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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Impact of globally spin-aligned vector mesons on the search for the chiral magnetic effect in heavy-ion collisions

In high-energy heavy-ion collisions, the chiral magnetic effect (CME) is predicted to arise from the interplay between the chirality imbalance of quarks in the nuclear medium and the intense magnetic field, and will cause a charge separation along the magnetic field direction. While the search for the CME is still ongoing in experiments at Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC), the CME-sensitive observables need to be scrutinized to exclude the non-CME contributions. In this work, we examine the influence of globally spin-aligned ρ mesons on the γ 112 correlator, the R Ψ 2 (ΔS) correlator, and the signed balance functions, via a toy model and a multiphase transport model (AMPT). The global spin alignment of vector mesons could originate from non-CME mechanisms in heavy-ion collisions, and is characterized by the 00-component of the spin density matrix, ρ 00 . Here, we find that the CME observables show similar dependence on ρ 00 , and could receive a positive (negative) contribution from ρ-decay pions, if the ρ 00 of ρ mesons is larger (smaller) than 1/3. Since pions are the most abundant particles in such collisions, the ρ 00 measurements for ρ mesons become crucial to the interpretation of the CME data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

First measurement of prompt and non-prompt D* + vector meson spin alignment in pp collisions at $\sqrt{s}$ = 13 TeV

This letter reports the first measurement of spin alignment, with respect to the helicity axis, for D* + vector mesons and their charge conjugates from charm-quark hadronisation (prompt) and from beauty meson decays (non-prompt) in hadron collisions. The measurements were performed at midrapidity (|y| < 0.8) as a function of transverse momentum (p T ) in proton–proton (pp) collisions collected by ALICE at the centre-of-mass energy $\sqrt{s}$ = 13 TeV. The diagonal spin density matrix element $ρ$00 of D* + mesons was measured from the angular distribution of the D* + → D 0 (→ K - π + )π + decay products, in the D* + rest frame, with respect to the D* + momentum direction in the pp centre of mass frame. The $ρ$00 value for prompt D* + mesons is consistent with 1/3, which implies no spin alignment. However, for non prompt D* + mesons an evidence of $ρ$00 larger than 1/3 is found. The measured value of the spin density element is $ρ$00 = 0.455±0.022(stat.)±0.035(syst.) in the 5 < p T < 20 GeV/c interval, which is consistent with a Pythia 8 Monte Carlo simulation coupled with the EvtGen package, which implements the helicity conservation in the decay of D* + meson from beauty mesons. In non-central heavy-ion collisions, the spin of the D* + mesons may be globally aligned with the direction of the initial angular momentum and magnetic field. Based on the results for pp collisions reported in this letter it is shown that alignment of non-prompt D* + mesons due to the helicity conservation coupled to the collective anisotropic expansion may mimic the signal of global spin alignment in heavy-ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Dynamic security assessment of systems powered only by grid-forming power plants with uncertain dispatch using polynomial vectors

A modern challenge in power engineering is to perform the dynamic security assessment (DSA) of grids that are 100% powered by inverter-based resources (IBRs). Addressing this challenge is difficult because: (i) the dispatch of IBRs can be uncertain as a result of the variability of renewable resources and (ii) they have hard current control limits that cannot be neglected, contrasting synchronous machines. To address this problem, this paper sets forth a framework to conduct DSA of bulk power systems that are 100% powered by grid-forming IBRs. Furthermore, the framework considers that IBR operational conditions are unknown but bounded by a zonotope which is also expressed as a polynomial vector for uncertainty propagation via Dormand–Prince integration. The framework is applied to modified versions of the WSCC 9-bus and IEEE 39-bus grids.

14 SOLAR ENERGY↗
DOE OSTI2014

Reducing computation in an i-vector speaker recognition system using a tree-structured universal background model

The majority of state-of-the-art speaker recognition systems (SR) utilize speaker models that are derived from an adapted universal background model (UBM) in the form of a Gaussian mixture model (GMM). This is true for GMM supervector systems, joint factor analysis systems, and most recently i-vector systems. In all of the identified systems, the posterior probabilities and sufficient statistics calculations represent a computational bottleneck in both enrollment and testing. We propose a multi-layered hash system, employing a tree-structured GMM–UBM which uses Runnalls’ Gaussian mixture reduction technique, in order to reduce the number of these calculations. Moreover, with this tree-structured hash, we can trade-off reduction in computation with a corresponding degradation of equal error rate (EER). As an example, we also reduce this computation by a factor of 15× while incurring less than 10% relative degradation of EER (or 0.3% absolute EER) when evaluated with NIST 2010 speaker recognition evaluation (SRE) telephone data.

