Results for “Image coding” — Page 8

DOE OSTI2025

Maps of growing season gross primary production and net ecosystem exchange for Council Road Mile Marker 71, Seward Peninsula, Alaska, [2017-2023]

This data archive is in support of the Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) publication "Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape", by Murphy et al. (2025a). Murphy et al. (2025a) evaluated whether incorporating observed Arctic vegetation heterogeneity into ELM, the land model of the Department of Energy’s Energy Exascale Earth System Model (E3SM), improved simulations of tundra carbon cycling. The associated model archive can be found at Murphy et al. (2025b). The study focused on the spatial patterns and net landscape-level growing season productivity and carbon uptake. As part of this evaluation, observationally derived maps of average growing season (June–August) net ecosystem exchange (NEE) and gross primary production (GPP) were developed for the same domain. These maps, which form the dataset described here, integrate eddy covariance flux tower, remote sensing, and vegetation community data to provide spatially explicit benchmarks for model evaluation. The maps provide spatially explicit estimates of average growing season NEE and GPP across 13 tundra vegetation communities within the study domain. By combining flux tower observations with Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) hyperspectral imagery and drone-based normalized difference vegetation index (NDVI), these maps capture the heterogeneity of carbon fluxes associated with different Arctic vegetation types. While they represent average seasonal conditions rather than interannual variability, the maps provide a unique dataset for evaluating model performance, comparing vegetation community contributions to landscape-scale carbon cycling, and supporting regional analyses of Arctic carbon dynamics. This data archive contains 5 m resolution maps of vegetation communities, vegetation community average growing season GPP, and vegetation community average growing season NEE (three *.tif files), a User’s Guide (*pdf file), and Table 1 of the User’s Guide displaying vegetation community coverage and average growing season NEE and GPP values (*.csv file).

Murphy, Bailey [ORNL] (ORCID:0000000203995221)↗

DOE OSTI2025

Investigation into Scalable and Detection-Enhanced Satellite Conjunction Assessment

Imaging opportunities (viewable conjunctions) of Resident Space Objects (RSOs) by satellites are not continuously discovered. We propose to continuously produce and report viewable conjunctions among objects in orbit. Viewable conjunctions are events in space and time when a satellite may favorably view a Resident Space Object (RSO). Favorability is defined by a set of constraints, e.g., solar illumination, distance between observer and target, orbital location for viewable event. Computing viewable conjunctions requires calculation of orbital propagation while considering constraints based on the state vectors of position, velocity, with covariance for both satellite and RSO. We propose two parallel lanes of effort: acceleration and research. The objective of acceleration is to avoid missed opportunities and reduce latency for satellite maneuver requests through continuous prediction and reporting of viewable conjunctions. The effort will begin by deploying currently available software on dedicated systems and continue with optimizing the code for high performance computing hardware. The research lane aims to expand RSO inspection and modeling capabilities. Among our current research ideas are spectral characterization of RSO materials and planning multiple observations to recover RSO 3D form. Computing resources at Oak Ridge National Laboratory (ORNL) are available for the acceleration work. Laika, Maxar conjunction prediction dashboard software, and Bluesim, Maxar orbital propagation software, are expected to be the first software in the acceleration lane. Laike and Bluesim are to be provided by the sponsor, and output will be made accessible through its dashboard. Deliverables will follow a gated schedule to the sponsor. ORNL will provide progressively more robust viewable conjunction assessments from both modelled and actual ephemerides.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Helical Photonic Metamaterials for Encrypted Chiral Holograms

