the high resolutions scans.

R A Zeigler↗
NASA NTRS1977

A comparison of digitally simulated holographic images with actual holographic images

In making digitally generated holograms the digital computer and its associated plotting equipment degrade the quality of the hologram. It is necessary then to study the computer generated hologram in terms of these degradations. A computer simulated optical processor allows the results to be observed via computer simulated images. This research reports a method for optimizing the computer image reconstruction and compares these images with optically produced holographic images. The versatility of the simulated optical processor is illustrated by several spatial filtering and hologram reconstructions.

Calhoun, M. D.↗
NASA NTRS2011

Material Characterization and Geometric Segmentation of a Composite Structure Using Microfocus X-Ray Computed Tomography Image-Based Finite Element Modeling

This study utilizes microfocus x-ray computed tomography (CT) slice sets to model and characterize the damage locations and sizes in thermal protection system materials that underwent impact testing. ScanIP/FE software is used to visualize and process the slice sets, followed by mesh generation on the segmented volumetric rendering. Then, the local stress fields around several of the damaged regions are calculated for realistic mission profiles that subject the sample to extreme temperature and other severe environmental conditions. The resulting stress fields are used to quantify damage severity and make an assessment as to whether damage that did not penetrate to the base material can still result in catastrophic failure of the structure. It is expected that this study will demonstrate that finite element modeling based on an accurate three-dimensional rendered model from a series of CT slices is an essential tool to quantify the internal macroscopic defects and damage of a complex system made out of thermal protection material. Results obtained showing details of segmented images; three-dimensional volume-rendered models, finite element meshes generated, and the resulting thermomechanical stress state due to impact loading for the material are presented and discussed. Further, this study is conducted to exhibit certain high-caliber capabilities that the nondestructive evaluation (NDE) group at NASA Glenn Research Center can offer to assist in assessing the structural durability of such highly specialized materials so improvements in their performance and capacities to handle harsh operating conditions can be made.

Abdul-Aziz, Ali↗
NASA NTRS1974

Mapping of hydrothermal alternation zones and regional rock types using computer enhanced ERTS MSS images

A combination of digital computer processing and color compositing of ERTS MSS images has been used to map hydrothermal alternation zones and regional rock types in south-central Nevada. The technique is based on enhancement of subtle visible and near infrared reflectivity differences between mineralogically dissimilar rocks, especially unaltered and altered rocks. MSS spectral bands are ratioed, pixel by pixel, in the computer and subsequently stretched. These ratio values are used to produce a new black and white image which shows the subtle spectral reflectivity differences. Additional enhancement is achieved by preparing color composites of two or more stretched ratio images. The choice of MSS bands for rationing depends on the spectral reflectance properties of the rocks to be discriminated. Although this technique is in the initial stage of development and is untested in other areas, it already appears to have considerable potential for targeting mineral prospects and for regional geologic mapping.

Rowan, L. C.↗
NASA NTRS1983

Information theory analysis of sensor-array imaging systems for computer vision

Information theory is used to assess the performance of sensor-array imaging systems, with emphasis on the performance obtained with image-plane signal processing. By electronically controlling the spatial response of the imaging system, as suggested by the mechanism of human vision, it is possible to trade-off edge enhancement for sensitivity, increase dynamic range, and reduce data transmission. Computational results show that: signal information density varies little with large variations in the statistical properties of random radiance fields; most information (generally about 85 to 95 percent) is contained in the signal intensity transitions rather than levels; and performance is optimized when the OTF of the imaging system is nearly limited to the sampling passband to minimize aliasing at the cost of blurring, and the SNR is very high to permit the retrieval of small spatial detail from the extensively blurred signal. Shading the lens aperture transmittance to increase depth of field and using a regular hexagonal sensor-array instead of square lattice to decrease sensitivity to edge orientation also improves the signal information density up to about 30 percent at high SNRs.

