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NASA NTRS2019

Universal Expansion with Spatially Varying G

We calculate the expansion of the Universe under the assumptions that G varies in space and the radial size r of the Universe is very large (we call this the MOND regime of varying-G gravity). The inferred asymptotic behaviour turns out to be different from that found by McCrea & Milne in 1934 and our equations bear no resemblance to those of the relativistic case. In this cosmology, the scale factor R(t) increases linearly with time t, the radial velocity is driven by inertia, and gravity is incapable of hindering the expansion. Yet, Hubble’s law is borne out without any additional assumptions. When we include a repulsive acceleration a(sub de) due to dark energy, the resulting universal expansion is then driven totally by this new term and the solutions for a(sub de) → 0 do not reduce to those of the a(sub de) ≡ 0 case. This is a realization of a new Thom catastrophe: The inclusion of the new term alters the conservation of energy and the dark energy solutions are not reducible to those in the case without dark energy.

Christodoulou, Dimitris M.↗

NASA NTRS1990

The magnetic field in the dust ring at the center of the Galaxy

Measurements of the polarization of the far-infrared thermal emission from six points in the dust ring at Sgr A are presented. The position angles are approximately perpendicular to the long axis of the ring as projected on the sky. The inferred magnetic field is therefore approximately in the plane of the ring. The pattern traced by the polarization vectors resembles that expected for a magnetic accretion disk. The measurements indicate a field in which the outward radial component is much greater than the axial component at the surface of the disk. The field thus appears to satisfy the condition proposed by Blandford and Payne (1982) for removing energy and angular momentum through centrifugal acceleration of surface material moving along the field lines.

Hildebrand, R. H.↗

DOE OSTI2025

Benchmarking the Use of BPM Quadrupole Moments to Measure Emittance

For the PIP-II program, transverse emittance in the Fermilab Booster must remain well controlled at higher bunch intensities. 4-plate beam position monitors (BPMs) have a small but measurable quadrupole moment, making it possible to infer transverse emittance. By compositing many BPMs together, it becomes possible to improve the quality of the quadrupole signal. The Fermilab Booster BPM system has been used to measure these quadrupole moments in the past year and derive emittances from them. Recent benchmarks show that the derived BPM emittances show similar emittance evolution and value to IPM and Multiwire data. This approach can both supplement and complement existing non-intercepting emittance monitors in accelerators.

Balcewicz, M. A. [Fermilab]↗

DOE OSTI2025

Benchmarking the Use of BPM Quadrupole Moments to Measure Emittance

Balcewicz, Michael A. [Fermilab] (ORCID:0009000557↗

NASA NTRS1985

Approximate supernova remnant dynamics with cosmic ray production

Supernova explosions are the most violent and energetic events in the galaxy and have long been considered probably sources of Cosmic Rays. Recent shock acceleration models treating the Cosmic Rays (CR's) as test particles nb a prescribed Supernova Remnant (SNR) evolution, indeed indicate an approximate power law momentum distribution f sub source (p) approximation p(-a) for the particles ultimately injected into the Interstellar Medium (ISM). This spectrum extends almost to the momentum p = 1 million GeV/c, where the break in the observed spectrum occurs. The calculated power law index approximately less than 4.2 agrees with that inferred for the galactic CR sources. The absolute CR intensity can however not be well determined in such a test particle approximation.

Voelk, H. J.↗

DOE OSTI2020

Cross-correlation of the extragalactic gamma-ray background with the thermal Sunyaev-Zel’dovich effect in the cosmic microwave background

Cosmic rays in galaxy clusters are unique probes of energetic processes operating with large-scale structures in the Universe. Precise measurements of cosmic rays in galaxy clusters are essential for improving our understanding of nonthermal components in the intracluster medium (ICM) as well as the accuracy of cluster mass estimates in cosmological analyses. In this paper, we perform a cross-correlation analysis with the extragalactic gamma-ray background and the thermal Sunyaev-Zeldovich (tSZ) effect in the cosmic microwave background. The expected cross-correlation signal would contain rich information about the cosmic-ray-induced gamma-ray emission in the most massive galaxy clusters at $\textit{z}$ ~ 0.1 – 0.2 . We analyze the gamma-ray background map with 8 years of data taken by the Large Area Telescope onboard Fermi satellite and the publicly available tSZ map by Planck. We confirm that the measured cross-correlation is consistent with a null detection, and thus it enables us to put the tightest constraint on the acceleration efficiency of cosmic-ray protons at shocks in and around galaxy clusters. In this work, we find the acceleration efficiency must be below 5% with a 2σ confidence level when the hydrostatic mass bias of clusters is assumed to be 30%, and our result is not significantly affected by the assumed value of the hydrostatic mass bias. Our constraint implies that the nonthermal cosmic-ray pressure in the ICM can introduce only a≲3% level of the hydrostatic mass bias, highlighting that cosmic rays alone do not account for the mass bias inferred by the Planck analyses. Finally, we discuss future detectability prospects of cosmic-ray-induced gamma rays from the Perseus cluster for the Cherenkov Telescope Array.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1984