Helical structures are among the most quintessential three-dimensional (3D) forms that exhibit mirror asymmetry, a hallmark of chirality. Various structural parameters of helices directly linked to chiroptical properties highlight their importance as essential optical metamaterials for polarization-resolved sensors, imaging, and spectroscopies. However, such function-defining properties remain incompletely understood due to fabrication challenges and the lack of a relationship between structure and optical properties. Here, helical structures are analyzed parametrically, and correlations are established that are applicable to the design of chiral helical optical metamaterials. By systematically varying independent parameters—such as from single-turn to five-turn helices and from small major radii to larger ones optimized to fit the unit cell—the underlying relationships with ellipticty are revealed. In addition to theoretical modeling, the findings are experimentally validated using 3D printing and terahertz spectroscopy. The results demonstrate that optimized helical structures are mechanically tunable and exhibit unprecedented optical properties, including broadband and high-magnitude ellipticity spectra. Being embedded in soft elastomers, helical arrays can serve as soft, stretchable optical-mechanical sensors and holograms containing encoded information, such as barcodes and quick response (QR) codes. Chiral QR codes are realized using pixelated single helices with different handedness, demonstrating their potential as advanced encryption/decryption systems for security applications and chiral metaholograms.

Encrypted QR codes↗

DOE OSTI2024

Shielding development for the spallation neutron source VENUS instrument

VENUS is a neutron imaging instrument that will use a broad range of neutron wavelengths, from epithermal to cold energies, and will include enhanced contrast mechanisms. It will offer novel energy-selective imaging techniques directly connecting complex engineering materials and systems’ structures, properties, and functions to reveal practical and fundamental answers about their real-world performance. Here, the instrument will be built at SNS beamline 10, facing the decoupled poisoned hydrogen moderator. The driving cost for the instrument is the beamline and instrument cave shielding. Final analyses were performed to evaluate the thickness and composition of shielding materials for the instrument cave and beamline to meet radiation safety criteria for the instrument to start up in 2024 after completing the SNS proton power upgrade.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Realization of a gas puff imaging system on the Wendelstein 7-X stellarator

A system for studying the spatiotemporal dynamics of fluctuations in the boundary of the W7-X plasma using the “Gas-Puff Imaging” (GPI) technique has been designed, constructed, installed, and operated. This GPI system addresses a number of challenges specific to long-pulse superconducting devices, such as W7-X, including the long distance between the plasma and the vacuum vessel wall, the long distance between the plasma and diagnostic ports, the range of last closed flux surface (LCFS) locations for different magnetic configurations in W7-X, and management of heat loads on the system’s plasma-facing components. The system features a pair of “converging–diverging” nozzles for partially collimating the gas puffed locally ≈135 mm radially outboard of the plasma boundary, a pop-up turning mirror for viewing the gas puff emission from the side (which also acts as a shutter for the re-entrant vacuum window), and a high-throughput optical system that collects visible emission resulting from the interaction between the puffed gas and the plasma and directs it along a water-cooled re-entrant tube directly onto the 8 × 16 pixel detector array of the fast camera. The DEGAS 2 neutral code was used to simulate the Hα (656 nm) and HeI (587 nm) line emission expected from well-characterized gas-puffs of H2 and He and excited within typical edge plasma profiles in W7-X, thereby predicting line brightnesses used to reduce the risks associated with system sensitivity and placement of the field of view. Operation of GPI on W7-X shows excellent signal-to-noise ratios (>100 at 2 Mframes/s) over the field of view for minimally perturbing gas puffs. The GPI system provides detailed measurements of the two-dimensional (radial and poloidal) dynamics of plasma fluctuations in the W7-X edge and scrape-off layer and in and around the magnetic islands outside the LCFS that make up the island divertor configuration employed on W7-X.

Instruments & Instrumentation↗

DOE OSTI2026

Calibration and Data Analysis of a Frequency Selectable Laser Source for CMB Detector Characterization

