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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Search for a muonphilic scalar X 0 or vector X 1 via J / ψ → μ + μ − + invisible decays at BESIII

A light scalar X 0 or vector X 1 particles have been introduced as a possible explanation for the ( g − 2 ) μ anomaly and dark matter phenomena. Using ( 8.998 ± 0.039 ) × 10 9 J / ψ events collected by the BESIII detector, we search for a light muon philic scalar X 0 or vector X 1 in the processes J / ψ → μ + μ − X 0 , 1 with X 0 , 1 invisible decays. No obvious signal is found, and the upper limits on the coupling g 0 , 1 ′ between the muon and the X 0 , 1 particles are set to be between 1.1 × 10 − 3 and 1.0 × 10 − 2 for the X 0 , 1 mass in the range of 1 < M ( X 0 , 1 ) < 1000 MeV / c 2 at 90% credibility level. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2024

Nucleon axial-vector form factor and radius from future neutrino experiments

Precision measurements of antineutrino elastic scattering on hydrogen from future neutrino experiments offer a unique opportunity to access the low-energy structure of protons and neutrons. We discuss the determination of the nucleon axial-vector form factor and radius from antineutrino interactions on hydrogen that can be collected at the future Long-Baseline Neutrino Facility and study the sources of theoretical and experimental uncertainties. The projected accuracy would improve existing measurements by 1 order of magnitude and be competitive with contemporary lattice-QCD determinations, potentially helping to resolve the corresponding tension with measurements from (anti)neutrino elastic scattering on deuterium. We find that the current knowledge of the nucleon vector form factors could be one of the dominant sources of uncertainty. We also evaluate the constraints that can be simultaneously obtained on the absolute ν ¯ μ flux normalization. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Mechanism of endosomal escape by p H -responsive nucleic-acid vectors

Successful intracellular delivery of nucleic acids (NAs) hinges on many factors, one of them being NAs’ efficacious escape from endosomes. As competent NA vectors, pH-responsive gemini surfactants (GSs) might achieve high efficacy by facilitating endosomal escape. However, how the GSs assist the escape remains debated as many proposed mechanisms still lack experimental support, which hinders replication and further improvement of the efficient delivery. Here, via UV, fluorescence spectroscopy, and small-angle neutron scattering (SANS), we examined a pH-responsive GS's and a pH-unresponsive GS's capabilities to compact DNA and withstand binding competition, and their interactions with model endosomal and lysosomal membranes, at varied pHs. Acidification-driven enhancement of DNA-compaction capability and of stability against binding competition were found specific to the pH-responsive GS. Alongside the pH-responsive GS's structural perturbation to the membranes as observed with SANS, the features suggest that pH-responsive GSs facilitate endosomal escape by releasing excess GS molecules from DNA-GS complexes upon acidification in endosome maturation, with the released GS molecules disrupting endosomal and lysosomal membranes and thereby assisting the escape. Here a general design principle for NA vectors is proposed on the basis of this experimental finding.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Spin Alignment of Vector Mesons in Heavy-Ion Collisions

Polarized quarks and antiquarks in high-energy heavy-ion collisions can lead to the spin alignment of vector mesons formed by quark coalescence. Here, using the relativistic spin Boltzmann equation for vector mesons derived from Kadanoff-Baym equations with an effective quark-meson model for strong interaction and quark coalescence model for hadronizaton, we calculate the spin density matrix element $ρ_{00}$ for Φ mesons and show that anisotropies of local field correlations with respect to the spin quantization direction lead to Φ meson's spin alignment. We propose that the local correlation or fluctuation of Φ fields is the dominant mechanism for the observed Φ meson's spin alignment and its strength can be extracted from experimental data as functions of collision energies. The calculated transverse momentum dependence of $ρ_{00}$ agrees with STAR's data. We further predict the azimuthal angle dependence of $ρ_{00}$ which can be tested in future experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Study of High-Transverse-Momentum Higgs Boson Production in Association with a Vector Boson in the qqbb Final State with the ATLAS Detector

