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DOE OSTI2024

Deep learning based event reconstruction for cyclotron radiation emission spectroscopy

The objective of the cyclotron radiation emission spectroscopy (CRES) technology is to build precise particle energy spectra. This is achieved by identifying the start frequencies of charged particle trajectories which, when exposed to an external magnetic field, leave semi-linear profiles (called tracks) in the time–frequency plane. Due to the need for excellent instrumental energy resolution in application, highly efficient and accurate track reconstruction methods are desired. Deep learning convolutional neural networks (CNNs) - particularly suited to deal with information-sparse data and which offer precise foreground localization—may be utilized to extract track properties from measured CRES signals (called events) with relative computational ease. In this work, we develop a novel machine learning based model which operates a CNN and a support vector machine in tandem to perform this reconstruction. A primary application of our method is shown on simulated CRES signals which mimic those of the Project 8 experiment—a novel effort to extract the unknown absolute neutrino mass value from a precise measurement of tritium β - -decay energy spectrum. When compared to a point-clustering based technique used as a baseline, we show a relative gain of 24.1% in event reconstruction efficiency and comparable performance in accuracy of track parameter reconstruction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Pushing the Limits of High-speed X-ray Tomography to See the Unknown

First-of-their kind datasets from a high-speed X-ray tomography system were collected, and a novel numerical effort utilizing temporal information to reduce measurement uncertainty was shown. The experimental campaign used three high-speed X-ray imaging systems to collect data at 100 kHz of a scene containing high-velocity objects. The scene was a group of known objects propelled by a 12-gauge shotgun shell reaching speeds of hundreds of meters per second. These data represent a known volume where the individual components are known, with experimental uncertainties that can be used for reconstruction algorithm validation. The numerical effort used synthetic volumes in MATLAB to produce projections along known lines of sight to perform tomographic reconstructions. These projections and reconstructions were performed on a single object at two orientations, representing two timesteps, to increase the reconstruction accuracy.

36 MATERIALS SCIENCE↗

NASA NTRS1973

A holographic interferometer system for measuring density profiles in high-velocity flows

This paper describes a holographic interferometric technique for obtaining density measurements across a test gas that is traveling at a velocity of over 5500 m/sec in an expansion tube facility. Interferometric data describing the flow in the test section are obtained using a long coherence length CW argon laser in a holographic system and a rotating drum camera recorder. The object beam, which passes through the test section, intersects the reference beam at a small angle to form an interference pattern of about 170 lines/mm, and is recorded as a hologram. Before a test, this hologram is placed in its original position and rotated slightly so that an interference pattern is generated by the intersection of the reconstructed and real-time object beams.

Burner, A. W.↗

NASA NTRS1972

A Holographic Interferometer System for Measuring Density Profiles in High-Velocity Flows

This paper describes a holographic interferometric technique for obtaining density measurements across a test gas that is traveling at a velocity of over 5500 meters per second in an expansion tube facility. Interferometric data describing the flow in the test section are obtained using a long coherence length cw argon laser in a holographic system and a rotating drum camera recorder. The object beam, which passes through the test section, intersects the reference beam at a small angle (5 degrees) to form an interference pattern of about 170 lines per millimeter, and is recorded as a hologram. Before a test, this hologram is placed in its original position and rotated slightly so that an interference pattern is generated by the intersection of the reconstructed and real-time object beams. This interference pattern is adjusted to a series of bright, horizontal fringes having a spatial frequency of about 5 fringes per centimeter. During the few milliseconds it takes the test gas to pass through the test section, variations in the gas density across the 8.4-centimeter test section produce phase variations in the object beam and result in a varying interference pattern. A rotating drum camera with a 0.15-millimeter slit aligned perpendicular to the fringes is used to record the varying fringe shifts with a time resolution of about 3 microseconds. The average gas density across the test section is determined by measuring these fringe shifts.

