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All sources NASA NTRS DOE OSTI

DOE OSTI2024

Applying Machine‐Learning Methods to Laser Acceleration of Protons: Lessons Learned From Synthetic Data

ABSTRACT In this study, we consider three different machine‐learning methods—a three‐hidden‐layer neural network, support vector regression, and Gaussian process regression—and compare how well they can learn from a synthetic data set for proton acceleration in the Target Normal Sheath Acceleration regime. The synthetic data set was generated from a previously published theoretical model by Fuchs et al. 2005 that we modified. Once trained, these machine‐learning methods can assist with efforts to maximize the peak proton energy, or with the more general problem of configuring the laser system to produce a proton energy spectrum with desired characteristics. In our study, we focus on both the accuracy of the machine‐learning methods and the performance on one GPU including memory consumption. Although it is arguably the least sophisticated machine‐learning model we considered, support vector regression performed very well in our tests.

Desai, Ronak↗

DOE OSTI2024

Macroscopic Traffic Modeling Using Probe Vehicle Data: A Machine Learning Approach

Abstract The macroscopic fundamental diagram (MFD) captures an orderly relationship among traffic flow, density, and speed at the network level. It is a simple yet powerful tool for modeling traffic dynamics in large urban networks with broad application in traffic control and management. However, empirically derived MFDs in urban regions require high-resolution traffic data from the network. Having the network flow and vehicular density estimated at the (granular) census tract level using vehicle probe data, we apply machine learning methods to predict the MFDs across U.S. urban areas and capture the impacts of location-specific input features on the network flow–density relationships at a large scale. The results show that, among the four tested machine learning approaches (Random Forest, XGBoost, Support Vector Machine, and Neural Network), XGBoost delivers the best performance in predicting network traffic flow based on vehicular density and location attributes. Using interaction Shapley Additive explanation (SHAP) values and partial correlation analysis, we examine the factors influencing MFD shapes across different locations. Our empirical findings reveal that across U.S. urban areas, network topology, transportation infrastructure, and land use are primary factors shaping MFD curves, while demand and trip-related factors play a lesser role. Specifically, higher ranking roads, centrality, and development levels correlate positively with network capacity and critical density, whereas negative associations are observed for network connectivity, mixed-use development, and road roughness levels.

Jin, Ling↗

DOE OSTI2024

Fiducial and differential cross-section measurements of electroweak $W\gamma jj$ production in $pp$ collisions at $\sqrt{s} = 13$ TeV with the ATLAS detector

The observation of the electroweak production of a W boson and a photon in association with two jets, using pp collision data at the Large Hadron Collider at a centre of mass energy of $\sqrt{s} = 13$ TeV, is reported. The data were recorded by the ATLAS experiment from 2015 to 2018 and correspond to an integrated luminosity of 140 fb -1 . This process is sensitive to the quartic gauge boson couplings via the vector boson scattering mechanism and provides a stringent test of the electroweak sector of the Standard Model. Events are selected if they contain one electron or muon, missing transverse momentum, at least one photon, and two jets. Multivariate techniques are used to distinguish the electroweak $W\gamma jj$ process from irreducible background processes. The observed significance of the electroweak $W\gamma jj$ process is well above six standard deviations, compared to an expected significance of 6.3 standard deviations. Fiducial and differential cross sections are measured in a fiducial phase space close to the detector acceptance, which are in reasonable agreement with leading order Standard Model predictions from MADGRAPH5+PYTHIA8 and SHERPA. The results are used to constrain new physics effects in the context of an effective field theory.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

A New Vehicle-to-Vehicle Communication System: Visual-Enhanced Cooperative Traffic Operations

The advent of Connected and Autonomous Vehicles (CAVs) has highlighted the necessity for robust communication systems between vehicles and their environment. This study introduces a novel vehicle-to-vehicle (V2V) communication system, termed the Visual-Enhanced Cooperative Traffic Operations (VECTOR) system. The VECTOR system addresses the need for robust communication by converting dynamic data (including velocity and yaw angle data) into binary code, which is displayed on an LED panel mounted on the top of the vehicle. Following vehicles detect this panel and decode the information using a camera, implementing a visual-based communication method. VECTOR system employs a comprehensive five-module process. Initially, polynomial fitting techniques are applied to velocity data over fixed time intervals using third-degree polynomials, with validation via R² and MSE metrics. The second module converts velocity and yaw angle data into binary form, thereby enhancing detection and processing efficiency. The third module focuses on improving detection stability across various environmental conditions to enhance traffic safety. The fourth module decodes the binary data back into trajectory information, ensuring the fidelity of velocity and yaw angles. The final module integrates eco-control through the VECTOR system, employing advanced control algorithms to minimize energy consumption in CAVs. Experimental evaluations conducted using a modified CAV test platform based on the Lincoln MKZ demonstrate the feasibility and efficiency of the VECTOR system, achieving a 75% R-squared accuracy rate in replicating original velocity data. This methodology not only highlights potential applications but also underscores significant implications for advancing CAV technology.