Cosmic Microwave Background (CMB) experiments study faint radiation left over from the early universe. The CMB was created when the universe became cool enough for light to travel freely through space, and today it gives scientists one of the earliest images of the universe. One important goal of modern CMB experiments is to measure this radiation with higher precision in order to search for evidence that supports the theory of cosmic inflation. To do this, scientists use extremely sensitive detectors that must be calibrated accurately. The Frequency Selectable Laser Source, or FLS, is a new calibration tool that can send selected frequencies to detectors and help measure their response. During my internship, I worked on the FLS after it returned to Fermilab from Chile, where it had been used to characterize detectors at the Simons Observatory. The system came back in parts, so the first part of my project was helping rebuild the optical and mechanical setup. After the system was rebuilt, we performed alignments to maximize the receiver photocurrent. We then collected calibration measurements over different frequency ranges, including 543 GHz to 568 GHz, 740 GHz to 766 GHz, and 60 GHz to 500 GHz. These measurements were used to check waterline calibration and reflectivity features and compare new data with previous data. Another major part of my project was learning Python so I could understand previous analysis code, modify it for new files, and write my own code to compare the mean response between datasets. The results showed that the new data was close to previous measurements and that waterline features near 556 GHz and 752 GHz were found within less than 1.5 GHz of the expected values. I also completed the reflectivity analysis for five prisms in two polarization orientations. In the original orientation, the results were consistent between the five prisms and close to values measured on a different system at the University of Chicago. I then collected a second set of measurements on my own with the polarization of the laser rotated by 90 degrees and compared them with the original data using the same Python workflow. The measured reflectivity increased for all five prisms in the new orientation, showing that the prism reflectivity depends on polarization. Future work will focus on using the FLS to characterize real CMB detectors.

Pumarino, Rafael [Unlisted]↗

DOE OSTI2026

Calibration and Data Analysis of a Frequency Selectable Laser Source for CMB Detector Characterization

Cosmic Microwave Background (CMB) experiments study faint radiation left over from the early universe. The CMB was created when the universe became cool enough for light to travel freely through space, and today it gives scientists one of the earliest images of the universe. One important goal of modern CMB experiments is to measure this radiation with higher precision in order to search for evidence that supports the theory of cosmic inflation. To do this, scientists use extremely sensitive detectors that must be calibrated accurately. The Frequency Selectable Laser Source, or FLS, is a new calibration tool that can send selected frequencies to detectors and help measure their response. During my internship, I worked on the FLS after it returned to Fermilab from Chile, where it had been used to characterize detectors at the Simons Observatory. The system came back in parts, so the first part of my project was helping rebuild the optical and mechanical setup. After the system was rebuilt, we performed alignments to maximize the receiver photocurrent. We then collected calibration measurements over different frequency ranges, including 543 GHz to 568 GHz, 740 GHz to 766 GHz, and 60 GHz to 500 GHz. These measurements were used to check waterline calibration and reflectivity features and compare new data with previous data. Another major part of my project was learning Python so I could understand previous analysis code, modify it for new files, and write my own code to compare the mean response between datasets. The results showed that the new data was close to previous measurements and that waterline features near 556 GHz and 752 GHz were found within less than 1.5 GHz of the expected values. I also completed the reflectivity analysis for five prisms in two polarization orientations. In the original orientation, the results were consistent between the five prisms and close to values measured on a different system at the University of Chicago. I then collected a second set of measurements on my own with the polarization of the laser rotated by 90 degrees and compared them with the original data using the same Python workflow. The measured reflectivity increased for all five prisms in the new orientation, showing that the prism reflectivity depends on polarization. Future work will focus on using the FLS to characterize real CMB detectors.

Pumarino Meza, Rafael [Unlisted, US; Fermilab]↗

DOE OSTI2026

Calibration and Data Analysis of a Frequency Selectable Laser Source for CMB Detector Characterization

