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DOE OSTI2024

RandONets: Shallow networks with random projections for learning linear and nonlinear operators

Deep neural networks have been extensively used for the solution of both the forward and the inverse problem for dynamical systems. However, their implementation necessitates optimizing a high-dimensional space of parameters and hyperparameters. This fact, along with the requirement of substantial computational resources, pose a barrier to achieving high numerical accuracy, but also interpretability. Here, to address the above challenges, we present Random Projection-based Operator Networks (RandONets): shallow networks with random projections and tailor-made numerical analysis methods that learn accurately and fast linear and nonlinear operators. Building on previous works, we prove that RandOnets are universal approximators of linear and nonlinear operators. Due to their simplicity, RandONets provide a one-step transformation of the input space, facilitating interpretability. For the evaluation of their performance, we focus on operators of PDEs. We show, that RandONets outperform by several orders of magnitude, both in terms of numerical approximation accuracy and computational cost, the “vanilla” DeepONets. Hence, we believe that our method will trigger further developments in the field of scientific machine learning, for the development of new ‘’light”schemes that will provide high accuracy while reducing dramatically the computational cost. A MATLAB toolbox for RandONets, including demos, is available on GitHub at https://github.com/GianlucaFabiani/RandONets.

Interpretable machine learning↗

DOE OSTI2025

Summary of Working Group 7: Linear colliders

The contributions presented during the Working Group 7: Linear Colliders (WG7) sessions at the 2024 Advanced Accelerator Concepts Workshop are briefly summarized, as well as the discussions regarding a design initiative for a linear collider based on wakefield accelerator technology.

Advanced Accelerator Concepts↗

DOE OSTI2025

γIn-beam angular distribution and linear polarization measurements with GRETINA using a simple energy-ordering approach

Angular distribution and linear polarization measurements are powerful tools for inferring the spins and parities of nuclear levels. In this work, the performance of the Gamma-Ray Energy Tracking In-beam Nuclear Array (GRETINA) as a Compton polarimeter was characterized in a fusion-evaporation reaction experiment using a simple energy-ordering approach for the interaction points assigned in the signal decomposition process. A variety of multipolarities and characters for γ-ray transitions in the reaction products 25 Mg, 25 Na, and 22 Ne, formed from fusion-evaporation of an 18 O beam on a 9 Be target, were examined. The experimental angular distributions and linear polarization asymmetries were consistent with predictions using the theoretical formalism accounting for the Lorentz boost.

Angular distribution↗

DOE OSTI2025

Broadband Infrared Carbon Nanotube Linear Photodetector Arrays

Carbon nanotubes (CNTs) possess exceptional optoelectronic properties, including broadband absorption and high absorption coefficients, making them promising candidates for photodetector applications. However, conventional designs often rely on single or aligned nanotubes, which restrict device scalability and require complex fabrication techniques. Here, in this work, we address these limitations by utilizing CNT-suspended solutions to fabricate large-area photodetectors based on CNT networks via vacuum filtration and direct laser scribing. CNT networks are uniformly formed onto low-thermal-conductance polymeric filter papers that serve as substrates and mitigate the need for suspended structures, reducing the fabrication complexity and cost. The CNT films are patterned into single devices and 49-pixel linear arrays by using a laser-cutting process, enabling scalable and cost-effective production. The resulting devices operate as bolometers and exhibit broad spectral sensitivity extending from visible to midwave infrared, showing stable operation at room temperature. We further demonstrate proof-of-concept IR imaging using linear arrays.

