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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
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 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 OSTI2022

On the new universality class in structurally disordered n -vector model with long-range interactions

We study a stability boundary of a region where nontrivial critical behavior of an n-vector model with long-range power-law decaying interactions is induced by the presence of a structural disorder (e.g., weak quenched dilution). This boundary is given by the marginal dimension of the order parameter nc dependent on space dimension, d, and a control parameter of the interaction decay, σ, below which the model belongs to the new dilution-induced universality class. Exploiting the Harris criterion and recent field theoretical renormalization group results for the pure model with long-range interactions, we get nc as a three loop ɛ = 2σ – d-expansion. We provide numerical values for nc applying series resummation methods. Our results show that not only the Ising systems (n = 1) can belong to the new disorder-induced long-range universality class at d = 2 and 3.

Physics↗
DOE OSTI2023

Vector meson photoproduction in UPCs with FoCal

Abstract We discuss the physics prospects of photon-induced measurements using the high-granularity FoCal detector to be installed at the ALICE experiment, covering the pseudorapidity interval 3.4 ≤ η ≤ 5.8. This new detector, scheduled to be in operation from Run 4, will explore the small Bjorken- x physics region in an unprecedented way. In this region the gluon ,saturation phenomenon is expected to be dominant. Combined with the rest of the ALICE subdetectors, including the zero degree calorimenters, FoCal will serve to reconstruct in a model-independent way the measured photoproduction cross sections for vectors mesons in a wide range of photon-target energies, down to x values of about 7 × 10 −6 and 2 × 10 −6 in ultra-peripheral photon–proton and photon–lead collisions, respectively.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Polarized photoelectrons from converging vector waves

Abstract This paper investigates the spin characteristics of photoelectrons when hydrogen-like ions are centro-symmetrically irradiated with converging vector waves—a non-paraxial form of structured light. For a photon with given total angular momentum and third component thereof, photoelectrons with both helicities are obtained—in contrast to the fixed helicities produced by left- or right-circularly polarized light. The angular distribution of photoelectrons is broadly tunable through the radiation mode numbers, and opposite helicities can be extracted in synchronism.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Vectorization techniques for probability distribution functions using VecCore

Probability distribution functions (PDFs) are very used in modeling random processes and physics simulations. Improving the performance of algorithms that generate many random numbers under complex PDFs is often a very challenging task when methods as direct functions are not available. In this work we present general strategies on how to vectorize some PDFs using VecCore library. We show the results for the Exponential, Gaussian, discrete Poisson and Gamma probability distributions.

Chaparro Amaro, Oscar R.↗
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

ZMPY3D: accelerating protein structure volume analysis through vectorized 3D Zernike moments and Python-based GPU integration

Abstract Motivation Volumetric 3D object analyses are being applied in research fields such as structural bioinformatics, biophysics, and structural biology, with potential integration of artificial intelligence/machine learning (AI/ML) techniques. One such method, 3D Zernike moments, has proven valuable in analyzing protein structures (e.g., protein fold classification, protein–protein interaction analysis, and molecular dynamics simulations). Their compactness and efficiency make them amenable to large-scale analyses. Established methods for deriving 3D Zernike moments, however, can be inefficient, particularly when higher order terms are required, hindering broader applications. As the volume of experimental and computationally-predicted protein structure information continues to increase, structural biology has become a “big data” science requiring more efficient analysis tools. Results This application note presents a Python-based software package, ZMPY3D, to accelerate computation of 3D Zernike moments by vectorizing the mathematical formulae and using graphical processing units (GPUs). The package offers popular GPU-supported libraries such as CuPy and TensorFlow together with NumPy implementations, aiming to improve computational efficiency, adaptability, and flexibility in future algorithm development. The ZMPY3D package can be installed via PyPI, and the source code is available from GitHub. Volumetric-based protein 3D structural similarity scores and transform matrix of superposition functionalities have both been implemented, creating a powerful computational tool that will allow the research community to amalgamate 3D Zernike moments with existing AI/ML tools, to advance research and education in protein structure bioinformatics. Availability and implementation ZMPY3D, implemented in Python, is available on GitHub (https://github.com/tawssie/ZMPY3D) and PyPI, released under the GPL License.