Cosmic Microwave Background (CMB) experiments study faint radiation left over from the early universe. The CMB was created when the universe became cool enough for light to travel freely through space, and today it gives scientists one of the earliest images of the universe. One important goal of modern CMB experiments is to measure this radiation with higher precision in order to search for evidence that supports the theory of cosmic inflation. To do this, scientists use extremely sensitive detectors that must be calibrated accurately. The Frequency Selectable Laser Source, or FLS, is a new calibration tool that can send selected frequencies to detectors and help measure their response. During my internship, I worked on the FLS after it returned to Fermilab from Chile, where it had been used to characterize detectors at the Simons Observatory. The system came back in parts, so the first part of my project was helping rebuild the optical and mechanical setup. After the system was rebuilt, we performed alignments to maximize the receiver photocurrent. We then collected calibration measurements over different frequency ranges, including 543 GHz to 568 GHz, 740 GHz to 766 GHz, and 60 GHz to 500 GHz. These measurements were used to check waterline calibration and reflectivity features and compare new data with previous data. Another major part of my project was learning Python so I could understand previous analysis code, modify it for new files, and write my own code to compare the mean response between datasets. The results showed that the new data was close to previous measurements and that waterline features near 556 GHz and 752 GHz were found within less than 1.5 GHz of the expected values. I also completed the reflectivity analysis for five prisms in two polarization orientations. In the original orientation, the results were consistent between the five prisms and close to values measured on a different system at the University of Chicago. I then collected a second set of measurements on my own with the polarization of the laser rotated by 90 degrees and compared them with the original data using the same Python workflow. The measured reflectivity increased for all five prisms in the new orientation, showing that the prism reflectivity depends on polarization. Future work will focus on using the FLS to characterize real CMB detectors.

Pumarino Meza, Rafael [Unlisted, US; Fermilab]↗

DOE OSTI2025

Correcting for Selection Biases in the Determination of the Hubble Constant from Time-Delay Cosmography

The time delay between multiple images of strongly lensed quasars has been used to infer the Hubble constant. The primary systematic uncertainty for time-delay cosmography is the mass-sheet transform (MST), which preserves the lensing observables while altering the inferred ⁠H 0 . The TDCOSMO collaboration used velocity dispersion measurements of lensed quasars and lensed galaxies to infer that mass sheets are present, which decrease the inferred H 0 by 8 per cent. Here, we test the assumption that the density profiles of galaxy–galaxy and galaxy–quasar lenses are the same. We use a composite star-plus-dark-matter mass profile for the parent deflector population and model the selection function for galaxy–galaxy and galaxy–quasar lenses. We find that a power-law density profile with an MST is a good approximation to a two-component mass profile around the Einstein radius, but we find that galaxy–galaxy lenses have systematically higher mass-sheet components than galaxy–quasar lenses. For individual systems, λ int correlates with the ratio of the half-light radius and Einstein radius of the lens. By propagating these results through the TDCOSMO hierarchical inference code, we find that H 0 is lowered by a further 3 per cent. Using a more recent measurement of velocity dispersions and our fiducial model for selection biases, we infer H 0 = 66 ± 4 (stat) ± 1 (model sys) ± 2 (measurement sys) km s -1 Mpc -1 for the TDCOSMO plus SLACS data set. The first residual systematic error is due to plausible alternative choices in modelling the selection function, and the second is an estimate of the remaining systematic error in the measurement of velocity dispersions for SLACS lenses. Accurate time-delay cosmography requires precise velocity dispersion measurements and accurate calibration of selection biases.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Machine Learning for Predictive Performance Analysis in Charged Particle Beam Tools

Imaging methods driven by probes, electrons, and ions have played a dominant role in modern science and engineering. Opportunities for machine vision and AI that focus on consumer problems like driving and feature recognition, are now presenting themselves for automating aspects of the scientific processes. This proposal aims to enable and drive discovery in ultra-low energy implantation by taking advantage of faster processing, flexible control and detection methods, and architecture-agnostic workflows that will result in higher efficiency and shorter scientific development cycles. Custom microscope control, collection and analysis hardware will provide a framework for conducting novel in situ experiments revealing unprecedented insight into surface dynamics at the nanoscale. Ion implantation is a key capability for the semiconductor industry. As devices shrink, novel materials enter the manufacturing line, and quantum technologies transition to being more mainstream. Traditional implantation methods fall short in terms of energy, ion species, and positional precision. Here we demonstrate 1 keV focused ion beam Au implantation into Si and validate the results via atom probe tomography. We show the Au implant depth at 1 keV is 0.8 nm and that identical results for low energy ion implants can be achieved by either lowering the column voltage, or decelerating ions using bias – while maintaining a sub-micron beam focus. We compare our experimental results to static calculations using SRIM and dynamic calculations using binary collision approximation codes TRIDYN and IMSIL. A large discrepancy between the static and dynamic simulation is found that is due to lattice enrichment with high stopping power Au and surface sputtering. Additionally, we demonstrate how model details are particularly important to the simulation of these low-energy heavy-ion implantations. Finally, we discuss how our results pave a way to much lower implantation energies, while maintaining high spatial resolution.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Analysis of a Prototype Multi-Detector Fast-Neutron Radiography Panel