This Letter presents the first study of Higgs boson production in association with a vector boson (V=W or Z) in the fully hadronic qqbb final state using data recorded by the ATLAS detector at the LHC in proton-proton collisions at $\sqrt{s}$=13 TeV and corresponding to an integrated luminosity of 137 fb –1 . The vector bosons and Higgs bosons are each reconstructed as large-radius jets and tagged using jet substructure techniques. Dedicated tagging algorithms exploiting b-tagging properties are used to identify jets consistent with Higgs bosons decaying into $b\bar{b}$. Dominant backgrounds from multijet production are determined directly from the data, and a likelihood fit to the jet mass distribution of Higgs boson candidates is used to extract the number of signal events. The VH production cross section is measured inclusively and differentially in several ranges of Higgs boson transverse momentum: 250–450, 450–650, and greater than 650 GeV. The inclusive signal yield relative to the standard model expectation is observed to be μ=1.4$^{+1.0}_{–0.9}$ and the corresponding cross section is 3.1±1.3⁢(stat)$^{+1.8}_{–1.4}$(syst.) pb.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Determination of the Relative Sign of the Higgs Boson Couplings to W and Z Bosons Using WH Production via Vector-Boson Fusion with the ATLAS Detector

The associated production of Higgs and W bosons via vector-boson fusion is highly sensitive to the relative sign of the Higgs boson couplings to W and Z bosons. In this Letter, two searches for this process are presented, using 140 fb -1 of proton-proton collision data at $\sqrt{s} =$ 13 TeV recorded by the ATLAS detector at the LHC. The first search targets scenarios with opposite-sign couplings of the W and Z bosons to the Higgs boson, while the second targets standard model-like scenarios with same-sign couplings. Both analyses consider Higgs boson decays into a pair of b quarks and W boson decays with an electron or muon. The data exclude the opposite-sign coupling hypothesis with a significance beyond 5⁢σ, and the observed (expected) upper limit set on the cross section for vector-boson fusion W⁢H production is 9.0 (8.7) times the standard model value at 95% confidence level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Cosmic structure strikes back: The elimination of vector-mediated nonstandard interaction models as a mechanism for sterile neutrino dark matter production

We revisit sterile neutrino production enabled by nonstandard interactions (NSIs) among active neutrinos mediated by new bosons. We focus on vector mediators, including neutrinophilic, gauged 𝐿 𝜇 −𝐿 𝜏 , and 𝐵−𝐿 realizations, that modify in-medium dispersion and scattering, thereby altering the active-sterile conversion history. Building on a novel production framework with NSI thermal potentials and collision integrals, we compute nonthermal phase-space distributions across sterile neutrino mixing and NSI parameters and map each point to an equivalent thermal warm dark matter particle mass 𝑚 th via linear theory transfer function fitting with the cosmological structure formation Boltzmann solver. This enables a direct reinterpretation of state-of-the-art structure formation limits from Milky Way satellites, strong lensing, and the Lyman-𝛼 forest. These limits, in conjunction with x-ray decay searches, as well as results from a wide variety of particle physics experiments allow for a more complete examination of these models. We find that these vector-mediated models are ruled out when the full combination of current constraints, listed above, are taken into account. NSI scalar-mediated models and models with low reheating temperatures remain viable.

cosmology↗
DOE OSTI2022

Performance of an Astrophysical Radiation Hydrodynamics Code under Scalable Vector Extension Optimization

We present results of a performance study of an astrophysical radiation hydrodynamics code, V2D, on the Arm-based A64FX processor developed by Fujitsu. The code solves sparse linear systems, a task for which the A64FX architecture should be well suited. Here, we performed the performance analysis study on Ookami, an Apollo 80 platform utilizing the A64FX processor. We explored several compilers and performance anal-ysis packages and found the code did not perform as expected under scalable vector extension optimization, suggesting that a “deeper dive” into analyzing the code is worthwhile. However, a simple driver program that exercised basic sparse linear algebra routines used by V2D did show significant speedup with the use of the scalable vector extension optimization. We present the initial results from the study which used V2D on a relatively simple test problem that emphasized the repeated solution of sparse linear systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Sparse Binary Matrix-Vector Multiplication on Neuromorphic Computers