IR imaging↗

DOE OSTI2024

Computer vision models enable mixed linear modeling to predict arbuscular mycorrhizal fungal colonization using fungal morphology

Abstract The presence of Arbuscular Mycorrhizal Fungi (AMF) in vascular land plant roots is one of the most ancient of symbioses supporting nitrogen and phosphorus exchange for photosynthetically derived carbon. Here we provide a multi-scale modeling approach to predict AMF colonization of a worldwide crop from a Recombinant Inbred Line (RIL) population derived from Sorghum bicolor and S. propinquum . The high-throughput phenotyping methods of fungal structures here rely on a Mask Region-based Convolutional Neural Network (Mask R-CNN) in computer vision for pixel-wise fungal structure segmentations and mixed linear models to explore the relations of AMF colonization, root niche, and fungal structure allocation. Models proposed capture over 95% of the variation in AMF colonization as a function of root niche and relative abundance of fungal structures in each plant. Arbuscule allocation is a significant predictor of AMF colonization among sibling plants. Arbuscules and extraradical hyphae implicated in nutrient exchange predict highest AMF colonization in the top root section. Our work demonstrates that deep learning can be used by the community for the high-throughput phenotyping of AMF in plant roots. Mixed linear modeling provides a framework for testing hypotheses about AMF colonization phenotypes as a function of root niche and fungal structure allocations.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Connected Traffic Signal Coordination Optimization Framework through Network-Wide Adaptive Linear Quadratic Regulator–Based Control Strategy

Traffic congestion in metropolitan areas causes several significant challenges, such as longer travel times, decreased productivity, increased fuel consumption and vehicle emissions, and even severe injuries during crashes. Traffic signal control is a management approach to reduce traffic congestion and allocate the appropriate right of way for safety and mobility efficiency, both in temporal and spatial domains. Here, this study proposes a network-wide adaptive signal control coordination optimization framework based on the linear quadratic regulator algorithm. The traffic flow conditions driven by signal control inputs are formulated based on their network-wide state-space representation. After modeling traffic control regulation constraints, an adaptive linear quadratic regulator algorithm is designed to maximize the network-wide total throughput under the current conditions. Optimal signal control split time durations for multiple intersections in the network are derived by solving the algebraic Riccati equation. Furthermore, the recursive least square parameter estimation method is employed to quantify dynamic traffic condition changes. To verify the effectiveness of this proposed signal control framework, both simulation and real-world experimental tests are conducted for multiple intersections in downtown Chattanooga, Tennessee, United States. In preparation for real-world experimental tests, pipelines for real-time data processing implementation and historical traffic flow data analysis are conducted. The test results demonstrate that the proposed control framework achieves a decrease in travel time by up to 19.4%, total time spent (TTS) by up to 11.9%, and relative queue balance (RQB) by up to 15.6%. The research findings indicate that the proposed signal control framework can be generalized to handle large scale signal control optimization network-wide.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Spin dynamics in linear magnetoelectric material Mn 3 Ta 2 O 8

We performed inelastic neutron scattering experiments on single crystal samples of a linear magnetoelectric material Mn 3 Ta 2 O 8 , which exhibits a collinear antiferromagnetic order, to reveal the spin dynamics. Numerous modes observed in the neutron spectra were reasonably reproduced by linear spin-wave theory on the basis of the spin Hamiltonian including eight Heisenberg interactions and an easy-plane type single-ion anisotropy. In conclusion, the presence of strong frustration was found in the identified spin Hamiltonian.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Improved Evaluation of Large Network Matrices for Linear Power Flow Within Optimization Problems

This work presents methods for evaluating the Power Transfer Distribution Factor (PTDF) and Line Outage Distribution Factor (LODF) matrices by employing sparse linear algebra for large-scale computing applications. These matrices play a critical role in many power system applications, such as the Unit Commitment Problem (UC), pre- and post-contingency power flow analysis, and transmission expansion. These matrices are typically dense, which means they require a significant amount of time and memory to be computed for large networks. However, by analyzing the structure of the matrices and their computation method, it is possible to use reduced memory methods based on sparse matrix operations. This paper shows that sparse linear algebra algorithms are faster and require less memory and time than traditional dense approaches. Additionally, we explore the effect of matrix sparsification by eliminating trailing digits on power flow calculations.

large scale↗

DOE OSTI2024

Computational study of tungsten and depleted uranium photoneutron targets for a 20 MeV electron linear accelerator