A multi-detector fast neutron radiography panel was built using the previous work on scalable neutron radiography using the IDEAS ROSSPAD readout module. A new aluminum housing was built to accommodate a large number of detectors tiled together. Additional changes to startup and processing code were made to operate the detector as one cohesive unit. Spatial resolution of the full panel using Cs-137 gammas was reported to be 0.42 line pairs per centimeter at 90% MTF and 2.09 line pairs per centimeter at 10% MTF. Here, three neutron radiographs generated using a Cf-252 fission neutron source were used to determine the spatial resolution of the panel for neutrons. The experiments had 90% MTF values of 0.24, 0.3, and 0.27 line pairs per centimeter and 10% MTF values of 1.30, 1.46, and 1.40 line pairs per centimeter. An example neutron radiograph was also used to prove that the radiography panel can perform true neutron radiography.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Dynamics of implosion, bounce, and re-implosion of a shell directly driven by a time-shaped laser pulse

Gas-filled plastic spherical shells have been imploded using the 60-beam OMEGA laser. The same laser pulse was used as in a previous experiment, which demonstrated the dynamic formation of a shell by irradiating a homogeneous plastic foam sphere. In the present experiment, the shell initially implodes, bounces, and expands; a new shell then forms and undergoes a second implosion. Analysis of x-ray self-emission-streaked images and sequences of 2D x-ray self-emission framing camera images show shell evolution that is in reasonable agreement with 1D simulations. Shell integrity and symmetry are well maintained until the formation of the new shell. The final implosion, instead, is affected by substantial asymmetries.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Scale-up Unlearnable Examples Learning with High-performance Computing

Recent advancements in AI models, like ChatGPT, are structured to retain user interactions, which could inadvertently include sensitive healthcare data. In the healthcare field, particularly when radiologists use AI-driven diagnostic tools hosted on online platforms, there is a risk that medical imaging data may be repurposed for future AI training without explicit consent, spotlighting critical privacy and intellectual property concerns around healthcare data usage. Addressing these privacy challenges, a novel approach known as Unlearnable Examples (UEs) has been introduced, aiming to make data unlearnable to deep learning models. A prominent method within this area, called Unlearnable Clustering (UC), has shown improved UE performance with larger batch sizes but was previously limited by computational resources (e.g., a single workstation). To push the boundaries of UE performance with theoretically unlimited resources, we scaled up UC learning across various datasets using Distributed Data Parallel (DDP) training on the Summit supercomputer. Our goal was to examine UE efficacy at high-performance computing (HPC) levels to prevent unauthorized learning and enhance data security, particularly exploring the impact of batch size on UE’s unlearnability. Utilizing the robust computational capabilities of the Summit, extensive experiments were conducted on diverse datasets such as Pets, MedMNist, Flowers, and Flowers102. Our findings reveal that both overly large and overly small batch sizes can lead to performance instability and affect accuracy. However, the relationship between batch size and unlearnability varied across datasets, highlighting the necessity for tailored batch size strategies to achieve optimal data protection. The use of Summit’s high-performance GPUs, along with the efficiency of the DDP framework, facilitated rapid updates of model parameters and consistent training across nodes. Our results underscore the critical role of selecting appropriate batch sizes based on the specific characteristics of each dataset to prevent learning and ensure data security in deep learning applications. The source code is publicly available at https: // github. com/ hrlblab/ UE_ HPC .

