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At least 217 records · Page 12

Shuttle Radar Topography Mission (SRTM) Flight System Design and Operations Overview

This paper provides an overview of the Shuttle Radar Topography Mission (SRTM), with emphasis on flight system implementation and mission operations from systems engineering perspective. Successfully flown in February, 2000, the SRTM's primary payload consists of several subsystems to form the first spaceborne dual-frequency (C-band and X-band) fixed baseline interferometric synthetic aperture radar (InSAR) system, with the mission objective to acquire data sets over 80% of Earth's landmass for height reconstruction. The paper provides system architecture, unique design features, engineering budgets, design verification, in-flight checkout and data acquisition of the SRTM payload, in particular for the C-band system. Mission operation and post-mission data processing activities are also presented. The complexity of the SRTM as a system, the ambitious mission objective, the demanding requirements and the high interdependency between multi-disciplined subsystems posed many challenges. The engineering experience and the insight thus gained have important implications for future spaceborne interferometric SAR mission design and implementation.

Shen, Yuhsyen↗

Super-Resolution Ptychography with Small Segmented Detectors

To overcome the spatial resolution limit set by aperture-limited diffraction in traditional scanning transmission electron microscopy, microscopists have developed ptychography enabled by iterative phase retrieval algorithms and high-dynamic-range pixel array detectors. Current detector designs are limited by the data rate off chip, so a high-pixel-count detector has a proportionally lower frame rate than the few-segment detectors used for differential phase contrast (DPC) imaging. This slower acquisition speed leads to heightened vulnerability to scan noise, drift, and potential sample damage. This creates opportunities for repurposing fast segmented detectors for ptychography by trading a reduction in reciprocal space pixels for an increase in real space pixels. Here, we explore a strategy of oversampling in real space and instead apply detector pixel upsampling during the reconstruction process. Further, we demonstrate the viability of achieving super-resolution ptychography on thin objects using only 2 × 2 detector pixels, surpassing the resolution of integrated DPC (iDPC) imaging. With optimization using simulated datasets and experiments on MoTe 2 /WSe 2 bilayer moiré superlattices, we achieved super-resolution ptychography reconstructions under rapid acquisition conditions (37.5 pA, 1 μs dwell time), yielding over 50% improvements in contrast and information limit compared to annular dark field and iDPC imaging on the same detectors.

2D materials↗

Reconstruction of decays to merged photons using end-to-end deep learning with domain continuation in the CMS detector

A novel technique based on machine learning is introduced to reconstruct the decays of highly Lorentz-boosted particles. Using an end-to-end deep learning strategy, the technique bypasses existing rule-based particle reconstruction methods typically used in high energy physics analyses. It uses minimally processed detector data as input and directly outputs particle properties of interest. The new technique is demonstrated for the reconstruction of the invariant mass of particles decaying in the CMS detector. The decay of a hypothetical scalar particle A into two photons, A → γ γ , is chosen as a benchmark decay. Lorentz boosts γ L = 60 – 600 are considered, ranging from regimes where both photons are resolved to those where the photons are closely merged as one object. A training method using domain continuation is introduced, enabling the invariant mass reconstruction of unresolved photon pairs in a novel way. The new technique is validated using π 0 → γ γ decays in LHC collision data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Semi-Automated, Object-Based Tomography of Dislocation Structures

The characterization of the three-dimensional arrangement of dislocations is important for many analyses in materials science. Dislocation tomography in transmission electron microscopy is conventionally accomplished through intensity-based reconstruction algorithms. Although such methods work successfully, a disadvantage is that they require many images to be collected over a large tilt range. Here, we present an alternative, semi-automated object-based approach that reduces the data collection requirements by drawing on the prior knowledge that dislocations are line objects. Our approach consists of three steps: (1) initial extraction of dislocation line objects from the individual frames, (2) alignment and matching of these objects across the frames in the tilt series, and (3) tomographic reconstruction to determine the full three-dimensional configuration of the dislocations. Drawing on innovations in graph theory, we employ a node-line segment representation for the dislocation lines and a novel arc-length mapping scheme to relate the dislocations to each other across the images in the tilt series. We demonstrate the method for a dataset collected from a dislocation network imaged by diffraction-contrast scanning transmission electron microscopy. Based on these results and a detailed uncertainty analysis for the algorithm, we discuss opportunities for optimizing data collection and further automating the method.