Neuromorphic computers offer the opportunity for low-power, efficient computation. Though they have been primarily applied to neural network tasks, there is also the opportunity to leverage the inherent characteristics of neuromorphic computers (low power, massive parallelism, collocated processing and memory) to perform non-neural network tasks. Here, we demonstrate how an approach for performing sparse binary matrix-vector multiplication on neuromorphic computers. We describe the approach, which relies on the connection between binary matrix-vector multiplication and breadth first search, and we introduce the algorithm for performing this calculation in a neuromorphic way. We validate the approach in simulation. Finally, we provide a discussion of the runtime of this algorithm and discuss where neuromorphic computers in the future may have a computational advantage when performing this computation.

Schuman, Catherine↗
DOE OSTI2025

Measurements of Higgs boson production via gluon–gluon fusion and vector-boson fusion using $H\rightarrow WW^*\rightarrow \ell \nu \ell \nu$ decays in pp collisions with the ATLAS detector and their effective field theory interpretations

Higgs boson production cross-sections via gluon–gluon fusion and vector-boson fusion in proton–proton collisions are measured in the $H\rightarrow WW^*\rightarrow \ell \nu \ell \nu$ decay channel. The Large Hadron Collider delivered proton–proton collisions at a centre-of-mass energy of 13 TeV between 2015 and 2018, which were recorded by the ATLAS detector, corresponding to an integrated luminosity of $140\,\text {fb}^{-1}.$ The total cross-sections for Higgs boson production by gluon–gluon fusion and vector-boson fusion times the $H\rightarrow WW^*$ branching ratio are measured to be $12.4^{+1.3}_{-1.2}\,\text {pb}$ and $0.79^{+0.18}_{-0.16}\,\text {pb},$ respectively, in agreement with the Standard Model predictions. Higgs boson production is further characterised through measurements of Simplified Template Cross-Sections in a total of fifteen kinematic fiducial regions. A new scheme of kinematic fiducial regions has been introduced to enhance the sensitivity to CP-violating effects in Higgs boson interactions. Both schemes are used to constrain CP-even and CP-odd dimension-six operators in the Standard Model effective field theory.

Aad, G. [CPPM, Aix-Marseille Université, CNRS/IN2P↗
DOE OSTI2026

VECTOR Phase 1 Dataset: CAV Trajectory and Energy Consumption Records

This dataset contains benchmark experimental data from Phase 1 of the VECTOR project, focusing on the energy impact of CAV hardware components. The dataset includes vehicle trajectory data (speed and position) and corresponding energy consumption records collected from a CAV platform equipped with lidar, cameras, onboard computation units, and communication modules. The primary objective is to quantify the baseline energy consumption attributable to sensing and computing systems, independent of any advanced cooperative control strategies. During experiments, the leading vehicle followed a predetermined velocity profile, and the following CAV mirrored this trajectory using a basic car-following control to ensure consistent driving behavior. This setup enables a reliable benchmark for assessing the energy cost introduced by onboard CDA hardware (e.g., lidar and GPU-based processing). The dataset is essential for evaluating energy baselines and supports future comparative studies involving additional cooperative strategies. ![system img](system.png) ![vector img](vector.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Updates to Relevance Vector Machine: Multiclass Classification, Variable Selection, and Proof-of-Concept Application to Safeguards Fresh Fuel Verification using List-Mode Neutron Collar Data