The production of ion conics by oblique double layers

Magnetized test ions are subjected to acceleration through a numerically simulated oblique double layer in order to determine whether they emerge with velocity vectors aligned with or oblique to the ambient magnetic field. A criterion for oblique alignment, depending on the double-layer parameters and on the external magnetization, is obtained. When it is applied to observed and theoretical auroral double layers, this criterion predicts that accelerated heavy ions will be substantially less magnetic field aligned than will accelerated hydrogen ions, thus suggesting auroral double layers as a source of high-energy ion conics. Test particle simulations are also used to investigate the perpendicular heating of ions at low altitudes by the electric fields associated with moving auroral arcs. The rapid motion of small-scale structures in the arcs is suggested as a source of low-energy conical ion distributions, and the slow drifts of the entire arc forms are inferred to heat ionospheric ions.

Borovsky, J. E.↗

DOE OSTI2020

CQNN: a CGRA-based QNN Framework

We propose a novel Coarse-Grained Reconfigurable Architecture-based (CGRA) QNN acceleration framework, CQNN. CQNN has a large number of basic components for binary functions. By programming CQNN at runtime according to the target QNN models, these basic components are integrated efficiently to support QNN functions with any data-width and hyper-parameter requirements and CQNN is reconfigured to have the optimal architecture for the target models. The framework includes compiler, architecture design, simulator and RTL generator. Experimental results show CQNNs can complete the inference of AlexNet and VGG-16 within 0.13ms and 2.63ms.

Geng, Tong↗

NASA NTRS1993

Mass loss from pre-main-sequence accretion disks. I - The accelerating wind of FU Orionis

We present evidence that the wind of the pre-main-sequence object FU Orionis arises from the surface of the luminous accretion disk. A disk wind model calculated assuming radiative equilibrium explains the differential behavior of the observed asymmetric absorption-line profiles. The model predicts that strong lines should be asymmetric and blueshifted, while weak lines should be symmetric and double-peaked due to disk rotation, in agreement with observations. We propose that many blueshifted 'shell' absorption features are not produced in a true shell of material, but rather form in a differentially expanding wind that is rapidly rotating. The inference of rapid rotation supports the proposal that pre-main-sequence disk winds are rotationally driven.

Calvet, Nuria↗

DOE OSTI2025

Helium bubble formation in aged plutonium metal at ambient conditions

A model of helium bubble formation is developed that assumes the initial nascent bubbles are generated when two diffusing helium atoms come within a distance of about the interatomic spacing of the plutonium atoms. These nascent bubbles are assumed to be locked in place and grow as additional helium atoms diffuse across their surfaces. Calculations of the helium-bubble number density and sizes as a function of age are compared to experiment. This leads to an inferred helium diffusion coefficient of-the-order of 10 -20 m 2 /s, supports the idea that most of the helium from alpha-decay end up in bubbles, and that previous transmission electron microscopy size estimates are biased low. The energy that helium can transfer to 40-year-old plutonium, upon expansion, is determined to be <0.1 Joules per gram of metal. The model predicts differences between the bubble properties in naturally and accelerated aged plutonium.

36 MATERIALS SCIENCE↗

NASA NTRS1986

Observations of ionospheric magnetospheric coupling - DE and Chatanika coincidences

Observations from several experiments on board the Dynamics Explorer 1 and 2 (DE 1 and 2) spacecraft and ground-based radar measurements from the Chatanika radar are combined in order to examine the details of ionospheric/magnetospheric coupling in the local evening sector. DE 1 and DE 2 were in coplanar polar orbits that provided measurements almost simultaneously in time and magnetically coincident with the Chatanika radar from L = 3 to L = 17. The coupling processes are inferred from the density, temperature, composition, and angular distributions of the low-energy plasma observed from the E region of the ionosphere to magnetospheric altitudes of 2.5 earth radii. Plasma characteristics of the plasmasphere, main trough, auroral zone, and polar cap can be studied in this data set. The observations imply that as L increases, the dominant coupling mechanism between the ionosphere and magnetosphere in the measured energy range changes from equilibrium diffusion to perpendicular acceleration and finally to parallel acceleration.