Ma, Ke↗

DOE OSTI2025

$η(') → π0γγ$ decays: Test of meson exchange models and searches of leptophobic $B$ bosons

We analyze the vector and scalar meson exchange contributions to the doubly radiative decays $η(') → π0γγ$ and $η → ηγγ$, and study the sensitivity of these decays to a leptophobic B boson in the sub-GeV mass range. Our results are relevant for studies of these decays at existing (A2, BESIII, KLOE-2) and forthcoming $η/η'$-factories, such as the JEF and REDTOP experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Electroweak, QCD and flavour physics studies with ATLAS data from Run 2 of the LHC

A of precision measurements sensitive to electroweak, QCD and quark-flavour effects performed by the ATLAS Collaboration at the Large Hadron Collider is reported. The measurements are predominantly performed on proton–proton ( p p ) collision data recorded at a centre-of-mass energy of 13 TeV taken from 2015 to 2018, with an integrated luminosity of up to 140 fb−1, with some results based on p p and Pb+Pb data recorded at lower nucleon centre-of-mass energies. The results cover a wide range of topics, from strong production of particles at low energies and the spectroscopy of hadrons to perturbative QCD with hadronic jets and electroweak and strong production of single and multiple vector bosons. They provide precise measurements of fundamental constants and stringent tests of the Standard Model with unprecedented precision and in energy ranges never explored before. They are also used to explore the proton structure and to perform model-independent searches for new physics.

Source record↗

DOE OSTI2026

Identification of proteins influencing CRISPR-associated transposases for enhanced genome editing

CRISPR-associated transposases (CASTs) hold tremendous potential for microbial genome editing because of their ability to integrate large DNA cargos in a programmable, site-specific manner. However, their widespread application has been hindered by poorly understood host factor requirements for transposition. To address this gap, we conducted the first genome-wide screen for host factors affecting Vibrio cholerae CAST (VchCAST) activity using an Escherichia coli RB-TnSeq library and identified 15 genes affecting VchCAST transposition. Of these, seven factors were validated to improve VchCAST activity, and two were inhibitory. Guided by the identification of homologous recombination effectors, RecD and RecA, we tested the λ-Red recombineering system in our VchCAST editing vectors and increased editing efficiency by 55.2-fold in E. coli, 5.6-fold in Pseudomonas putida, and 10.8-fold in Klebsiella michiganensis while maintaining high target specificity and similar insertion arrangements. This study improves the understanding of factors affecting VchCAST activity and enhances its efficiency as a bacterial genome editor.

Song, Leo C T↗

DOE OSTI2026

A tetrahedral probe constellation approach for measuring canonical momentum in self-organized laboratory plasma

To examine momentum redistribution processes and study generalized helicities during plasma relaxation in Madison Symmetric Torus, MST, reversed field pinch plasma, a new probe is being tested to measure the full 3D plasma ion flow and magnetic field vectors at four spatial locations arranged in a tetrahedral shape reminiscent of a satellite measurement constellation. These measurements permit calculation of ∇ x $\vec{u}$ and canonical momentum, where $\vec{u}$ is the plasma ion flow vector. The probe consists of four probe heads arranged in a tetrahedral pattern, with an overall probe diameter of ∼31.75 mm. The probe head diameter is ∼1.0 cm, which is of the order of the ion Larmor radius. Each head has four molybdenum electrodes, also arranged in tetrahedral geometry, which are biased relative to a common return electrode, using four power supplies (one for each head), to measure the local ion flow. Additionally, each head has three orthogonal magnetic pickup coils within it to measure equilibrium and fluctuating magnetic fields.

Physics - Plasma physics↗

DOE OSTI2025

Machine learning-powered data cleaning for LEGEND: a semi-supervised approach using affinity propagation and support vector machines

Neutrinoless double-beta decay ($0\nu\beta\beta$) is a rare nuclear process that, if observed, will provide insight into the nature of neutrinos and help explain the matter-antimatter asymmetry in the Universe. The large enriched germanium experiment for neutrinoless double-beta decay (LEGEND) will operate in two phases to search for $0\nu\beta\beta$. The first (second) stage will employ 200 (1000) kg of High-Purity Germanium (HPGe) enriched in 76 Ge to achieve a half-life sensitivity of 10 27 (10 28 ) years. In this study, we present a semi-supervised data-driven approach to remove non-physical events captured by HPGe detectors powered by a novel artificial intelligence model. We utilize affinity propagation to cluster waveform signals based on their shape and a support vector machine to classify them into different categories. We train, optimize, and test our model on data taken from a natural abundance HPGe detector installed in the Full Chain Test experimental stand at the University of North Carolina at Chapel Hill. We demonstrate that our model yields a maximum sacrifice of physics events of $0.024 ^{+0.004}_{-0.003} \%$ after data cleaning. Our model is being used to accelerate data cleaning development for LEGEND-200 and will serve to improve data cleaning procedures for LEGEND-1000.

