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DOE OSTI2023

Many-body expansion for light nuclear systems

Here we extend the many-body expansion (MBE), previously applied to hydrogen bonded and molecular systems, to the light nuclear systems 3 H and 3 He by considering the nucleonic degrees of freedom as fundamental in the expansion. The analysis is based on the Pauli nucleonic dynamics (PND) model, a simple antisymmetrized dynamical code, inspired by the sophisticated constrained molecular dynamics (CoMD) model. The total energy of the 2 H nucleus is calculated with this model at -2.312 MeV, which is within 4% of the experimental value of -2.225 MeV. The application of the MBE yields results for the three-body term in the 3 H nucleus that is comparable with previous estimates, while it is reported for the first time for the nucleus of 3 He . The energies of 3 H and 3 He that include the sum of the one- and two-body terms with the model are - 6.97 ± 0.21 MeV and - 6.19 ± 0.21 MeV and the three-body terms, estimated from the difference of the sum of the one- and two-body terms from the experimentally measured energies, are -1.51 ± 0.21 MeV and -1.53 ± 0.21 MeV, respectively. The MBE for the 3 H and 3 He nuclei is qualitatively similar to the one previously reported for the water trimer: the two- and three-body terms are negative with the latter amounting to ~3% of the former. Additionally, the three-body terms correspond to about 16–23% of the total energy of the bound systems, a percentage that is also comparable to the one in the water trimer (17%). In this manner, the MBE analysis can be applied to light nuclear systems following the same protocol as the one that has been previously extensively used for hydrogen bonded molecular systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Measuring the mass of the black widow PSR J1555-2908

ABSTRACT Accurate measurements of the masses of neutron stars are necessary to test binary evolution models, and to constrain the neutron star equation of state. In pulsar binaries with no measurable post-Keplerian parameters, this requires an accurate estimate of the binary system’s inclination and the radial velocity of the companion star by other means than pulsar timing. In this paper, we present the results of a new method for measuring this radial velocity using the binary synthesis code Icarus. This method relies on constructing a model spectrum of a tidally distorted, irradiated star as viewed for a given binary configuration. This method is applied to optical spectra of the newly discovered black widow PSR J1555–2908. By modeling the optical spectroscopy alongside optical photometry, we find that the radial velocity of the companion star is 397 ± 4 km s−1 (errors quoted at 95 per cent confidence interval), as well as a binary inclination of >75°. Combined with γ-ray pulsation timing information, this gives a neutron star mass of 1.67$^{+0.15}_{-0.09}$ M⊙ and a companion mass of 0.060$^{+0.005}_{-0.003}$ M⊙, placing PSR J1555–2908 at the observed upper limit of what is considered a black widow system.

Kennedy, M. R.↗

DOE OSTI2025

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

We present hls4ml, a free and open-source platform that translates machine learning (ML) models from modern deep learning frameworks into high-level synthesis (HLS) code that can be integrated into full designs for field-programmable gate arrays (FPGAs) or application-specific integrated circuits (ASICs). With its flexible and modular design, hls4ml supports a large number of deep learning frameworks and can target HLS compilers from several vendors, including Vitis HLS, Intel oneAPI and Catapult HLS. Together with a wider eco-system for software-hardware co-design, hls4ml has enabled the acceleration of ML inference in a wide range of commercial and scientific applications where low latency, resource usage, and power consumption are critical. In this paper, we describe the structure and functionality of the hls4ml platform. The overarching design considerations for the generated HLS code are discussed, together with selected performance results.

FOS: Computer and information sciences↗

DOE OSTI2025

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

Schulte, Jan-Frederik [Purdue U.] (ORCID:000000034↗

DOE OSTI2026

Universal Optimization and Tighter Fidelity Bounds for Approximate Quantum Error Correction

Approximate quantum error correction (AQEC) not only dictates the performance of discrete- and continuous-variable quantum error correction codes but also serves as a unifying framework across various physical disciplines. Identifying the optimal recovery channel to maximize the entanglement fidelity via standard semidefinite programming is computationally bottlenecked by the exponentially growing number of Kraus operators with system size, rendering large-scale optimization prohibitive. While analytical near-optimal maps exist, they typically work only when the Knill-Laflamme conditions are nearly satisfied. In this Letter, we establish an efficient framework by leveraging the duality between recovery and environment decoupling. This framework yields a tighter analytical lower bound on entanglement fidelity than the conventional limit set by the transpose channel. Furthermore, by exploiting the decayed weights of noise Kraus operators, we introduce a framework based on principal component analysis to reduce the dimension. In thermal loss channels where the weights decay exponentially, our approach achieves a 33-fold computational speedup while maintaining rigorous accuracy. Our approach enables high-precision optimization for AQEC codes that were previously intractable due to the curse of dimensionality.