Neutron production can be realized with a high energy electron linear accelerator by using Bremsstrahlung and photoneutron converters. In this study, Monte Carlo N-Particle Code (MCNP) was used to evaluate potential photonuclear target designs for a high energy electron linear accelerator for applications such as neutron radiography and neutron resonance spectroscopy. A computational model was developed to inform a target design that would yield a high number of neutrons. It consists of a 20 MeV electron beam incident on a Bremsstrahlung target and a photonuclear target to generate neutrons. This computational model showed that a thickness of 0.75 inches for both tungsten and depleted uranium yields the most neutrons from photoneutron reactions. Saturation in the total number of generated neutrons was observed at over 0.75-inch thickness for both evaluated materials. Depleted uranium yielded approximately twice the number of neutrons overall compared to tungsten. The highest neutron surface flux for Depleted Uranium was 1.06 × 10-4 neutrons/cm2/source electron, and for Tungsten it was 5.12 × 10-5 neutrons/cm2/source electron. The optimal target design for this study’s application would consist of a 0.75 inch-thick block of depleted uranium with the length, width, and/or diameter varying dependent on application.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

Adaptive Control for Load-Following of Boiling Water Reactors Part I: Linear Systems and Fully-Observable Dynamics

Automation control is a key strategy to improve the economic competitiveness of nuclear power plants. Not only does it help reduce operational costs, but it also extends the value proposition of these plants to nontraditional markets, including unattended operations in remote villages and space. However, the dynamics of the operating environments of nuclear reactors are subject to changes over time, and there are no widely adopted methods to ensure that the automation strategy will remain effective over the extended durations required for these applications. Adaptive control is a discipline that offers the possibility to accommodate such changes online. However, it relies on mathematical assumptions that must be respected to ensure robustness and reliability. In this work, we derive an adaptive control formulation for linear systems in which all states are observable and apply it to an instance of load-follow operation for Boiling Water Reactors. We assumed uncertainty in two factors: the temperature coefficient and the control rod worth, both of which are affected over time by the evolution of the nuclear reactor core environment. With an arbitrary penalty factor of 5, we found that the mean absolute and integral time absolute errors can be reduced by more than 90%, underscoring the strength of adaptive control. To extend the application to more challenges, different uncertainties and load-follow trajectories, as well as new formulations that include non-linearity and partial observability, are currently being developed.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Birefringent Glass‐Engraved Quasi‐Linear Nanograting Metasurface Based on Self‐Organizing Process for Large Aperture High Power Laser Applications

All-glass metasurface “nanograting” structures that exhibit birefringence in the formed layer are reported. The key enabler of this work is ion beam processing at an angle sufficiently off-normal incidence, inducing self-assembly of a deposited metal layer into quasi-linear metallic features that can function as an etching mask. As a result, a fused silica metasurface, monolithic to the underlying substrate, is demonstrated at 375 nm wavelength to exhibit a phase delay angle of 30° between the principal axes. The capability of an angled etch mask replenishment process is also demonstrated for achieving deeper etch depth and for increasing the grating period, another first – to the best of the knowledge. This is the first display of a technology capable of fabricating glass-engraved near-linear grating structure with a feature-to-feature period as small as 118.6 nm. Furthermore, this technology has the potential to generate grating-like structures with periods as small as 12.4 nm, as demonstrated here with reactive ion beam processing assisted mask assembly. Furthermore, these structures are shown to have reflectivity < 0.4% across the wavelength band 350 nm – 1000 nm. Such a technology can enable laser-durable grating structures for the deep-UV and even down to soft X-ray wavelengths.

Ray, Nathan J. [Lawrence Livermore National Labora↗

DOE OSTI2024

Ab initio exploration of low–lying electronic states of linear and bent MNX + (M = Ca, Sr, Ba, Ra; X = O, S, Se, Te, Po) and their origins