42 ENGINEERING↗
DOE OSTI2022

QForte: An Efficient State-Vector Emulator and Quantum Algorithms Library for Molecular Electronic Structure

Here, we introduce a novel open-source software package QForte, a comprehensive development tool for new quantum simulation algorithms. QForte incorporates functionality for handling molecular Hamiltonians, fermionic encoding, ansatz construction, time evolution, and state-vector emulation, requiring only a classical electronic structure package as a dependency. QForte also contains black-box implementations of a wide variety of quantum algorithms, including variational and projective quantum eigensolvers, adaptive eigensolvers, quantum imaginary time evolution, and quantum Krylov methods. We highlight two features of QForte: (i) how the Python class structure of QForte enables the facile implementation of new algorithms, and (ii) how existing algorithms can be executed in just a few lines of code.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Chiral structures of electric polarization vectors quantified by X-ray resonant scattering

Resonant elastic X-ray scattering (REXS) offers a unique tool to investigate solid-state systems providing spatial knowledge from diffraction combined with electronic information through the enhanced absorption process, allowing the probing of magnetic, charge, spin, and orbital degrees of spatial order together with electronic structure. A new promising application of REXS is to elucidate the chiral structure of electrical polarization emergent in a ferroelectric oxide superlattice in which the polarization vectors in the REXS amplitude are implicitly described through an anisotropic tensor corresponding to the quadrupole moment. Here, we present a detailed theoretical framework and analysis to quantitatively analyze the experimental results of Ti L-edge REXS of a polar vortex array formed in a PbTiO 3 /SrTiO 3 superlattice. Based on this theoretical framework, REXS for polar chiral structures can become a useful tool similar to x-ray resonant magnetic scattering (XRMS), enabling a comprehensive study of both electric and magnetic REXS on the chiral structures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Binary vector copy number engineering improves Agrobacterium -mediated transformation

The copy number of a plasmid is linked to its functionality, yet there have been few attempts to optimize higher-copy-number mutants for use across diverse origins of replication in different hosts. We use a high-throughput growth-coupled selection assay and a directed evolution approach to rapidly identify origin of replication mutations that influence copy number and screen for mutants that improve Agrobacterium-mediated transformation (AMT) efficiency. By introducing these mutations into binary vectors within the plasmid backbone used for AMT, we observe improved transient transformation of Nicotiana benthamiana in four diverse tested origins (pVS1, RK2, pSa and BBR1). For the best-performing origin, pVS1, we isolate higher-copy-number variants that increase stable transformation efficiencies by 60–100% in Arabidopsis thaliana and 390% in the oleaginous yeast Rhodosporidium toruloides. Our work provides an easily deployable framework to generate plasmid copy number variants that will enable greater precision in prokaryotic genetic engineering, in addition to improving AMT efficiency.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

On fast simulation of dynamical system with neural vector enhanced numerical solver

The large-scale simulation of dynamical systems is critical in numerous scientific and engineering disciplines. However, traditional numerical solvers are limited by the choice of step sizes when estimating integration, resulting in a trade-off between accuracy and computational efficiency. To address this challenge, we introduce a deep learning-based corrector called Neural Vector (NeurVec), which can compensate for integration errors and enable larger time step sizes in simulations. Our extensive experiments on a variety of complex dynamical system benchmarks demonstrate that NeurVec exhibits remarkable generalization capability on a continuous phase space, even when trained using limited and discrete data. NeurVec significantly accelerates traditional solvers, achieving speeds tens to hundreds of times faster while maintaining high levels of accuracy and stability. Moreover, NeurVec’s simple-yet-effective design, combined with its ease of implementation, has the potential to establish a new paradigm for fast-solving differential equations based on deep learning.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The role of excitation vector fields and all-polarisation state control in cavity magnonics