47 OTHER INSTRUMENTATION↗

A mathematical model for spatial orientation from pictorial perspective displays

A previously formulated mathematical model, describing how observers reconstruct three-dimensional spatial layouts from perspective projections, has been extended to more complex situations. The model assumes that the observer has a priori knowledge of certain characteristics of the viewed objects, like size, shape, or parallelism or perpendicularity of lines or planes. These assumptions are used in a three-dimensional process to reconstruct a spatial layout that `best matches' the perceived lines of sight to the object coordinates. Sources of errors and biases in this process are specified and their effects on model outputs are discussed. An experiment, in which eight subjects judged the relative direction of one object with respect to another, has been conducted to validate the model. The model has been found to generally reproduce the systematic trends of the experimental results and also has provided an analytical explanation for them. The mathematical model is expected to be a useful tool in analyzing and developing pictorial perspective flight displays.

Grunwald, Arthur J.↗

Improving ICARUS track reconstruction algorithms

The ICARUS experiment is part of the Short-Baseline Neutrino program at Fermilab. Its primary objective is to explore the possible existence of sterile neutrinos in the O(1 eV) mass range and to clarify the anomalies observed in the Liquid Scintillator Neutrino Detector and MiniBooNE experiments. The ICARUS-T600 detector is a Liquid Argon Time Projection Chamber, capable of producing high-resolution 3D images and precise calorimetric measurements of ionizing particles. This technology allows for a detailed study of neutrino interactions across a broad energy range, from a few keV to several hundred GeV. The track reconstruction is achieved through a software framework that applies a series of pattern recognition algorithms, transforming raw detector signals into fully reconstructed event topologies. This process involves identifying interaction vertices, particle tracks, and electromagnetic showers within the TPC. However, in certain cases, these algorithms may mistakenly break a single particle track into several shorter segments, interpreting each as a distinct particle. Since track length is used to estimate the particle's energy, such fragmentation can result in an energy underestimation of several hundred MeV. Furthermore, when a track is split into multiple segments, the particle identification (which relies on analyzing the energy loss as a function of the residual range) may fail, potentially leading to the loss of the entire event. To mitigate this problem, we have developed a dedicated algorithm designed to identify and reconnect (“stitch”) the tracks that were erroneously divided into multiple segments.

Ricci, Alessandro Maria [Pisa U.; INFN, Pisa] (ORC↗

Potential of Attosecond Coherent Diffractive Imaging

Attosecond science has been transforming our understanding of electron dynamics in atoms, molecules, and solids. However, to date almost all of the attoscience experiments have been based on spectroscopic measurements because attosecond pulses have intrinsically very broad spectra due to the uncertainty principle and are incompatible with conventional imaging systems. In this paper we report an important advance towards achieving attosecond coherent diffractive imaging. Using simulated attosecond pulses, we simultaneously reconstruct the spectrum, 17 probes, and 17 spectral images of extended objects from a set of ptychographic diffraction patterns. We further confirm the principle and feasibility of this method by successfully performing a ptychographic coherent diffractive imaging experiment using a light-emitting diode with a broad spectrum. We believe this work clears the way to an unexplored domain of attosecond imaging science, which could have a far-reaching impact across different disciplines.

36 MATERIALS SCIENCE↗

TAOS Orbit Determination Results Using Global Positioning Satellites

Orbit determination results for the Air Force Phillips Laboratory's Technology for Autonomous Operational Survivability (TAOS) satellite using a Rockwell AST V Global Positioning System (GPS) receiver are presented in this paper. Under a cooperative effort, GPS orbit determination technology developed at Jet Propulsion Laboratory (JPL) has been transferred to the U.S. Air Force. JPL's post processing differential GPS software MIRAGE [1] was modified to perform precise orbit determination for the TAOS satellite. Reconstructed TAOS position accuracies of 10 meters (3 sigma) are the objective. With four days of data, three-dimensional positions of less than 3 meters (1 sigma) have been achieved with overlapping orbit determination spans. Orbit determination results are also compared with those of the on-board GPS receiver's navigation solutions and with the Air Force's Satellite Control Network SGLS processing.

TAOS↗

Learning neural representations for X-ray ptychography reconstruction with unknown probes

X-ray ptychography provides exceptional nanoscale resolution and is widely applied in materials science, biology, and nanotechnology. However, its full potential is constrained by the critical challenge of accurately reconstructing images when the illuminating probe is unknown. Conventional iterative methods and deep learning approaches are often suboptimal, particularly under the low-signal conditions inherent to low-dose and high-speed experiments. These limitations compromise reconstruction fidelity and restrict the broader adoption of the technique. In this work, we introduce the Ptychographic Implicit Neural Representation (PtyINR), a self-supervised framework that simultaneously addresses the object- and probe-recovery problem. By parameterizing both as continuous neural representations, PtyINR performs end-to-end reconstruction directly from raw diffraction patterns without requiring any pre-characterization of the probe. Extensive evaluations demonstrate that PtyINR achieves superior reconstruction quality on both simulated and experimental data, with remarkable robustness under challenging low-signal conditions. Furthermore, PtyINR offers a generalizable, physics-informed framework for addressing probe-dependent inverse problems, making it applicable to a wide range of computational microscopy problems.