Lai, Jhih-Siang (ORCID:0000000156775890)↗
DOE OSTI2025

Off forward non- s -channel helicity conserving contributions to exclusive vector quarkonium production from the spin dependent BFKL Pomeron

A novel contribution to off forward, exclusive vector quarkonium production, γ(*)+p → V+p, at high energy is derived which corresponds to a t-channel exchange of a Balitsky-Fadin-Kuraev-Lipatov (BFKL) hard Pomeron, with a helicity flip of the proton. This “spin-dependent BFKL Pomeron” is required in a consistent expansion in powers of the momentum transfer t ≈−Δ$^{2}_{⊥}$ beyond first order. The spin-dependent Pomeron violates s-channel helicity conservation at O(Δ$^{2}_{⊥}$), and beyond. Expanding to leading twist only, it corresponds to generalized parton distributions E g (x,t) for vanishing skewness. We derive explicit expressions for the eikonal BFKL amplitudes, to all orders in dipole size times momentum transfer, for all helicity configurations of the particles in the initial and final states. We also provide numerical estimates of the helicity flip two gluon exchange amplitude at moderate x from a light cone quark model of the proton. The spin dependent BFKL Pomeron could, in principle, be discovered via double spin asymmetries in e+p → e+p+J/ψ with a transversely polarized proton and longitudinally polarized electron in the initial state.

Deep inelastic scattering↗
DOE OSTI2026

Practical considerations for measuring global spin density matrix elements of vector mesons in heavy-ion collisions

The STAR Collaboration has reported a significant 𝜙-meson global spin alignment (𝜌 00 ) signal in Au+Au collisions at $\sqrt{s_{NN}}$ ≤ 62 GeV by measuring the polar angle distribution of 𝜙-meson daughters with respect to the orbital angular momentum direction of the collision system. Here, in this paper, a new method is explored for studying vector-meson global spin alignment in heavy-ion collisions by examining the two-dimensional (2D) polar and azimuthal angle distribution. This method allows simultaneous extraction of 𝜌 00 and off-diagonal spin density matrix elements (SDMEs), providing unique access to local quark-antiquark spin correlations and spin hydrodynamics in quark-gluon plasma. The new 2D method also removes potential biases from nonzero off-diagonal SDMEs on 𝜌 00 with the 1D method. A detailed procedure to correct for detector acceptance and resolution effects is also presented and validated by simulation studies.

Wilks, Gavin [University of Illinois, Chicago, IL ↗
DOE OSTI2020

Vector Electrometry in a Wide-Gap-Semiconductor Device Using a Spin-Ensemble Quantum Sensor

Nitrogen-vacancy (N-V) centers in diamond work as a quantum electrometer. Using an ensemble state of N-V centers, we propose vector electrometry and demonstrate measurements in a diamond electronic device. A transverse electric field applied to the N-V axis under a high voltage is measured, while applying a transverse magnetic field. The response of the energy-level shift against the electric field is significantly enhanced compared with that against an axial magnetic field. Repeating the measurement of the transverse electric field for multiple N-V axes, our team obtains the components of the electric field generated in the device.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Machine learning for improved current-density reconstruction from two-dimensional vector magnetic images

The reconstruction of electrical current densities from magnetic field measurements is an important technique with applications in materials science, circuit design, quality control, plasma physics, and biology. Analytic reconstruction methods exist for planar currents, but break down in the presence of high-spatial-frequency noise or large standoff distance, restricting the types of systems that can be studied. Here, we demonstrate the use of a deep convolutional neural network for current density reconstruction from two-dimensional images of vector magnetic fields acquired by a quantum diamond microscope . Trained network performance significantly exceeds analytic reconstruction for data with high noise or large standoff distances. This machine learning technique can perform quality inversions on lower-signal-to-noise-ratio data, significantly reducing the data collection time and permitting reconstructions of weaker and three-dimensional current sources. Published by the American Physical Society 2025