Burner, Alpheus W.↗

NASA NTRS1989

Interferometric tomography of continuous fields with incomplete projections

Interferometric tomography in the presence of an opaque object has been investigated. In principle the developed iterative algorithm does not need to augment the missing information. It is based on the successive reconstruction of the difference field, the difference between the object field to be reconstructed and its estimate, in the defined region only. The application of the algorithm results in stable convergence.

Cha, Soyoung S.↗

NASA NTRS1999

A Comprehensive Orbit Reconstruction for the Galileo Prime Mission in the J2000 System

The Galileo spacecraft arrived at Jupiter in December of 1995 to begin an orbital tour of the Jovian system. The objective of the tour was up close study of the planet, its satellites, and its magnetosphere. The spacecraft completed its 11 orbit prime mission in November of 1997 having had 16 successful close encounters with the Galilean satellites (including two prior to Jupiter orbit insertion). Galileo continues to operate and will have made an additional 10 orbits of Jupiter by the date of this Conference. Earlier papers discuss the determination of the spacecraft orbit in support of mission operations from arrival at Jupiter through the first 9 orbits. In this paper we re-examine those earlier orbits and extend the analysis through orbit 12, the first orbit of the Galileo Europa Mission (GEM). The objective of our work is the reconstruction of the spacecraft trajectory together with the development of a consistent set of ephemerides for the Galilean satellites. As a necessary byproduct of the reconstruction we determine improved values for the Jovian system gravitational parameters and for the Jupiter pole orientation angles. Our preliminary analyses have already led to many of the results reported in the scientific literature. Unlike the Galileo Navigation Team which operates in the EME-1950 coordinate system, we elected to work in the (J2000) International Celestial Reference Frame (ICRF), the reference frame of the current JPL planetary and satellite ephemerides as well as the standard frame of the international astronomical and planetary science community. Use of this frame permits more precise modelling of the spacecraft and satellite observations. Moreover, it is the frame of choice for all other operational JPL missions and will probably be the frame for future missions for some time. Consequently, our adoption of the ICRF will facilitate the combination of our results with any obtained from future missions (e.g. the proposed Europa Orbiter mission). In addition, our results may be used by the science community, without need of a reference frame conversion.

Jacobson, Robert A.↗

NASA NTRS1991

Object enhanced optical correlation

A major drawback of optical correlator systems is the poor quality of correlation signals. Background noise is one of the many sources of false correlation peaks. However, by reconstructing an input scene with the object's amplitude function, an object-enhanced scene - used as input to the optical correlators - (with respect to background) can be obtained. Thus, the optical correlation of this enhanced image improves the signal-to-noise ratio in the correlation image. Furthermore, construction of a filter plane mask that permits simultaneous scene enhancement and cross-correlation operations is described. Experimental results demonstrate the practicality of this approach.

Scholl, Marija S.↗

NASA NTRS2021

A multi-model CMIP6-PMIP4 study of Arctic sea ice at 127 ka: sea ice data compilation and model differences