Zhu, Yanfan [Vanderbilt University, Nashville, TN,↗

DOE OSTI2025

Data from a throughfall exclusion experiment: Fine root dynamics, morphology, chemistry, and AMF colonization across four lowland Panamanian forests

Fine roots regulate forest nutrient, carbon, and water cycling, yet their variation within and among tropical forests remains under-characterized. We quantified root productivity, disappearance, and stocks to 1 m using minirhizotron imaging, and we measured morphology, elemental composition [root carbon (C), root nitrogen (N), root phosphorus (P)], and arbuscular mycorrhizal fungi (AMF) colonization to 20 cm using ingrowth cores and sequential coring. Sampling took place in four distinct lowland Panamanian forests (32 plots; 8 per forest) from 2018 through 2022 under control and throughfall-exclusion (drought) treatments in the Panama Rainforest Changes with Experimental Drying (PARCHED) experiment.The dataset is presented as an Excel workbook with six tabs. The first tab is the data dictionary. Tab S1 contains ingrowth-core production and mortality, morphology and soil moisture. Tab S2 contains sequential-coring standing stocks with associated morphology and soil moisture. Tab S3 contains minirhizotron row data records to 1 m depth, including per-frame root length and diameter, normalized length metrics, and session timing. Tab S4 contains AMF colonization. Tab S5 contains fine-root chemistry at 0–10 cm, reporting %P, %C, %N, and C:N for samples collected via ingrowth cores and sequential-coring standing stocks. CSV mirrors for each tab are provided, and a KML file supplies coordinates for all 32 plots.Key variables span live and dead fine-root biomass (and coarse fractions where applicable), specific root length (SRL) and area (SRA), diameter, root tissue density (RTD), soil moisture, AMF colonization, root %N, %C, %P, and C:N, along with minirhizotron root length and diameter. Depth, season, treatment, and plot/site identifiers are included to support cross-tab integration and analysis from 0–100 cm (minirhizotron) and 0–20 cm (cores).Units are reported in-column and missing values are coded as NA. No special software is required to open or use the files (Excel, CSV, and KML compatible).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Extreme Longitudinal Compression of Optimized Beams for MEV Ultrafast Electron Diffraction (Final Technical Report)

We worked out the design of a high repetition rate MeV energy ultrafast electron diffraction instrument based on the existing Cornell photoinjector, which can readily be applied to the presented findings. This example is a blueprint of other similarly arranged UED setups. Using particle tracking simulations in conjunction with multiobjective genetic algorithm optimization, we explored the smallest bunch lengths, emittance, and probe spot sizes achievable. As two limits, we defined stroboscopic conditions (with single electrons per pulse) and operation with 10 5 electrons per bunch which may be suitable for single-shot diffraction images. In the stroboscopic case, the flexibility provided by the many cavity bunching and acceleration allows for longitudinal phase space linearization without a higher harmonic field, providing sub-fs bunch lengths at the sample. Given low emittance photoemission conditions, these small bunch lengths can be maintained with probe transverse sizes at the single micron (1 μm) scale and below. In the case of 10 5 electrons per pulse, we simulated state-of-the-art 5D brightness conditions: rms bunch lengths of 10 fs with 3-nm normalized emittances, while permitting repetition rates as high as 1.3 GHz. We showed that in conjunction with collimating apertures, a novel focusing scheme achieves very high-quality emittance compensation for the central core of the beam composing 40% of particles, for a resulting beam size of 5 μm (rms). Finally, to aid in the design of new SRF-based ultrafast electron diffraction machines, we simulated the trade-off between the number of cavities used and achievable bunch length and emittance. In the longitudinal dimension, we made use of the fact that MeV UED requires much lower energy than the 15-MeV maxi mum energy of Cornell’s CBETA injector, and we may therefore use several of the SRF cavities for bunch length compression. In practice, we used a genetic optimization algorithm to choose the phases and amplitudes of the cavities appropriately for optimal bunching. In the zero space charge case, we found that bunching and acceleration are distributed across the six cavities in a way that produces a linearizing effect. And we showed that the ultimate bunch length can be limited by time-of-flight differences arising from transverse size and transverse momentum spread. The space charge code developed and used for this development is now permanent part of the Bmad accelerator simulation code and has already contributed to other developments, e.g., for the EIC electron cooler design.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

Studies of localized mix and asymmetry caused by the stalk in inertial fusion experiments at OMEGA