Wu, Jing [Fermilab] (ORCID:0000000249460732)↗

DOE OSTI2023

CEGANN: CRYSTAL EDGE GRAPH ATTENTION NEURAL NETWORK

SF-22-156 Machine learning (ML) models and applications in materials design and discovery typically involve the use of feature representations or descriptors followed by a learning algorithm that maps them to user desired properties of interest. Most popular mathematical formulation-based descriptors are not unique across atomic environments and suffer from transferability issues across different application domains and/or material classes. The CEGANN code provides a unified interface to facilitate material characterization across materials across multiple scales (from atomic to mesoscale) and diverse classes of materials ranging from metals oxides, non-metals, and even hierarchical materials such as zeolites and semi ordered materials such as mesophases. CEGANN implements a Graph Attention Network (GAT) type convolution architecture. The details of network architecture can be found in the paper https://doi.org/10.48550/arXiv.2207.10168. The software comes with pretrained examples and dataset for the classification of the following representative systems: (1) Structure-level representation such as space group (2) Structural dimensionality (e.g., bulk, 2D, clusters etc.) (3) Grain boundary identification (4) Nucleation and growth of a zeolite polymorph (5) Characterization of binary mesophases and their phase transitions (6) Growth of ice. The code is written in python programming language.

CHAN, HENRYT↗

DOE OSTI2026

Leveraging Qubit Loss Detection in Fault-Tolerant Quantum Algorithms

Qubit loss errors constitute a dominant source of noise in many quantum hardware systems, particularly in neutral-atom quantum computers. We develop a theoretical framework to effectively detect and correct loss errors in logical algorithms and leverage such loss information in decoding. Considering general quantum error correction codes and logical circuits, we introduce a delayed-erasure decoder for experimentally motivated error models which leverages information from delayed loss detection to accurately correct loss errors, even when the precise moment of the error is unknown. Using this decoder, we identify strategies for detecting and correcting loss errors based on the logical circuit structure. For deep circuits prior to logical measurement, we explore methods to integrate loss detection into syndrome extraction with minimal overhead, identifying optimal strategies depending on the qubit loss fraction in the noise and hardware capabilities. In contrast, we find that many key algorithmic subroutines involve frequent gate teleportation, shortening the circuit depth before logical measurement and naturally replacing qubits with no additional experimental overhead. We simulate this setting using a toy model algorithm for small-angle synthesis and find a significant performance improvement as the loss fraction increases. These results provide a path forward for advancing large-scale fault-tolerant quantum computation in systems with loss error detection.

atoms↗

DOE OSTI2023

Solution and sensitivity analysis of nonlinear equations using a hypercomplex-variable Newton-Raphson method

Here, the classical Newton-Raphson (NR) method for solving nonlinear equations is enhanced in two ways through the use of hypercomplex variables and algebra. In particular, i) the Jacobian is computed in a highly accurate and automated way, and ii) the derivative of the solution to the nonlinear equations is computed with respect to any parameter contained within the system of equations. These advances provide two significant enhancements in that it is straightforward to provide an accurate Jacobian and to construct a reduced order model (ROM) of arbitrary order with respect to any parameter of the system. The ROM can then be used to approximate the solution for other parameter values without requiring additional solutions of the nonlinear equations. Several case studies are presented including 1D and 2D academic examples with fully functioning Python code provided. Additionally, a case of study of the catenary of an elastic cable subject to its own weight and a vertical point load. Derivatives up to 10th order were computed with respect to material, loading, and geometrical parameters. The derivatives were used to generate reduced order models of the cable deformation and reaction forces at its ends with respect to multiple input parameters. Results show that from a single hypercomplex evaluation of the cable under a single vertical point load, it is possible to generate an accurate reduced order model capable of predicting the cable deformation with 1.5 times the load in the opposite direction and with 3.5 times the load in the same direction without resolving the system of equations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Reaction Temperature Manipulation as a Process Intensification Approach for CO 2 Absorption