The Last Interglacial period (LIG) is a period with increased summer insolation at high northern latitudes, which results in strong changes in the terrestrial and marine cryosphere. Understanding the mechanisms for this response via climate modelling and comparing the models' representation of climate reconstructions is one of the objectives set up by the Paleoclimate Modelling Intercomparison Project for its contribution to the sixth phase of the Coupled Model Intercomparison Project. Here we analyse the results from 16 climate models in terms of Arctic sea ice. The multi-model mean reduction in minimum sea ice area from the pre industrial period (PI) to the LIG reaches 50 % (multi-model mean LIG area is 3.20×10^6 sq.km, compared to 6.46×10^6 sq.km for the PI). On the other hand, there is little change for the maximum sea ice area (which is 15–16×10^6 sq.km for both the PI and the LIG. To evaluate the model results we synthesise LIG sea ice data from marine cores collected in the Arctic Ocean, Nordic Seas and northern North Atlantic. The reconstructions for the northern North Atlantic show year-round ice-free conditions, and most models yield results in agreement with these reconstructions. Model–data disagreement appear for the sites in the Nordic Seas close to Greenland and at the edge of the Arctic Ocean. The northernmost site with good chronology, for which a sea ice concentration larger than 75 % is reconstructed even in summer, discriminates those models which simulate too little sea ice. However, the remaining models appear to simulate too much sea ice over the two sites south of the northernmost one, for which the reconstructed sea ice cover is seasonal. Hence models either underestimate or overestimate sea ice cover for the LIG, and their bias does not appear to be related to their bias for the pre-industrial period. Drivers for the inter-model differences are different phasing of the up and down short-wave anomalies over the Arctic Ocean, which are associated with differences in model albedo; possible cloud property differences, in terms of optical depth; and LIG ocean circulation changes which occur for some, but not all, LIG simulations. Finally, we note that inter-comparisons between the LIG simulations and simulations for future climate with moderate (1 %/yr) CO2 increase show a relationship between LIG sea ice and sea ice simulated under CO2 increase around the years of doubling CO2. The LIG may therefore yield insight into likely 21st century Arctic sea ice changes using these LIG simulations.

Arctic sea ice↗

DOE OSTI2026

Beyond Contrast Transfer: Spectral SNR as a Finite-Dose Metric for STEM Phase Retrieval

The contrast transfer function (CTF) is widely used to evaluate phase retrieval methods in scanning transmission electron microscopy (STEM), including center-of-mass imaging, parallax imaging, direct ptychography, and iterative ptychography. However, the CTF reflects only the maximum usable signal, neglecting the effects of finite electron fluence and the Poisson-limited nature of detection. As a result, it can significantly overestimate practical performance, especially in low-dose regimes. Here, we employ the spectral signal-to-noise ratio (SSNR), as a finite-dose statistical framework to evaluate the recoverable signal as a function of spatial frequency. Using numerical reconstructions of white-noise objects, we show that center-of-mass, parallax, and direct ptychography exhibit dose-independent SSNRs, with close-form analytic expressions. In contrast, iterative ptychography exhibits a surprising dose dependence: at low fluence, its SSNR converges to that of direct ptychography; at high fluence, it saturates at a value consistent with the maximum detective quantum efficiency predicted by recent quantum Fisher information bounds. The results highlight the limitations of CTF-based evaluation and motivate SSNR as a more accurate, finite-dose metric for assessing STEM phase retrieval methods.

STEM phase retrieval↗

DOE OSTI2026

Detector architecture and data flow of the CMS HGCAL Phase-2 Endcap Calorimeter Upgrade

The CMS High Granularity Calorimeter (HGCAL) is the Phase-2 endcap calorimeter upgrade for the High-Luminosity Large Hadron Collider, designed to provide precise spatial, energy, and timing measurements in a high-radiation, high-pileup environment. This work presents an overview of the HGCAL assembly process, detector architecture, and end-to-end data flow. The data flow goes from signal generation in silicon sensors and scintillator tiles through front-end electronics, optical transmission, and back-end data acquisition. The study highlights how the integrated detector, electronics, and readout systems enable efficient event reconstruction and support the physics objectives of the HL-LHC.

Osei Boakye, Prince [Grambling State U.]↗

NASA NTRS2007

Optimizing RHESSI X-ray Imaging

RHESSI X-ray imaging is possible with angular resolution as fine as 2 arcsec (FWHM) at energies from as low as 3 keV to >100 keV. However, taking full advantage of this capability has proven to be challenging given the Fourier-transform imaging technique that is used, specific instrumental considerations that must be taken into account, and the many different options of the available image reconstruction algorithms. Such considerations as the best reconstruction algorithm to use, the optimal weighting of the different Fourier components, deciding between short image integration times and rapid imaging cadence, the different energy ranges covered by the 9 detectors, the effect of pulse pile-up and albedo, etc. must all be taken into account in obtaining and interpreting RHESSI X-ray images. This poster describes different techniques for optimizing the image reconstruction depending on the science objectives - identifying compact or extended sources, searching for source motion, obtaining the best photometry, determining the believability of different features in an image, etc. The emphasis is on making full use of data from all the RHESSI detectors, including the ones behind the finest grids when warranted by the source structure. This is the case for the hard X-ray emission along the ribbons of the flare on 2005 May 13 reported by Liu et al. (2007) and this event will be used as an example.