In an inertially confined fusion experiment, a capsule of fusion fuel is compressed to high temperatures and densities using lasers, creating a hot plasma in which thermonuclear fusion reactions take place. To achieve efficient conversion of laser energy to fuel heating, the implosion must be as spherically symmetric as possible. One common source of asymmetry that degrades performance is the stalk and glue spot that hold the capsule in place before the experiment. The exact nature and magnitude of this perturbation had not been previously quantified. In this work, inertially confined fusion experiments were executed with an additional stalk on the capsule to measure and quantify the effect of the stalk and glue spot on the symmetry and performance. It is found that the stalk drives low-mode asymmetry by shadowing the laser drive on the part of the shell near the glue spot, enhancing the hot-spot velocity toward the stalk by 40–80 km/s and elongating the hot-spot along the stalk axis. It is also found that localized mix due to the additional stalk has a negligible effect on implosion performance. Two-dimensional radiation-hydrodynamic simulations using the xRAGE code reproduce the direction of the experimentally observed change to hot-spot velocity and implosion performance metrics, but not the observed elongation, suggesting that this feature results from an interaction between stalk perturbations and other preexisting asymmetry seeds, such as laser drive asymmetry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Development of an ab initio learned model of electron deposition range in deuterium-tritium plasmas through time-dependent density functional theory calculations and machine learning

Accurate hydrodynamic modeling for laser-direct-drive (LDD) inertial-confinement-fusion (ICF) relies on precise calculations of the electron thermal conduction in all target materials. The nonlocal stopping range of electrons in ICF plasmas directly influences thermal conduction; yet, no first principles model exists for the electron mean free path in the conduction-zone regime. This work utilized time-dependent stochastic density-functional theory (TD-sDFT) to calculate the electron stopping power in deuterium-tritium (DT) plasmas at (ρ, T) conditions relevant to the conduction zone and the compressed shell in ICF. Using a combination of our TD-sDFT data and already established analytical models, we developed and trained an artificial neural network to create a global model for the nonlocal electron deposition range, λ E . We compared our machine-learning (ML) based model for λ E to the currently-used modified-Lee-More model in LDD radiation-hydrodynamic codes, such as lilac, and saw an overall decrease in the deposition range. To understand the effects of λ E on LDD ICF implosion dynamics, we implemented the ML-based model into lilac; specifically, we looked at designs consistent with a current experiment on the OMEGA laser and for a newly designed LDD-ICF target for the future OMEGA-Next facility. In both cases, we saw an overall drop in predicted ablation pressure, peak areal density, and neutron yield due to the reduced thermal conduction (smaller λ E ) in DT plasmas. Comparisons with the experiment on OMEGA are also made.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Enabling end-to-end secure federated learning in biomedical research on heterogeneous computing environments with APPFLx

Facilitating large-scale, cross-institutional collaboration in biomedical machine learning (ML) projects requires a trustworthy and resilient federated learning (FL) environment to ensure that sensitive information such as protected health information is kept confidential. Specifically designed for this purpose, this work introduces APPFLx - a low-code, easy-to-use FL framework that enables easy setup, configuration, and running of FL experiments. APPFLx removes administrative boundaries of research organizations and healthcare systems while providing secure end-to-end communication, privacy-preserving functionality, and identity management. Furthermore, it is completely agnostic to the underlying computational infrastructure of participating clients, allowing an instantaneous deployment of this framework into existing computing infrastructures. Experimentally, the utility of APPFLx is demonstrated in two case studies: (1) predicting participant age from electrocardiogram (ECG) waveforms, and (2) detecting COVID-19 disease from chest radiographs. Here, ML models were securely trained across heterogeneous computing resources, including a combination of on-premise high-performance computing and cloud computing facilities. By securely unlocking data from multiple sources for training without directly sharing it, these FL models enhance generalizability and performance compared to centralized training models while ensuring data remains protected. In conclusion, APPFLx demonstrated itself as an easy-to-use framework for accelerating biomedical studies across organizations and healthcare systems on large datasets while maintaining the protection of private medical data.

Biomedical Research↗