Green, J. L.↗

DOE OSTI2026

Reduced‐Order Modeling of Energetic Materials Using Physics‐Aware Recurrent Convolutional Neural Networks in a Latent Space (LatentPARC)

Physics-aware deep learning (PADL) has gained popularity for use in spatiotemporal dynamics simulations, such as those in computational modeling of energetic materials (EM). We show that the challenge PADL methods face while learning complex field evolution problems can be simplified and accelerated by decoupling it into two tasks: learning complex geometric features in evolving fields and modeling dynamics over these features in a lower-dimensional feature space. We build upon our previous work on physics-aware recurrent convolutional neural networks (PARC). PARC embeds knowledge of underlying physics into its neural network architecture for more robust and accurate prediction of evolving physical fields. PARC was shown to effectively learn complex nonlinear features such as the formation of hotspots and coupled shock fronts in various initiation scenarios of EMs, as a function of microstructures, serving effectively as a microstructure-aware burn model. Here, we further accelerate PARC and reduce its computational cost by projecting the original dynamics onto a lower-dimensional invariant manifold, or “latent space.” The projected latent representation encodes the complex geometry of evolving fields (e.g., temperature and pressure) in a set of data-driven features. The reduced dimension of this latent space allows us to learn the dynamics during the initiation of EM with a lighter and more efficient model. We observe a significant decrease in training and inference time while maintaining results comparable to PARC at inference. This work takes steps towards enabling rapid prediction of EM thermomechanics at larger scales and characterization of EM structure–property–performance linkages at a full application scale.

Mathematics and Computing↗

NASA NTRS1980

Doppler radar observations of the three-dimensional turbulent structure of a quasi-steady thunderstorm

The spatial patterns and temporal evolution of Doppler radar-inferred turbulence within a quasi-steady, left-moving thunderstorm are reported. An organized downdraft circulation was observed, which maintained a persistent, continuously-propagating, anticyclonic and turbulent updraft. The updrafts attained peak speeds of 25 m/s, and maximum estimated reflectivity factors exhibited peak magnitudes of 50-55 dBZ. Mechanical and buoyant production appeared to be the primary generators of turbulence, although buoyancy generation may have also significantly contributed, since turbulent and dynamic entrainment into the vertically accelerating updraft was appreciable below the strongest turbulent activity at 7 km. Patterns of the radial shears of radial velocity exhibited a significant decrease in strength and areal coverage as the storm weakened, which is attributed to decreased activity of large turbulent eddies and the diminution of large-scale mean wind gradients produced by vertical exchanges of horizontal momentum and strong updraft gradients.

Knupp, K. R.↗

NASA NTRS2023

Unusually Long Path Length for a Nearly Scatter-Free Solar Particle Event Observed By Solar Orbiter at 0.43 au

Context. After their acceleration and release at the Sun, solar energetic particles (SEPs) are injected into the interplanetary medium and are bound to the interplanetary magnetic field (IMF) by the Lorentz force. The expansion of the IMF close to the Sun focuses the particle pitch-angle distribution, and scattering counteracts this focusing. Solar Orbiter observed an unusual solar particle event on 9 April 2022 when it was at 0.43 astronomical units (au) from the Sun. Aims. We show that the inferred IMF along which the SEPs traveled was about three times longer than the nominal length of the Parker spiral and provide an explanation for this apparently long path. Methods. We used velocity dispersion analysis (VDA) information to infer the spiral length along which the electrons and ions traveled and infer their solar release times and arrival direction. Results. The path length inferred from VDA is approximately three times longer than the nominal Parker spiral. Nevertheless, the pitch-angle distribution of the particles of this event is highly anisotropic, and the electrons and ions appear to be streaming along the same IMF structures. The angular width of the streaming population is estimated to be approximately 30 degrees. The highly anisotropic ion beam was observed for more than 12 h. This may be due to the low level of fluctuations in the IMF, which in turn is very probably due to this event being inside an interplanetary coronal mass ejection The slow and small rotation in the IMF suggests a flux-rope structure. Small flux dropouts are associated with very small changes in pitch angle, which may be explained by different flux tubes connecting to different locations in the flare region. Conclusions. The unusually long path length along which the electrons and ions have propagated virtually scatter-free together with the short-term flux dropouts offer excellent opportunities to study the transport of SEPs within interplanetary structures. The 9 April 2022 solar particle event offers an especially rich number of unique observations that can be used to limit SEP transport models.

Robert F. Wimmer-Schweingruber↗

DOE OSTI2023

Imaging electron angular distributions to assess a full-power petawatt-class laser focus