Reactor temperature manipulation to increase product yields of chemical reactions is a known technique used in many industrial processes. In the case of exothermic chemical reactions, the well-known Le Chatelier’s principle predicts that a decrease in temperature will displace the chemical reaction toward the formation of products by increasing the value of the equilibrium constant. The reverse is true for endothermic reactions. Reactor temperature manipulation in an industrial system, however, affects the values of many variables, including physical properties, transport parameters, reaction kinetic parameters, etc. In the case of reactive absorption, some variables change with increasing temperatures due to solute absorption, while others change in such a way that the solute absorption rate decreases. For example, temperature drop increases product formation for exothermic reactions but reduces the value of transport parameters, leading to decreasing interfacial concentrations and absorption rates. Therefore, temperature manipulation strategies must be designed carefully to achieve the process goals. In this work, we theoretically study the use of temperature as a tool to increase CO 2 absorption by solvents in a semi-batch reactor. A computer code has been developed and validated using reported experimental data. Calculated results demonstrate an increase in absorbed CO 2 of more than 28% with respect to the highest temperature used. Despite high agitation and high gas flow rate, the system is mass transfer controlled at short times, becoming kinetically controlled as time increases. An operating strategy to decrease cooling energy costs is also proposed. This study reveals that reactor temperature manipulation can be an effective process to improve CO 2 absorption by solvents in two-phase semi-batch reactors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

A nonhydrostatic formulation for MPAS-Ocean

The Model for Prediction Across Scales-Ocean (MPAS-Ocean) is an open-source, global ocean model and is one component of a family of climate models within the MPAS framework, including atmosphere, sea-ice, and land-ice models. Here, in this work, a new formulation for the ocean model is presented that solves the nonhydrostatic, incompressible Boussinesq equations on an unstructured, staggered, z-level grid. The introduction of this nonhydrostatic capability is necessary for the resolution of internal wave dynamics and large eddy simulations. Compared to the standard, hydrostatic formulation, a nonhydrostatic pressure solver and a vertical momentum equation are added, where the PETSc (Portable Extensible Toolkit for Scientific Computation) library is used for the inversion of a large sparse system for the nonhydrostatic pressure. Numerical results on a stratified seiche, internal solitary wave, overflow and lock-exchange test cases are presented, and the parallel efficiency of the code is evaluated using up to 1024 processors.

3D Poisson equation↗

DOE OSTI2025

A nonhydrostatic formulation for MPAS-Ocean

3D Poisson equation↗

DOE OSTI2024

Statistical data analysis of x-ray spectroscopy data enabled by neural network accelerated Bayesian inference

Bayesian inference applied to x-ray spectroscopy data analysis enables uncertainty quantification necessary to rigorously test theoretical models. However, when comparing to data, detailed atomic physics and radiation transfer calculations of x-ray emission from non-uniform plasma conditions are typically too slow to be performed in line with statistical sampling methods, such as Markov Chain Monte Carlo sampling. Furthermore, differences in transition energies and x-ray opacities often make direct comparisons between simulated and measured spectra unreliable. Here, we present a spectral decomposition method that allows for corrections to line positions and bound–bound opacities to best fit experimental data, with the goal of providing quantitative feedback to improve the underlying theoretical models and guide future experiments. In this work, we use a neural network (NN) surrogate model to replace spectral calculations of isobaric hot-spots created in Kr-doped implosions at the National Ignition Facility. The NN was trained on calculations of x-ray spectra using an isobaric hot-spot model post-processed with Cretin, a multi-species atomic kinetics and radiation code. The speedup provided by the NN model to generate x-ray emission spectra enables statistical analysis of parameterized models with sufficient detail to accurately represent the physical system and extract the plasma parameters of interest.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

3D simulations of inertial confinement fusion implosions part 1: inline modeling of polarized cross beam energy transfer and subsequent drive anomalies on OMEGA and NIF