artificial intelligence↗

DOE OSTI2024

Constraining Cosmology with Simulation-based inference and Optical Galaxy Cluster Abundance

We test the robustness of simulation-based inference (SBI) in the context of cosmological parameter estimation from galaxy cluster counts and masses in simulated optical datasets. We construct ``simulations'' using analytical models for the galaxy cluster halo mass function (HMF) and for the observed richness (number of observed member galaxies) to train and test the SBI method. We compare the SBI parameter posterior samples to those from an MCMC analysis that uses the same analytical models to construct predictions of the observed data vector. The two methods exhibit comparable performance, with reliable constraints derived for the primary cosmological parameters, ($\Omega_m$ and $\sigma_8$), and richness-mass relation parameters. We also perform out-of-domain tests with observables constructed from galaxy cluster-sized halos in the Quijote simulations. Again, the SBI and MCMC results have comparable posteriors, with similar uncertainties and biases. Unsurprisingly, upon evaluating the SBI method on thousands of simulated data vectors that span the parameter space, SBI exhibits worsened posterior calibration metrics in the out-of-domain application. We note that such calibration tests with MCMC is less computationally feasible and highlight the potential use of SBI to stress-test limitations of analytical models, such as in the use for constructing models for inference with MCMC.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Form factors for semi-leptonic $B_{(s)} \to D_{(s)}^∗\ell \nu_\ell$ decays

Semileptonic $B_{(s)}$ decays are of great phenomenological interestbecause they allow to extract CKM matrix elements or test lepton flavouruniversality. Taking advantage of existing data, we explore extractingform factors for vector final states using the narrow widthapproximation. Based on RBC/UKQCD's set of 2+1 flavour gauge fieldensembles with Shamir domain-wall fermion and Iwasaki gauge fieldaction, we study semileptonic $B_{(s)}$ decays using domain-wallfermions for light, strange and charm quarks, whereas bottom quarks aresimulated with the relativistic heavy quark (RHQ) action. Exploratoryresults for $B_s \to D_s^* \ell \nu_\ell$ are presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Detection and imaging of electric fields, using polarized neutrons

A method and corresponding apparatus are provided for measuring neutron spin precession in an electric field with high sensitivity suitable for practical applications in non-destructive testing, imaging, and the like. Production of a neutron beam with a polarization vector P is followed by transmitting the spin-polarized neutron beam through a sample region in which there is a target generating an electric field, polarization-analyzing the transmitted neutron beam with an analyzing direction orthogonal to P, detecting an intensity of the polarization-analyzed neutron beam; and mapping the detected neutron-beam intensity to a field-strength value for the target electric field.

Jau, Yuan-Yu↗

DOE OSTI2024

A Data-Driven Approach for High-Impedance Fault Localization in Distribution Systems

Accurate and quick identification of high-impedance faults (HIFs) is critical for the reliable operation of distribution systems. Unlike other faults in power grids, HIFs are very difficult to detect by conventional overcurrent relays due to the low fault current. Although HIFs can be affected by various factors, the voltage-current characteristics can substantially imply how the system responds to the disturbance and thus provides opportunities to effectively localize HIFs. In this work, we propose a data-driven approach for the identification of HIF events. To tackle the nonlinearity of the voltage-current trajectory, first, we formulate optimization problems to approximate the trajectory with piecewise functions. Then we collect the function features of all segments as inputs and use the support vector machine approach to efficiently identify HIFs at different locations. Numerical studies on the IEEE 123-node test feeder demonstrate the validity and accuracy of the proposed approach for real-time HIF identification.

explainable artificial intelligence↗

DOE OSTI2024

A Data-Driven Approach for High-Impedance Fault Localization in Distribution Systems: Preprint