Here we present a technique to assess the focal volume of petawatt-class lasers at full power. Our approach exploits quantitative measurement of the angular distribution of electrons born in the focus via ionization of rarefied gas, which are accelerated forward and ejected ponderomotively by the field. We show that a bivariate (θ,Φ) angular distribution, which was obtained with image plates, not only enables the peak intensity to be extracted, but also reflects nonideality of the focal-spot intensity distribution. In our prototype demonstration at intensities of a few ×10 19 to a few ×10 20 W/cm 2 , an f/10 optic produced a focal spot in the paraxial regime. This allows a plane-wave parametrization of the peak intensity given by tanθ c =2/a 0 (a 0 being the normalized vector potential and θ c the minimum ejection angle) to be compared with our measurements. Qualitative agreement was found using an a 0 inferred from the pulse energy, pulse duration, and focal spot distribution with a modified parametrization, tanθ c =2η/a 0 ($η=2.02^{+0.26}_{–0.22}$). This highlights the need for (i) better understanding of intensity degradation due to focal-spot distortions and (ii) more robust modeling of the ejection dynamics. Using single-shot detection of electrons, we showed that while there is significant shot-to-shot variation in the number of electrons ejected at a given angular position, the average distribution scales with the pulse energy in a way that is consistent with that seen with the image plates. Finally, we note that the asymptotic behavior as θ→0° limits the usability of angular measurement. For 800 nm, this limit is at an intensity ~10 21 W/cm 2 .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Photoelectrode Durability in Two- versus Three-Electrode Configurations: Understanding the Impact of Circuit Configuration on Water-Splitting Stability

Device durability remains a significant challenge in photoelectrochemical (PEC) water splitting under ambient conditions. Yet, a lack of understanding of the test configuration and applied bias effects continue to hinder progress. In this study, we differentiate two-electrode (2E) and three-electrode (3E) configurations for evaluating PEC material durability, focusing particularly on their impacts on photoabsorber solid-state operating conditions. Our results underscore the fallacy of inferring 2E device stability from durability measurements performed solely in 3E configurations. Unmeasured and often misunderstood total circuit bias in 3E tests moderates material degradation, leading to the overestimation of photoelectrode stability compared to short-circuit operation. We demonstrate how the photoabsorber's operating voltage critically governs charge separation, surface stability, and degradation mechanisms during PEC operation. With these findings, we propose a standardized framework for conducting more reliable 3E durability experiments that simulate unassisted performance to help accelerate the development of robust, stable materials for solar-driven water splitting.

08 HYDROGEN↗

DOE OSTI2025

Geometric GNNs for charged particle tracking at GlueX

Nuclear physics experiments are aimed at uncovering the fundamental building blocks of matter. The experiments involve high-energy collisions that produce complex events with many particle trajectories. Tracking charged particles resulting from collisions in the presence of a strong magnetic field is critical to enable the reconstruction of particle trajectories and precise determination of interactions. It is traditionally achieved through combinatorial approaches that scale worse than linearly as the number of hits grows. Since particle hit data naturally form a point cloud and can be structured as graphs, graph neural networks (GNNs) emerge as an intuitive and effective choice for this task. In this study, we evaluate the GNN model for track finding on the data from the GlueX experiment at Jefferson Lab. We use simulation data to train the model and test on both simulation and real GlueX measurements. We demonstrate that GNN-based track finding outperforms the currently used traditional method at GlueX in terms of segment-based efficiency at a fixed purity while providing faster inferences. We show that the GNN model can achieve significant speedup by processing multiple events in batches, which exploits the parallel computation capability of graphical processing units (GPUs). Finally, we compare the GNN implementation on GPU and field-programmable gate array and describe the trade-off.

batched GNN pipeline↗

DOE OSTI2022

Variational encoder geostatistical analysis (VEGAS) with an application to large scale riverine bathymetry

Estimation of riverbed profiles, also known as bathymetry, plays a vital role in many applications, such as safe and efficient inland navigation, prediction of bank erosion, land subsidence, and flood risk management. The high cost and complex logistics of direct bathymetry surveys, i.e, depth imaging, have encouraged the use of indirect measurements such as surface flow velocities. However, estimating high-resolution bathymetry from indirect measurements is an inverse problem that can be computationally challenging. Here, we propose a reduced-order model (ROM) based approach that utilizes a variational autoencoder (VAE), a type of deep neural network with a narrow layer in the middle, to compress bathymetry and flow velocity information and accelerate bathymetry inverse problems from flow velocity measurements. In our application, the shallow-water equations (SWE) with appropriate boundary conditions (BCs), e.g., the discharge and/or the free surface elevation, constitute the forward problem, to predict flow velocity. Then, ROMs of the SWEs are constructed on a nonlinear manifold of low dimensionality through a variational encoder and the bathymetry inversion problem is derived on the low-dimensional latent space in a Hierarchical Bayesian setting. Further, the reformulation allows variational inference with a small number (e.g., $\mathscr{O}$ (100) of ROM runs and efficient uncertainty quantification. We have tested our inversion approach on a one-mile reach of the Savannah River, GA, USA. Once the neural network is trained (offline stage), the proposed technique can perform the inversion operation orders of magnitude faster than traditional inversion methods that are commonly based on linear projections, such as principal component analysis (PCA), or the principal component geostatistical approach (PCGA). Furthermore, tests show that the algorithm can estimate the bathymetry with good accuracy even with sparse flow velocity measurements.

54 ENVIRONMENTAL SCIENCES↗