Dennis, Brian R.↗

NASA NTRS2008

A Novel 24 GHz One-Shot, Rapid and Portable Microwave Imaging System

Development of microwave and millimeter wave imaging systems has received significant attention in the past decade. Signals at these frequencies penetrate inside of dielectric materials and have relatively small wavelengths. Thus. imaging systems at these frequencies can produce images of the dielectric and geometrical distributions of objects. Although there are many different approaches for imaging at these frequencies. they each have their respective advantageous and limiting features (hardware. reconstruction algorithms). One method involves electronically scanning a given spatial domain while recording the coherent scattered field distribution from an object. Consequently. different reconstruction or imaging techniques may be used to produce an image (dielectric distribution and geometrical features) of the object. The ability to perform this accurate~v and fast can lead to the development of a rapid imaging system that can be used in the same manner as a video camera. This paper describes the design of such a system. operating at 2-1 GHz. using modulated scatterer technique applied to 30 resonant slots in a prescribed measurement domain.

Ghasr, M. T.↗

DOE OSTI2026

3D reconstruction and neural rendering for adversarial machine learning

While evasion attacks on computer vision systems have been widely studied, creating attacks that remain effective under significant changes in viewpoint continues to be challenging. Traditional approaches often rely on affine transformations of images, but these approaches degrade at larger perspective shifts and often produce unrealistic or ineffective perturbations. Recent methods use differentiable renderers to improve viewpoint robustness, but they typically depend on manually constructed 3D models. We introduce a semi-automated pipeline that generates physically printable and perspective-invariant adversarial patches using only a small set of 2D images. Our method integrates 3D reconstruction, neural rendering, adversarial patch optimization, and an object detection victim model into a unified workflow. We use 2D Gaussian Splatting for high fidelity mesh reconstruction and FlexPara for surface parameterization that produces texture maps suitable for patch editing. Together, these components form a fully differentiable pipeline in PyTorch3D that links texture modification to model outputs, enabling efficient optimization of patches that remain effective across many viewpoints. The complete process, from image capture to patch printing and physical evaluation, can be completed within a few hours. We demonstrate the effectiveness of the resulting patches through attacks on the YOLOv8 object detection model and discuss remaining challenges and opportunities for improving robustness and scalability.

Singhvi, Vivaan [ORNL] (ORCID:0009000586288221)↗

DOE OSTI2023

Three-dimensional nanoscale reduced-angle ptycho-tomographic imaging with deep learning (RAPID)

X-ray ptychographic tomography is a nondestructive method for three dimensional (3D) imaging with nanometer-sized resolvable features. The size of the volume that can be imaged is almost arbitrary, limited only by the penetration depth and the available scanning time. Here we present a method that rapidly accelerates the imaging operation over a given volume through acquiring a limited set of data via large angular reduction and compensating for the resulting ill-posedness through deeply learned priors. The proposed 3D reconstruction method “RAPID” relies initially on a subset of the object measured with the nominal number of required illumination angles and treats the reconstructions from the conventional two-step approach as ground truth. It is then trained to reproduce equal fidelity from much fewer angles. After training, it performs with similar fidelity on the hitherto unexamined portions of the object, previously not shown during training, with a limited set of acquisitions. In our experimental demonstration, the nominal number of angles was 349 and the reduced number of angles was 21, resulting in a x140 aggregate speedup over a volume of 4.48 x 93.18 x 3.92 μm 3 and with (14nm) 3 feature size, i.e. ~ 10 8 voxels. RAPID’s key distinguishing feature over earlier attempts is the incorporation of atrous spatial pyramid pooling modules into the deep neural network framework in an anisotropic way. We found that adjusting the atrous rate improves reconstruction fidelity because it expands the convolutional kernels’ range to match the physics of multi-slice ptychography without significantly increasing the number of parameters.