Huck, F. O.↗
NASA NTRS2009

Monitoring Disasters by Use of Instrumented Robotic Aircraft

Efforts are under way to develop data-acquisition, data-processing, and data-communication systems for monitoring disasters over large geographic areas by use of uninhabited aerial systems (UAS) robotic aircraft that are typically piloted by remote control. As integral parts of advanced, comprehensive disaster- management programs, these systems would provide (1) real-time data that would be used to coordinate responses to current disasters and (2) recorded data that would be used to model disasters for the purpose of mitigating the effects of future disasters and planning responses to them. The basic idea is to equip UAS with sensors (e.g., conventional video cameras and/or multispectral imaging instruments) and to fly them over disaster areas, where they could transmit data by radio to command centers. Transmission could occur along direct line-of-sight paths and/or along over-the-horizon paths by relay via spacecraft in orbit around the Earth. The initial focus is on demonstrating systems for monitoring wildfires; other disasters to which these developments are expected to be applicable include floods, hurricanes, tornadoes, earthquakes, volcanic eruptions, leaks of toxic chemicals, and military attacks. The figure depicts a typical system for monitoring a wildfire. In this case, instruments aboard a UAS would generate calibrated thermal-infrared digital image data of terrain affected by a wildfire. The data would be sent by radio via satellite to a data-archive server and image-processing computers. In the image-processing computers, the data would be rapidly geo-rectified for processing by one or more of a large variety of geographic-information- system (GIS) and/or image-analysis software packages. After processing by this software, the data would be both stored in the archive and distributed through standard Internet connections to a disaster-mitigation center, an investigator, and/or command center at the scene of the fire. Ground assets (in this case, firefighters and/or firefighting equipment) would also be monitored in real time by use of Global Positioning System (GPS) units and radio communication links between the assets and the UAS. In this scenario, the UAS would serve as a data-relay station in the sky, sending packets of information concerning the locations of assets to the image-processing computer, wherein this information would be incorporated into the geo-rectified images and maps. Hence, the images and maps would enable command-center personnel to monitor locations of assets in real time and in relation to locations affected by the disaster. Optionally, in case of a disaster that disrupted communications, the UAS could be used as an airborne communication relay station to partly restore communications to the affected area. A prototype of a system of this type was demonstrated in a project denoted the First Response Experiment (Project FiRE). In this project, a controlled outdoor fire was observed by use of a thermal multispectral scanning imager on a UAS that delivered image data to a ground station via a satellite uplink/ downlink telemetry system. At the ground station, the image data were geo-rectified in nearly real time for distribution via the Internet to firefighting managers. Project FiRE was deemed a success in demonstrating several advances essential to the eventual success of the continuing development effort.

Wegener, Steven S.↗
NASA NTRS1979

Spectral transformation in the SOFI complex for processing photographic images on the ES computer, part 1

A description is given of three programs catalogued in the form of object modules in the library of a system for processing photographic images computer. PFT is the subprogram of the multi-dimensional BPF of real-valued information, in the operative computer memory. INRECO is a subprogram-interface between the real and complex formats for representing two-dimensional spectra and images. FFT2 is a subprogram for calculating the correlation functions of the image using the previous subprograms.

Debabov, A. S.↗
DOE OSTI2022

Star–Galaxy Image Separation with Computationally Efficient Gaussian Process Classification

Abstract We introduce a novel method for discerning optical telescope images of stars from those of galaxies using Gaussian processes (GPs). Although applications of GPs often struggle in high-dimensional data modalities such as optical image classification, we show that a low-dimensional embedding of images into a metric space defined by the principal components of the data suffices to produce high-quality predictions from real large-scale survey data. We develop a novel method of GP classification hyperparameter training that scales approximately linearly in the number of image observations, which allows for application of GP models to large-size Hyper Suprime-Cam Subaru Strategic Program data. In our experiments, we evaluate the performance of a principal component analysis embedded GP predictive model against other machine-learning algorithms, including a convolutional neural network and an image photometric morphology discriminator. Our analysis shows that our methods compare favorably with current methods in optical image classification while producing posterior distributions from the GP regression that can be used to quantify object classification uncertainty. We further describe how classification uncertainty can be used to efficiently parse large-scale survey imaging data to produce high-confidence object catalogs.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2006

Distributed Computing Architecture for Image-Based Wavefront Sensing and 2 D FFTs

Image-based wavefront sensing (WFS) provides significant advantages over interferometric-based wavefi-ont sensors such as optical design simplicity and stability. However, the image-based approach is computational intensive, and therefore, specialized high-performance computing architectures are required in applications utilizing the image-based approach. The development and testing of these high-performance computing architectures are essential to such missions as James Webb Space Telescope (JWST), Terrestial Planet Finder-Coronagraph (TPF-C and CorSpec), and Spherical Primary Optical Telescope (SPOT). The development of these specialized computing architectures require numerous two-dimensional Fourier Transforms, which necessitate an all-to-all communication when applied on a distributed computational architecture. Several solutions for distributed computing are presented with an emphasis on a 64 Node cluster of DSPs, multiple DSP FPGAs, and an application of low-diameter graph theory. Timing results and performance analysis will be presented. The solutions offered could be applied to other all-to-all communication and scientifically computationally complex problems.

Smith, Jeffrey S.↗
NASA NTRS1992

Images constructed from computed flowfields

A method for constructing interferograms, schlieren, and shadowgraphs from ideal- and real-gas, two- and three-dimensional computed flowfileds is described. The computational grids can be structured or unstructured, and multiple grids are an option. The constructed images are compared to experimental images for several types of flow, including a ramp, a blunt-body, a nozzle, and a reacting flow. The constructed images simulate the features observed in the experimental images. They are sensitive to errors in the flowfield solutions and can be used to identify solution errors. In addition, techniques for obtaining phase shifts from experimental finite-fringe interferograms and for removing experimentally induced phase-shift errors are discussed. Both the constructed images and calculated phase shifts can be used for validation of computational fluid dynamics (CFD) codes.

Yates, Leslie A.↗
NASA NTRS1992

Images constructed from computed flow fields

A method for constructing interferograms, schlieren, and shadowgraphs from ideal- and real-gas, two- and three-dimensional computed flow fields is described. The computational grids can be structured or unstructured, and multiple grids are an option. The constructed images are compared to experimental images for several types of flow, including a ramp, a blunt-body, a nozzle, and a reacting flow. The constructed images simulate the features observed in the experimental images. They are sensitive to errors in the flow-field solutions and can be used to identify solution errors. In addition, techniques for obtaining phase shifts from experimental finite-fringe interferograms and for removing experimentally induced phase-shift errors are discussed. Both the constructed images and calculated phase shifts can be used for validation of computational fluid dynamics (CFD) codes.