To expand the capabilities of safeguards authorities to verify the integrity of fresh fuel assemblies, Oak Ridge National Laboratory has retrofit the existing electronics of the JCC-71 uranium neutron coincidence collar, which contains 18 3 He neutron detectors and an external 241 AmLi(α, n) neutron interrogation source arranged to surround a fresh nuclear fuel assembly. The new electronics system allows analysts to record list-mode neutron multiplicity data in addition to the singles and doubles rates that are currently measured. Based on previous proof-of-concept research, analysis of these new data will identify off-normal fuel configurations in an assembly and characterize or localize the specific partial fuel defects. The purpose of this report it to document the analysis algorithm development and then to demonstrate its capability for the safeguards verification of fresh fuel assemblies using list mode neutron collar data. To analyze the complex list-mode data collected with the upgraded uranium neutron collar, multivariate classification algorithms are being developed using a novel classification method, the relevance vector machine. This approach may be applied to multiclass problems to estimate the probability that test data belongs to one of many possible classes of data. In addition, our method identifies the most useful variables/channels for making predictions, which illuminates the basis for the model’s predictions, and this interpretability is largely unique among data analytics methods. Variable selection occurs during model training and parameter tuning and does not need any external hyperparameter tuning routines. Finally, we apply the modified relevance vector machine to a simulated dataset of list-mode neutron collar data generated with the radiation transport code MCNP. The method can correctly identify off-normal fuel configurations, categorize the data according to four fuel defect scenarios, and rank the channels in the data according to prediction utility. For nuclear safeguards applications, it is concluded that this method has the potential to increase the sensitivity and reliability to detect missing fuel rods from a standard 17 x 17 Pressurized Water Reactor (PWR) fresh fuel assembly. Within this analysis, “off-normal” (i.e., missing fuel rods) were correctly classified in 17 simulated test scenarios with one quarter (25%) of the fresh fuel rods missing using a training data set of 58 simulated measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Vectorization of Dynamic Subgraphs via Generative Models (Final Report)

An important class of data analysis tasks stem from comparing subsets of connected records within massive sets of complex relational data. A common approach is to represent each set of connected records with a small graph, or set of data entities (graph vertices) and their relationships (graph edges), and efficient methods to gauge similarity for pairs of graphs are of high interest. This project concentrated on dynamic graphs, where each edge record has an associated timestamp denoting the time of observation. Pre-existing techniques for comparing dynamic graphs concentrate on either computing graph edit distance (number of vertex and edge deletion, addition, and timestamp modifications) or vectorizing the graph with counts of a limited set of dynamic graph motifs (tiny fundamental subgraphs) and computing distances between the vectors. These approaches are less able to see similarities in graphs that are fairly different in size but come from identical graph generation processes. The motif counting approach can be improved for graphs from the same process, but suffers from requiring many types of motifs meaning it is expensive. Moreover, many motifs are not present for small graphs, meaning realizing a a much larger graph came from the same process is difficult.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

New Jet Tagging Techniques in Vector Boson Scattering (VBS) WV Analysis in the Semi-Leptonic Channel with the CMS Experiment

The first evidence for the electroweak vector boson scattering in the lνqq¯ decay channel of two weak vector bosons WV (V=W, Z), produced in association with two parton jets, was reported in 2021 by the CMS experiment in proton-proton collisions at √s = 13 TeV, collected during 2016-2018, with an integrated luminosity of 138 f b −1 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Robust Vector BOTDA Signal Processing with Probabilistic Machine Learning

This paper presents a novel probabilistic machine learning (PML) framework to estimate the Brillouin frequency shift (BFS) from both Brillouin gain and phase spectra of a vector Brillouin optical time-domain analysis (VBOTDA). The PML framework is used to predict the Brillouin frequency shift (BFS) along the fiber and to assess its predictive uncertainty. We compare the predictions obtained from the proposed PML model with a conventional curve fitting method and evaluate the BFS uncertainty and data processing time for both methods. The proposed method is demonstrated using two BOTDA systems: (i) a BOTDA system with a 10 km sensing fiber and (ii) a vector BOTDA with a 25 km sensing fiber. The PML framework provides a pathway to enhance the VBOTDA system performance.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

A VECTOR ANALYTICAL FRAMEWORK FOR POPULATION MODELING

We propose a vector alternative to the typical raster based population modeling framework. When compared with rasters, vectors are more precise, have the ability to hold more information, and are more conducive to areal constructs such as building and parcel outlines. While rasters have traditionally provided computational efficiency, much of this efficiency is reduced at finer resolutions and computational resources are more plentiful today. Herein we describe the approach and implementation methodology. We also describe the output data stack for the United States and provide examples and applications.

Moehl, Jessica↗