Inertial confinement fusion experiments are sensitive to cross-beam energy transfer (CBET), a laser-plasma instability that redistributes laser energy in the coronal plasma through self-generated ion acoustic wave (IAW) gratings. The detailed CBET coupling depends on the polarization state of the crossing wavefields. CBET itself can also scramble the beam polarizations by inducing ellipticity through the IAW grating, and rotating the seed polarization toward that of the pump. We develop a ray-based model that describes the polarized CBET coupling and that is compatible with the framework of 3D inline radiative hydrodynamics simulations. The model is implemented in the ASTER/IFRIIT code and verified against an academic test case and an offline polarized CBET post-processor. It is then applied to the detailed configuration of the distributed polarization rotator system on OMEGA, where results highlight how polarized CBET induces significant low modes in the collisional absorption source term. Finally, the modeling is applied to a simple indirect-drive configuration, comparing CBET calculations with 96 unpolarized or polarized beams with 24 unpolarized quads. It is shown that these cases produce similar power amplification per cone of beams grouped with similar polar angles. However, the 96 beam geometry itself is found to reduce azimuthal variations in quad power after the interaction and favors beams with larger polar angles within the cones, an effect that is amplified by the polarized CBET. Application of the model to inline calculations of OMEGA implosions are presented in a companion paper.

3D inline modeling↗

DOE OSTI2021

HDEV Depot Load Profile Generation Code (Code to Generate Heavy-Duty Electric Truck Depot Load Profiles) [SWR-21-72]

Code developed to generate heavy-duty electric truck depot load profiles for the study, "Heavy-Duty Truck Electrification and the Impacts of Depot Charging on Electricity Distribution Systems", by Borlaug et al., published in 2021. This software is provided as-is without dedicated support. The programming environment for this study may be reproduced with conda (installed via the Anaconda website): conda env create -f environment.yml To activate the environment: conda activate hdev-depot-charging-2021

Borlaug, Brennan↗

DOE OSTI2023

Hpc Natural Language Understanding (nlu) Dataset

This code provides natural language annotation and labels for multiple activities in high performance. The purpose is to enable machine learning for natural language processing algorithms with high performance computing systems.

Biggs, BrandonS↗

DOE OSTI2023

CoSMo - Shell Model Code

CoSMo is a comprehensive shell model code suite designed for nuclear shell model and configuration interaction calculations. Its highly structured and templated nature allows for flexibility and ease in applications, including those to open quantum systems with non-Hermitian Hamiltonians, clustering, and time-dependent dynamics.

Volya, Alexander↗

DOE OSTI2022

SAS4A/SASSYS-1 Validation with the EBR-II Tests SHRT-17 and SHRT-45R

The EBR-II sodium-cooled fast reactor supported a wide range of fast reactor research activities. The final fifteen years of operations at EBR-II were used for experiments and tests to demonstrate the importance of passive safety in liquid metal reactors and the capability of such systems to provide strong passive responses during off-normal conditions. The Shutdown Heat Removal Test program at EBR-II provided test data supporting the validation of computer codes for design, licensing, and operation of LMRs, among other objectives. The program included nearly sixty tests, most of which were protected and unprotected loss of flow and loss of heat sink tests run at various initial powers and flow rates.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

HEPA Filter Age Evaluation Report

In 2020, PNNL completed a literature search for high-efficiency particulate air (HEPA) filter age information. HEPA filters are used in many operations to remove particulate matter from effluent exhaust streams. They are thought to degrade over time both during proper storage and during normal operational service; however, the rate at which the filters degrade remains unknown. This brings into question if age is an adequate indicator of HEPA filter performance. Data from six previous reports were obtained from the literature search and combined to create a data set of 1600 operating filters. Filter usage was identified from multiple facilities. The various types of filters (e.g., axial flow, self-contained, and standard 24 x 24 x 11.5 inches; and both separator and separatorless) reported were constructed to the requirements Section FC (HEPA Filters) or Section FK (Special HEPA Filters) of the American Society of Mechanical Engineers AG-1 code. Filters were presumed to have continuously met the operational criteria and in particular passed both annual efficiency tests and annual DP measurements. The environmental conditions within the exhaust system were also assumed adequate for long-term filter operation. The data, by the nature of the reports, excludes rejected filters from quality assurance evaluations, intake, or installation testing. The collective data set shows over half of were operating past the current 10-year Department of Energy (DOE) limit. Data was evaluated for age lifetime using a linear trendline, survival function, probability functions, and failure rate; financial impacts were also addressed. This report supports the notion that HEPA filters can operate safely and efficiently under proper maintenance well past the 10-year lifetime established by DOE. Using the results of the four age evaluation approaches, they collectively point to the reasonableness of an operating HEPA filter lifetime of 20 years. The results are not necessarily definitive, but nevertheless, they are promising. The analysis provides reasonable assurance that when implemented using a graded approach with well-defined performance and operational requirements, extending the service life for HEPA filters beyond 10 years is low risk.

42 ENGINEERING↗