36 MATERIALS SCIENCE↗

Deep Learning Model Segmentations on Computed Tomography 3D Reconstructions of Coffee Beans to Determine Void Ratio (U-Net) and Roast Level (LinkNet)

This project will evaluate the functionality of Object Research Dragonfly software’s user produced deep learning (DL) models on Computed Tomography (CT) scanned coffee beans from green (unroasted) through a dark roast. DL models will be expected to identify voids within the coffee beans, and identify the level of roast of the bean from the CT reconstruction. The scope of this project is intended to meet the Capstone Project requirements of University of California San Diego (UCSD) Structural Engineering master’s degree and offer useful insight on Dragonfly’s DL capability for LANL’s Non-Destructive Evaluation (NDE) CT team. The results of this project will be presented to the E-6 NDE group within LANL. Data acquisition was completed with a North Star Imaging (NSI) X-25 CT Cabinet.

97 MATHEMATICS AND COMPUTING↗

Impact of Vehicle Flexibility on IRVE-II Flight Dynamics

The Inflatable Re-entry Vehicle Experiment II (IRVE-II) successfully launched from Wallops Flight Facility (WFF) on August 17, 2009. The primary objectives of this flight test were to demonstrate inflation and re-entry survivability, assess the thermal and drag performance of the reentry vehicle, and to collect flight data for refining pre-flight design and analysis tools. Post-flight analysis including trajectory reconstruction outlined in O Keefe3 demonstrated that the IRVE-II Research Vehicle (RV) met mission objectives but also identified a few anomalies of interest to flight dynamics engineers. Most notable of these anomalies was high normal acceleration during the re-entry pressure pulse. Deflection of the inflatable aeroshell during the pressure pulse was evident in flight video and identified as the likely cause of the anomaly. This paper provides a summary of further post-flight analysis with particular attention to the impact of aeroshell flexibility on flight dynamics and the reconciliation of flight performance with pre-flight models. Independent methods for estimating the magnitude of the deflection of the aeroshell experienced on IRVE-II are discussed. The use of the results to refine models for pre-flight prediction of vehicle performance is then described.

Bose, David M.↗

Learning robust parameter inference and density reconstruction in flyer plate impact experiments

Estimating physical parameters or material properties from experimental observations is a common objective in many areas of physics and material science. In many experiments, especially in shock physics, radiography is the primary means of observing the system of interest. However, radiography does not provide direct access to key state variables, such as density, which prevents the application of traditional parameter estimation approaches. Here we focus on flyer plate impact experiments on porous materials, and resolving the underlying parameterized equation of state (EoS) and crush porosity model parameters given radiographic observation(s). We use machine learning as a tool to demonstrate with high confidence that using only high impact velocity data does not provide sufficient information to accurately infer both EoS and crush model parameters, even with fully resolved density fields or a dynamic sequence of images. We thus propose an observable data set consisting of low and high impact velocity experiments/simulations that capture different regimes of compaction and shock propagation, and proceed to introduce a generative machine learning approach which produces a posterior distribution of physical parameters directly from radiographs. We demonstrate the effectiveness of the approach in estimating parameters from simulated flyer plate impact experiments, and show that the obtained estimates of EoS and crush model parameters can then be used in hydrodynamic simulations to obtain accurate and physically admissible density reconstructions. Finally, we examine the robustness of the approach to model mismatches, and find that the learned approach can provide useful parameter estimates in the presence of out-of-distribution radiographic noise and previously unseen physics, thereby promoting a potential breakthrough in estimating material properties from experimental radiographic images.

97 MATHEMATICS AND COMPUTING↗

Microwave Imaging on Metal Objects

This final report for the project discusses the attempts to model, using different methods, microwave image reconstruction. Maximum Entropy Method was not successful. Attempts to use Singular Value Decomposition (SVD) got some good results after initial failure. SVD is based upon a theory of linear algebra, to the effect that any M X N Matrix A whose number of rows M is greater than or equal to its number of columns, N can be written as the product of an M X N column-orthogonal matrix U, an N X N diagonal Matrix, W, with m positive or zero elements (the singular values) and the transposition of an N X N orthogonal matrix V. In microwave imaging, the scattered fields can be expressed by the induced current distribution. The SVD method required more contiguous computer memory than was available. Work was also done on the Conjugate Gradient Method (CGM), which didn't work well when tried earlier. It was found that separation of the imaginary part and the real part during calculation may work. This work was considered incomplete as of the end of the grant period.