47 OTHER INSTRUMENTATION↗

NASA NTRS1975

Development of a spectroscopic photoelectric imaging Fabry-Perot interferometer preliminary observational results

In order to observe extended astronomical objects at high spatial and spectral resolution, a spectroscopic photoelectric imaging Fabry-Perot interferometer was constructed. Among the properties chosen for the instrument are an air-spaced, piezoelectrically scanned design allowing an accurately settable free spectral range and employing a single etalon of high finesse. Careful design of the etalon mountings and optical train preserves high ligh throughput. Spectra of single spatial elements with a photomultiplier were obtained, and an SEC vidicon detector was used to record a series of images through the interferometer while scanning the wavelength in discrete steps. The latter procedure yields sufficient information to reconstruct spectral features over the entire object, and for the conditions assumed, either series of observations requires only a small fraction of a rotational period for Jupiter or Saturn. An electronic control system was also constructed which permits rapid and flexible variation of the operational mode of the Fabry-Perot and its ancilliary devices so as to minimize loss of observational time.

Smith, W. H.↗

NASA NTRS1976

Spectroscopic photoelectric imaging Fabry-Perot interferometer - Its development and preliminary observational results

In order to observe extended astronomical objects at high spatial and spectral resolution, we have constructed a spectroscopic photoelectric imaging Fabry-Perot interferometer (SPIFI). Among the properties chosen for the instrument are an air-spaced, piezoelectrically scanned design allowing an accurately settable free spectral range and employing a single etalon of high finesse. Careful design of the etalon mountings and optical train preserves high light throughput. We either obtain spectra of single spatial elements with a photomultiplier or use an SEC vidicon detector to record a series of images through the interferometer while scanning the wavelength in discrete steps. The latter procedure yields sufficient information to reconstruct spectral features over the entire object. For the conditions assumed, either series of observations requires only a small fraction of a rotational period for Jupiter or Saturn, for example.

Smith, W. H.↗

DOE OSTI2026

Demonstration of Algorithm for Sensor Placement Optimization using Simulation Data

This deliverable reports FY26 progress in advancing a neural-network-based Green’s-function framework for reconstructing neutron-flux distributions from ex-core measurements and for translating reconstruction requirements into a practical detector-layout strategy. Building on the FY25 formulation, the present work had two main objectives: (1) refine and re-evaluate the reconstruction methodology on an updated Purdue University Reactor Number One (PUR-1) model, and (2) develop a systematic, Green’s-function-guided procedure for boundary detector placement.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Improving High-Energy Particle Detectors with Machine Learning

Microseconds after the Big Bang, the universe existed in a state called the quark-gluon plasma (QGP). To experimentally study its properties, the QGP is recreated in high-energy nuclear collisions at the LHC, and the particles produced from the QGP are reconstructed from their energy deposition in the ATLAS calorimeter. This requires both classifying the particles and calibrating their deposited energy. The objective of this project is to improve the reconstruction by using machine learning techniques, where the energy depositions of clusters of cells, formed by ATLAS topo-clustering methods, are treated as three-dimensional images when inputted to neural networks. This approach significantly improves the calibration of deposited energies when cross-validating while training, and models trained on idealized data predict the calibrated energies of particles in more complex data sets well. Additionally, implementation of a data generator using uproot allows the program to load input data into memory as needed while training or predicting, significantly reducing the amount of memory used. The data generator also allows for use of multiprocessing to speed up training and evaluating. This work illustrates that using machine learning methods for both classification and calibration has the potential to significantly improve particle reconstruction.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