Yates, Leslie A.↗
DOE OSTI2024

Diffractive optical computing in free space

Abstract Structured optical materials create new computing paradigms using photons, with transformative impact on various fields, including machine learning, computer vision, imaging, telecommunications, and sensing. This Perspective sheds light on the potential of free-space optical systems based on engineered surfaces for advancing optical computing. Manipulating light in unprecedented ways, emerging structured surfaces enable all-optical implementation of various mathematical functions and machine learning tasks. Diffractive networks, in particular, bring deep-learning principles into the design and operation of free-space optical systems to create new functionalities. Metasurfaces consisting of deeply subwavelength units are achieving exotic optical responses that provide independent control over different properties of light and can bring major advances in computational throughput and data-transfer bandwidth of free-space optical processors. Unlike integrated photonics-based optoelectronic systems that demand preprocessed inputs, free-space optical processors have direct access to all the optical degrees of freedom that carry information about an input scene/object without needing digital recovery or preprocessing of information. To realize the full potential of free-space optical computing architectures, diffractive surfaces and metasurfaces need to advance symbiotically and co-evolve in their designs, 3D fabrication/integration, cascadability, and computing accuracy to serve the needs of next-generation machine vision, computational imaging, mathematical computing, and telecommunication technologies.

36 MATERIALS SCIENCE↗
NASA NTRS1976

Architecture and data processing alternatives for the TSE computer. Volume 2: Extraction of topological information from an image by the Tse computer

A simple programmable Tse processor organization and arithmetic operations necessary for extraction of the desired topological information are described. Hardware additions to this organization are discussed along with trade-offs peculiar to the tse computing concept. An improved organization is presented along with the complementary software for the various arithmetic operations. The performance of the two organizations is compared in terms of speed, power, and cost. Software routines developed to extract the desired information from an image are included.

Jones, J. R.↗
DOE OSTI2022

Coupling of multiscale imaging analysis and computational modeling for understanding thick cathode degradation mechanisms

Here, using a thick NMC811 (LiNi 0.8 Mn 0.1 Co 0.1 O 2 ) electrode as an example, we present a macro- to nanoscale 2D and 3D imaging analysis approach coupled with 4D (space + time) computational modeling to probe its degradation mechanism in a lithium-ion battery cell. Particle cracking increases and contact loss between particles and carbon-binder domain are observed to correlate with the cell degradation. This study unravels that the reaction heterogeneity within the thick cathode caused by the unbalanced electron conduction is the main cause of the battery degradation over cycling. The increased heterogeneity in the system will entail more cathode regions where the degree of active material utilization is uneven, leading to higher probabilities of particle cracking. These findings shed light on the crucial role of the electronic and ionic transportation networks in the performance deterioration of the thick cathode. They also provide guidance for cathode architecture optimization and performance improvement.

25 ENERGY STORAGE↗
DOE OSTI2024

Integrated positron emission particle tracking (PEPT) and X-ray computed tomography (CT) imaging of flow phenomena in twisted tape swirl flow

Abstract A combined positron emission particle tracking (PEPT) and X-ray computed tomography (CT) technique is presented, and its utility is demonstrated through investigation of flow in a pipe with twisted tape swirl insert with varying flow conditions (diameter-based Reynolds numbers 16,300–63,300). A description of this technique is given, as well as data handling practices used to relate geometric information captured by CT to fluid flow data gathered via PEPT. It is found that the CT component is readily capable of capturing the stainless steel insert geometry in this present system, but the use of combined plastic and metal materials leads to artifacts in imaging of the plastic surface. Nonetheless, CT data are related to PEPT flow measurements, and average velocity fields are calculated via a pseudo-framing and interpolation scheme and used to visualize and interrogate key flow phenomena within the system. Radial velocity profiles of the mean flow characteristics are seen to collapse to a nearly common form across all flow conditions considered. Helical vortices are seen propagating through the flow field, generated by bypass flow around the gap between the insert and pipe wall, with additional coherent secondary flow structures seen in the higher Reynolds number cases. These findings enhance the understanding of the mixing mechanisms in these swirl flows and encourage the continued development of PEPT-CT methodologies for 3D flow measurements in optically inaccessible systems.

42 ENGINEERING↗
DOE OSTI2023

Computer Vision: EO Imaging & Video Tasks, Metrics, and Datasets [Slides]

Classification is an assignment of an image to a certain category. Localization is identified by the box surrounding the object in the image. Object detection detects instances of semantic objects of a certain class. Semantic segmentation categorizes all the pixels of an image into classes of objects. Instance segmentation identifies each instance of each object in the image. Panoptic (i.e., showing or seeing everything at once) segmentation is a combination of semantic and instance segmentation and classifies all the pixels in the image.

97 MATHEMATICS AND COMPUTING↗