High-level multireference and coupled cluster quantum calculations were employed to analyze low-lying electronic states of linear-MNX + and side-bonded-M[NX] + (M = Ca, Sr, Ba, Ra; X = O, S, Se, Te, Po) species. Their full potential energy curves (PECs), dissociation energies (D e s), geometric parameters, excitation energies (T e s), and harmonic vibrational frequencies (ω e s) are reported. The first three chemically bound electronic states of MNX + and M[NX] + are 3 Σ – , 1 Δ, 1 Σ + and 3 A", 1 A', 1 A", respectively. The 3 Σ – , 1 Δ, 1 Σ + of MNX + originate from the M + ( 2 D) + NX( 2 Π) fragments, whereas the 3 A", 1 A', 1A" states of M[NX] + dissociate to M + ( 2 S) + NX( 2 Π) as a result of avoided crossings. The MNX + and M[NX] + are real minima on the potential energy surface and their interconversions are possible. The M 2+ NX – /M 2+ [NX] – ionic structure is an accurate representation for their low-lying electronic states. The D e s of MNX + species were found to depend on the dipole moment (μ) of the corresponding NX ligands and a linear relationship between these two parameters was observed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Highly Anisotropic Drude-Weight-Reduction and Enhanced Linear-Dichroism in van der Waals Weyl Semimetal T d -MoTe 2 with Coherent Interlayer Electronic Transport

Weyl semimetal (WSM) states can be achieved by breaking spatial-inversion symmetry or time reversal symmetry. However, the anisotropy of the energy reduction contributing to the emergence of WSM states has seldom been investigated by experiments. A van der Waals metal MoTe 2 exhibits a type-II WSM phase below the monoclinic-to-orthorhombic-phase-transition temperature T c ~ 250 K. Here, in this work, a combined linearly polarized optical-spectroscopy and electrical-transport study of MoTe 2 is reported at different temperatures. The Drude components in the a-axis, b-axis, and c-axis optical conductivity spectra, together with the metallic out-of-plane and in-plane electrical resistivities, indicate the coherent inter-layer and in-plane charge transports. Moreover, the Drude weight in σ 1a (ω), rather than the Drude weights in σ 1b (ω) and σ 1c (ω), decreases dramatically below T c , which exhibits a highly anisotropic decrease in its Drude weight and thus suggests a strongly anisotropic reduction of the electronic kinetic energy in the WSM phase. Furthermore, below T c , due to the in-plane anisotropic spectral-weight transfer from Drude component to high-energy region, the in-plane inter-band-absorption anisotropy increases remarkably ≈770 meV, and has the largest value (≈0.68) of normalized linear dichroism among the reported type-II WSMs. The work sheds light on seeking new WSMs and developing novel photonic devices based on WSMs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Non-linear dynamics of jet quenching

We develop a comprehensive analytic framework for jet quenching in QCD media, based on a medium-induced parton cascade sourced by collinear virtual splittings. We show that the energy flow out of the jet cone, driven by turbulent gluon cascades, is governed by a non-linear rate equation that resums gluon splittings at arbitrary angles and is enhanced by the medium length, L. The solution of this equation sets the initial condition for a non-linear DGLAP-like evolution equation, which describes the collinear early vacuum cascade resolved by the medium at angles exceeding the medium resolution angle, θ c . For asymptotic jet energies, the medium-induced cascade displays an exponential behavior that generalizes the Poisson-like distribution of parton energy loss. This formulation enables the resummation of leading contributions in α s ln(1/R), and α s ln(R/θ c ), and powers of α s L. We briefly explore the limit of strong quenching, where analytic treatments are feasible, offering insights into the impact of parton cascades on jet quenching. These results provide guidance for future numerical simulations and analytical investigations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Small scale electron linear accelerators for industrial applications

Linear accelerators (linacs), producing electron or X-ray radiation in the MeV range, are critical tools for industrial irradiation, medical device sterilization, food pasteurization, non-destructive testing, security, medical, and many other applications. Many of these applications require compact and flexible radiation sources. In this paper, we present new technologies for small-scale electron linear accelerators and examples of their practical implementations. Furthermore, these developments include low energy accelerators with self-shielding options and form factors, ranging from cabinet-size to hand-portable generators; medium-energy accelerators for novel radiotherapy and security applications; and high-energy 10 MeV linacs capable of reaching 20–35 kW beam power for emerging industrial and phytosanitary applications