Recently the field of cavity magnonics, a field focused on controlling the interaction between magnons and photons confined within microwave resonators, has drawn significant attention as it offers a platform for enabling advancements in quantum- and spin-based technologies. Here, we introduce excitation vector fields, whose polarisation and profile can be easily tuned in a two-port cavity setup, thus acting as an effective experimental dial to explore the coupled dynamics of cavity magnon-polaritons. Moreover, we develop theoretical models that accurately predict and reproduce the experimental results for any polarisation state and field profile within the cavity resonator. This versatile experimental platform offers a new avenue for controlling spin-photon interactions by manipulating the polarisation of excitation fields. By introducing real-time tunable parameters that control the polarisation state, our experiment delivers a mechanism to readily control the exchange of information between hybrid systems.

condensed-matter physics↗
DOE OSTI2022

Open-circuit submodule fault diagnosis in MMCs using support vector machines

Series connection of semiconductor submodules (SM) in a modular multilevel converter (MMC) makes the MMC prone to open-circuit (OC) IGBT failures inside SMs. If left undetected, these faults degrade the operation of the MMC and lead to its instability. This article proposes a method to detect, localise, and classify single OC SM faults in an MMC using support vector machines (SVM) trained with data obtained from the capacitor voltage balancing block of the MMC control system. The proposed method relies on data extracted from the sorted capacitor voltage arrays of the upper and lower phase arms. Therefore, it does not require extra measurements and hardware. Additionally, it offers a fixed time for detecting and localising OC SM faults. This method is easy to implement as SVM has a simple decision function. Time-domain simulation case studies are performed on a three-phase nine-level MMC to evaluate the performance of the proposed method.

42 ENGINEERING↗
DOE OSTI2018

Hybrid feature selection approach for power transformer fault diagnosis based on support vector machine and genetic algorithm

To further improve fault diagnosis accuracy, a new hybrid feature selection approach combined with a genetic algorithm (GA) and support vector machine (SVM) is presented in this study. Adaptive synthetic technique and arctangent transformation method are adopted to improve the statistical property of the training set (IEC TC10 dataset). Five filter methods based on different evaluation metrics are employed to rank 48 input features derived from dissolved gas analysis (DGA). Then, feature combination methods are applied to aggregate feature ranks and form a lower-dimension candidate feature subset. The GA-SVM model is implemented to optimise parameters and select optimal feature subsets. 5-fold cross-validation accuracy of the GA-SVM is used to evaluate fault diagnosis capability of feature subsets and finally, a novel subset is determined as the optimal feature subset. Accuracy comparison manifests the superiority of the optimal feature subsets over that of conventional approaches. Besides, generalisation and robustness of the optimal subset are validated by testing DGA samples from the local power utility. Results indicate that the optimal feature subset obtained by the proposed method can significantly improve the accuracies of power transformer fault diagnosis.

Kari, Tusongjiang↗
DOE OSTI2022

J-PLUS: Support vector regression to measure stellar parameters

Stellar parameters are among the most important characteristics in studies of stars which, in traditional methods, are based on atmosphere models. However, time, cost, and brightness limits restrain the efficiency of spectral observations. The Javalambre Photometric Local Universe Survey (J-PLUS) is an observational campaign that aims to obtain photometry in 12 bands. Owing to its characteristics, J-PLUS data have become a valuable resource for studies of stars. Machine learning provides powerful tools for efficiently analyzing large data sets, such as the one from J-PLUS, and enables us to expand the research domain to stellar parameters. The main goal of this study is to construct a support vector regression (SVR) algorithm to estimate stellar parameters of the stars in the first data release of the J-PLUS observational campaign. The training data for the parameter's regressions are featured with 12-waveband photometry from J-PLUS and are crossidentified with spectrum-based catalogs. These catalogs are from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, the Apache Point Observatory Galactic Evolution Experiment, and the Sloan Extension for Galactic Understanding and Exploration. We then label them with the stellar effective temperature, the surface gravity, and the metallicity. Ten percent of the sample is held out to apply a blind test. We develop a new method, a multi-model approach, in order to fully take into account, the uncertainties of both the magnitudes and the stellar parameters. The method utilizes more than 200 models to apply the uncertainty analysis. We present a catalog of 2 493 424 stars with the root mean square error of 160 K in the effective temperature regression, 0.35 in the surface gravity regression, and 0.25 in the metallicity regression. We also discuss the advantages of this multi-model approach and compare it to other machine-learning methods.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Search for DM at the LHC using vector boson fusion