Tolliver, C. L.↗

Fast quantum ghost imaging with a single-photon-sensitive time-stamping camera

Quantum ghost imaging (QGI) leverages correlations between entangled photon pairs to reconstruct an image using light that has never physically interacted with an object. Despite extensive research interest, this technique has long been hindered by slow acquisition speeds, due to the use of raster-scanned detectors or the slow response of intensified cameras. Here, we utilize a single-photon-sensitive time-stamping camera to perform QGI at ultra-low-light levels with rapid data acquisition and processing times, achieving high-resolution and high-contrast images in under 1 min. Our work addresses the trade-off between image quality, optical power, data acquisition time, and data processing time in QGI, paving the way for practical applications in biomedical and quantum-secured imaging.

Mavian, Alex (ORCID:0000000279448830)↗

Choice of image attribute for automated radargrammetry

This paper discusses SAR imaging with emphasis on radar backscatter properties. In studying how planetary surfaces modulate the radar cross-section, it is determined that both the amount of and variation in backscattered microwave energy provide the necessary cues (i.e., object shading and boundary information) for stereointerpretation. While past research into automated reconstruction of topography from radar stereopairs has concentrated on the use of shading, it is shown that boundary information may also be used successfully. How these attributes can be potentially misleading are discussed. This work suggests a process for generating high-quality topography maps from SAR imagery.

Matarese, Joseph R.↗

IRAS galaxies versus POTENT mass - Density fields, biasing, and Omega

A comparison of the galaxy density field extracted from a complete redshift survey of IRAS galaxies brighter than 1.936 Jy with the mass-density field reconstructed by the POTENT procedure from the observed peculiar velocities of 493 objects is presented. A strong correlation is found between the galaxy and mass-density fields; both feature the Great Attractor, part of the Perseus-Pisces supercluster, and the large void between them. Monte Carlo noise simulations show that the data are consistent with the hypotheses that the smoothed fluctuations of galaxy and mass densities at each point are proportional to each other with the 'biasing' factor of IRAS galaxies, b(I), and that the peculiar velocity field is related to the mass-density field as expected according to the gravitational instability theory. Under these hypotheses, the two density fields can be related by specifying b(I) and the cosmological density parameter, Omega.

Dekel, Avishai↗

Image reconstruction of IRAS survey scans

The IRAS survey data can be used successfully to produce images of extended objects. The major difficulties, viz. non-uniform sampling, different response functions for each detector, and varying signal-to-noise levels for each detector for each scan, were resolved. The results of three different image construction techniques are compared: co-addition, constrained least squares, and maximum entropy. The maximum entropy result is superior. An image of the galaxy M51 with an average spatial resolution of 45 arc seconds is presented, using 60 micron survey data. This exceeds the telescope diffraction limit of 1 minute of arc, at this wavelength. Data fusion is a proposed method for combining data from different instruments, with different spacial resolutions, at different wavelengths. Data estimates of the physical parameters, temperature, density and composition, can be made from the data without prior image (re-)construction. An increase in the accuracy of these parameters is expected as the result of this more systematic approach.

Bontekoe, Tj. Romke↗

Stereo Imaging Miniature Endoscope

Stereo imaging requires two different perspectives of the same object and, traditionally, a pair of side-by-side cameras would be used but are not feasible for something as tiny as a less than 4-mm-diameter endoscope that could be used for minimally invasive surgeries or geoexploration through tiny fissures or bores. The proposed solution here is to employ a single lens, and a pair of conjugated, multiple-bandpass filters (CMBFs) to separate stereo images. When a CMBF is placed in front of each of the stereo channels, only one wavelength of the visible spectrum that falls within the passbands of the CMBF is transmitted through at a time when illuminated. Because the passbands are conjugated, only one of the two channels will see a particular wavelength. These time-multiplexed images are then mixed and reconstructed to display as stereo images. The basic principle of stereo imaging involves an object that is illuminated at specific wavelengths, and a range of illumination wavelengths is time multiplexed. The light reflected from the object selectively passes through one of the two CMBFs integrated with two pupils separated by a baseline distance, and is focused onto the imaging plane through an objective lens. The passband range of CMBFs and the illumination wavelengths are synchronized such that each of the CMBFs allows transmission of only the alternate illumination wavelength bands. And the transmission bandwidths of CMBFs are complementary to each other, so that when one transmits, the other one blocks. This can be clearly understood if the wavelength bands are divided broadly into red, green, and blue, then the illumination wavelengths contain two bands in red (R1, R2), two bands in green (G1, G2), and two bands in blue (B1, B2). Therefore, when the objective is illuminated by R1, the reflected light enters through only the left-CMBF as the R1 band corresponds to the transmission window of the left CMBF at the left pupil. This is blocked by the right CMBF. The transmitted band is focused on the focal plane array (FPA).

Bae, Youngsam↗