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Survey-wide asteroid discovery with a high-performance computing enabled non-linear digital tracking framework

Modern astronomical surveys detect asteroids by linking together their appearances across multiple images taken over time. This approach faces limitations in detecting faint asteroids and handling the computational complexity of trajectory linking. Here, we present a novel method that adapts “digital tracking” – traditionally used for short-term linear asteroid motion across images – to work with large-scale synoptic surveys such as the Vera Rubin Observatory Legacy Survey of Space and Time (Rubin/LSST). Our approach combines hundreds of sparse observations of individual asteroids across their non-linear orbital paths to enhance detection sensitivity by several magnitudes. To address the computational challenges of processing massive data sets and dense orbital phase spaces, we developed a specialized high-performance computing architecture. We demonstrate the effectiveness of our method through experiments that take advantage of the extensive computational resources at Lawrence Livermore National Laboratory. This work enables the detection of significantly fainter asteroids in existing and future survey data, potentially increasing the observable asteroid population by orders of magnitude across different orbital families, from near-Earth objects (NEOs) to Kuiper belt objects (KBOs).

Asteroid discovery↗

DOE OSTI2024

Stress-hybrid virtual element method on six-noded triangular meshes for compressible and nearly-incompressible linear elasticity

In this paper, we present a first-order Stress-Hybrid Virtual Element Method (SH-VEM) on six-noded triangular meshes for linear plane elasticity. Here, we adopt the Hellinger–Reissner variational principle to construct a weak equilibrium condition and a stress based projection operator. In each element, the stress projection operator is expressed in terms of the nodal displacements, which leads to a displacement based formulation. This stress-hybrid approach assumes a globally continuous displacement field while the stress field is discontinuous across each element. The stress field is initially represented by divergence-free tensor polynomials based on Airy stress functions, but we also present a formulation that uses a penalty term to enforce the element equilibrium conditions, referred to as the Penalty Stress-Hybrid Virtual Element Method (PSH-VEM). Numerical results are presented for PSH-VEM and SH-VEM, and we compare their convergence to the composite triangle FEM and B-bar VEM on benchmark problems in linear elasticity. The SH-VEM converges optimally in the L 2 norm of the displacement, energy seminorm, and the L 2 norm of hydrostatic stress. Furthermore, the results reveal that PSH-VEM converges in most cases at a faster rate than the expected optimal rate, but it requires the selection of a suitably chosen penalty parameter.

42 ENGINEERING↗

DOE OSTI2024

Interpretable, extensible linear and symbolic regression models for charge density prediction using a hierarchy of many-body correlation descriptors

Here, density functional theory (DFT) is routinely used to make electronic structure predictions for high-throughput screening of materials and molecules for technologically relevant areas, like the identification of better catalysts, electronic materials, and drug discovery. However, the DFT formalism is limited by (a) its poor (quadratic-to-quartic) scaling, and (b) the need to perform repeated eigenvalue computations of the electronic Hamiltonian as part of its self-consistent field (SCF) iteration procedure to obtain the converged ground state electron density, ρ (r). Approaches that directly predict ρ (r) of a structure with high accuracy can accelerate conventional SCF calculations and can also be used in linearly scaling methods such as orbital-free DFT. To this end, we present a procedure to predict the ground state electron density of molecular and periodic three-dimensional systems directly from the atomic structure with a particular emphasis on physical interpretability. In our framework, ρ (r) is modeled using many-body correlation descriptors that accurately capture the effects of local atomic arrangements in the neighborhood of a grid point. Our use of a linear regression scheme to fit to charge density data enables transparent analysis of the relative contributions of various types of local atomic correlations. By systematically including increasingly complex correlations, our model is shown to accurately predict ρ (r) for a variety of chemically and electronically diverse systems — amorphous Ge, Al(001) slab, crystalline Ga 2 O 3 , molecular benzene, and polyethylene. We then demonstrate a symbolic regression-based protocol to construct easily computable, interpretable features from lower-order correlations that significantly improves our electron density predictions with effectively no increase in the computational cost.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