The Supersymmetry (SUSY) models are the best candidates to provide a cosmological connection to particle physics. The SUSY particles responsible for satisfying the dark matter content can be observed via cascade decay prcesses from the squarks, gluino productions. However if the squarks, gluinos are heavy, these particles also can be detected via vector boson fusion (VBF) production processes. In this review, I will summarize the search strategies involve VBF which will be very important to establish the cosmological connection.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Cylindrical vector beams of light from an electrically excited plasmonic lens

The production of cylindrical vector beams from a low-energy, electric, microscale light source is demonstrated both experimentally and theoretically. This is achieved by combining a “plasmonic lens” with the ability to locally and electrically excite propagating surface plasmons on gold films. The plasmonic lens consists of concentric circular subwavelength slits that are etched in a thick gold film. The local excitation arises from the inelastic tunneling of electrons from the tip of a scanning tunneling microscope. We report on the emission of radially polarized beams with an angular divergence of less than ±4°.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Assessment of approximate computational methods for conical intersections and branching plane vectors in organic molecules

Quantum-chemical computational methods are benchmarked for their ability to describe conical intersections in a series of organic molecules and models of biological chromophores. Reference results for the geometries, relative energies, and branching planes of conical intersections are obtained using ab initio multireference configuration interaction with single and double excitations (MRCISD). They are compared with the results from more approximate methods, namely, the state-interaction state-averaged restricted ensemble-referenced Kohn-Sham method, spin-flip time-dependent density functional theory, and a semiempirical MRCISD approach using an orthogonalization-corrected model. It is demonstrated that these approximate methods reproduce the ab initio reference data very well, with root-mean-square deviations in the optimized geometries of the order of 0.1 Å or less and with reasonable agreement in the computed relative energies. A detailed analysis of the branching plane vectors shows that all currently applied methods yield similar nuclear displacements for escaping the strong non-adiabatic coupling region near the conical intersections. Our comparisons support the use of the tested quantum-chemical methods for modeling the photochemistry of large organic and biological systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Optical trapping of core-shell magnetic microparticles by cylindrical vector beams

Optical trapping of core-shell magnetic microparticles is experimentally demonstrated by using cylindrical vector beams. Second, we investigate the optical trapping efficiencies. The results show that radially and azimuthally polarized beams exhibit higher axial trapping efficiencies than the Gaussian beam. Finally, a trapped particle is manipulated to kill a cancer cell. The results make possible utilizing magnetic particles for optical manipulation, which is an important advantage for magnetic particles as labeling agent in targeted medicine and biological analysis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Observation of genuine wave vector (k or β) gap in a dynamic transmission line and temporal photonic crystals

By definition, a temporal photonic crystal (TPC) has a permittivity ε(t) that varies periodically with time. We prove that, in the long wavelength limit, a TPC is accurately mimicked by a dynamic transmission line (DTL) having a capacitance (inductance) per unit length equal to ε(t) (μ). Employing a DTL in the microwave region, we measured the photonic band structure, which results to display a genuine wave vector (k or β) gap, in very good agreement with our theoretical model and the equivalent TPC.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

A three-axis SQUID-based absolute vector magnetometer

We report on the development of a three-axis absolute vector magnetometer suited for mobile operation in the Earth’s magnetic field. It is based on low critical temperature dc superconducting quantum interference devices (LTS dc SQUIDs) with sub-micrometer sized cross-type Josephson junctions and exhibits a white noise level of about 10 fT/Hz{sup 1/2}. The width of superconducting strip lines is restricted to less than 6 μm in order to avoid flux trapping during cool-down in magnetically unshielded environment. The long-term stability of the flux-to-voltage transfer coefficients of the SQUID electronics is investigated in detail and a method is presented to significantly increase their reproducibility. We further demonstrate the long-term operation of the setup in a magnetic field varying by about 200 μT amplitude without the need for recalibration.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