explainable artificial intelligence↗

DOE OSTI2024

Sprain energy consequences for damage localization and fracture mechanics

The 2023 smooth Lagrangian Crack-Band Model (slCBM), inspired by the 2020 invention of the gap test, prevented spurious damage localization during fracture growth by introducing the second gradient of the displacement field vector, named the “sprain,” as the localization limiter. The key idea was that, in the finite element implementation, the displacement vector and its gradient should be treated as independent fields with the lowest ( C 0 ) continuity, constrained by a second-order Lagrange multiplier tensor. Coupled with a realistic constitutive law for triaxial softening damage, such as microplane model M7, the known limitations of the classical Crack Band Model were eliminated. Here, we show that the slCBM closely reproduces the size effect revealed by the gap test at various crack-parallel stresses. To describe it, we present an approximate corrective formula, although a strong loading-path dependence limits its applicability. Except for the rare case of zero crack-parallel stresses, the fracture predictions of the line crack models (linear elastic fracture mechanics, phase-field, extended finite element method (XFEM), cohesive crack models) can be as much as 100% in error. We argue that the localization limiter concept must be extended by including the resistance to material rotation gradients. We also show that, without this resistance, the existing strain-gradient damage theories may predict a wrong fracture pattern and have, for Mode II and III fractures, a load capacity error as much as 55%. Finally, we argue that the crack-parallel stress effect must occur in all materials, ranging from concrete to atomistically sharp cracks in crystals.

Science & Technology - Other Topics↗

DOE OSTI2024

No evidence of Bartonella infections in host-seeking Ixodes scapularis and Ixodes pacificus ticks in the United States

Background. Bartonella spp. infect a variety of vertebrates throughout the world, with generally high prevalence. Several Bartonella spp. are known to cause diverse clinical manifestations in humans and have been recognized as emerging pathogens. These bacteria are mainly transmitted by blood-sucking arthropods, such as fleas and lice. The role of ticks in the transmission of Bartonella spp. is unclear. Methods. A recently developed quadruplex polymerase chain reaction (PCR) amplicon next-generation sequencing approach that targets Bartonella-specific fragments on gltA, ssrA, rpoB, and groEL was applied to test host-seeking Ixodes scapularis ticks (n=1641; consisting of 886 nymphs and 755 adults) collected in 23 states of the eastern half of the United States and Ixodes pacificus ticks (n=966; all nymphs) collected in California in the western United States for the presence of Bartonella DNA. These species were selected because they are common human biters and serve as vectors of pathogens causing the greatest number of vector-borne diseases in the United States. Results. No Bartonella DNA was detected in any of the ticks tested by any target. Conclusions. Owing to the lack of Bartonella detection in a large number of host-seeking Ixodes spp. ticks tested across a broad geographical region, our results strongly suggest that I. scapularis and I. pacificus are unlikely to contribute more than minimally, if at all, to the transmission of Bartonella spp.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

The Dark Energy Camera All Data Everywhere cosmic shear project V: Constraints on cosmology and astrophysics from 270 million galaxies across 13,000 deg$^2$ of the sky

We present constraints on models of cosmology and astrophysics using cosmic shear data vectors from three datasets: the northern and southern Galactic cap of the Dark Energy Camera All Data Everywhere (DECADE) project, and the Dark Energy Survey (DES) Year 3. These data vectors combined consist of 270 million galaxies spread across 13,000 ${\rm deg}^2$ of the sky. We first extract constraints for $Λ$CDM cosmology and find $S_8= 0.805^{+0.019}_{-0.019}$ and $Ω_{\rm m} = 0.262^{+0.023}_{-0.036}$, which is consistent within $1.9 σ$ of constraints from the Planck satellite. Extending our analysis to dynamical dark energy models shows that lensing provides some (but still minor) improvements to existing constraints from supernovae and baryon acoustic oscillations. Finally, we study six different models for the impact of baryons on the matter power spectrum. We show the different models provide consistent constraints on baryon suppression, and associated cosmology, once the astrophysical priors are sufficiently wide. Current scale-cut approaches for mitigating baryon contamination result in a residual bias of $\approx 0.3σ$ in the $S_8, Ω_{\rm m}$ posterior. Using all scales with dedicated baryon modeling leads to negligible improvement as the new information is used solely to self-calibrate the baryon model on small scales. Additional non-lensing datasets, and/or calibrations of the baryon model, will be required to access the full statistical power of the lensing measurements. The combined dataset in this work represents the largest lensing dataset to date (most galaxies, largest area) and provides an apt testing ground for analyses of upcoming datasets from Stage IV surveys. The DECADE shear catalogs, data vectors, and likelihoods are made publicly available.

Anbajagane, D. [Chicago U., Astron. Astrophys. Ctr↗

DOE OSTI2024

Cosmic Shear Analysis in the DECam Local Volume Exploration Survey

We forecast cosmological constraints and develop a cosmic shear analysis pipeline for the DECam Local Volume Exploration Survey (DELVE). We test the effects of two different intrinsic alignment frameworks (TATT and NLA) on simulated data vectors. In addition, we examine the impact of baryon contamination and apply scale cuts to reduce its weight. We find the forecast results to be as constraining as the DES Y3 cosmological parameter measurements.

79 ASTRONOMY AND ASTROPHYSICS↗