Reed, Niko R. (ORCID:0009000305222403)↗
DOE OSTI2020

Independence of the spin current from the Néel vector orientation in antiferromagnet CoO

Spin pumping from ferromagnetic Fe into antiferromagnetic CoO across a Ag spacer layer was studied using ferromagnetic resonance (FMR) in Py/CoO/Ag/Fe/Ag(001). The thin Py film on top of CoO permits an alignment of the CoO Neél vector through field cooling in two otherwise equivalent [110] and [110] crystalline axes which are parallel and perpendicular to the Fe magnetization direction, respectively. Fe FMR linewidth is measured as a function of Ag thickness in 10-20-GHz frequency range and in 180-330 K temperature range. Furthermore, we find that there exists an anisotropy in the Fe FMR damping for parallel and perpendicular alignment of the Fe and CoO spins. However, such anisotropic damping exists only at thin Ag thickness where there exists a magnetic interlayer coupling between Fe and CoO, and vanishes at thick Ag thickness where the interlayer coupling becomes negligible but permitting spin-current transmission into CoO. Our result indicates the absence of anisotropic spin current for parallel and perpendicular alignment of the Fe and CoO spin axes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Effects of filling, strain, and electric field on the Néel vector in antiferromagnetic CrSb

CrSb is a layered antiferromagnet (AFM) with perpendicular magnetic anisotropy, a high Néel temperature, and large spin-orbit coupling (SOC), which makes it interesting for AFM spintronic applications. To elucidate the various mechanisms of Néel vector control, the effects of strain, band filling, and electric field on the magnetic anisotropy energy (MAE) of bulk and thin-film CrSb are determined and analyzed using density functional theory. The MAE of the bulk crystal is large (1.2 meV per unit cell). Due to the significant ionic nature of the Cr-Sb bond, finite slabs are strongly affected by end termination. Truncation of the bulk crystal to a thin film with one surface terminated with Cr and the other surface terminated with Sb breaks inversion symmetry, creates a large charge dipole and average electric field across the film, and breaks spin degeneracy, such that the thin film becomes a ferrimagnet. The MAE is reduced such that its sign can be switched with realistic strain, and the large SOC gives rise to an intrinsic voltage controlled magnetic anisotropy. A slab terminated on both faces with Cr remains a compensated AFM, but with the compensation occurring nonlocally between mirror-symmetric Cr pairs. In-plane alignment of the moments is preferred, the magnitude of the MAE remains large, similar to that of the bulk, and it is relatively insensitive to filling.

36 MATERIALS SCIENCE↗
DOE OSTI2022

First-principles wave-vector- and frequency-dependent exchange-correlation kernel for jellium at all densities

Here we propose a spatially and temporally nonlocal exchange correlation (XC) kernel for the spin-unpolarized fluid phase of ground-state jellium for use in time-dependent density functional and linear response calculations. The kernel is constructed to satisfy known properties of the exact XC kernel to accurately describe the correlation energies of bulk jellium and to satisfy frequency-moment sum rules at a wide range of bulk jellium densities, including those low densities that display strong correlation and symmetry breaking. These effects are easier to understand in the simple jellium model than in real systems. All exact constraints satisfied by the recent MCP07 kernel are maintained in the revised MCP07 (rMCP07) kernel, while others are added. The revision $f^{rMCP07}_{XC}$ (q, ω) differs from MCP07 only for nonzero frequencies ω. Only at densities much lower than those of real bulk metals is the frequency dependence of the kernel important for the correlation energy of jellium. As the wave vector q tends to zero, the kernel has a -4$πα(ω)/q^2$ divergence whose frequency-dependent ultranonlocality coefficient $α(ω)$ vanishes in jellium, and is predicted by rMCP07 to be extremely small for the real metals Al and Na.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Effect of vector meson spin coherence on the observables for the chiral magnetic effect in heavy-ion collisions

The chiral magnetic effect (CME) in heavy-ion collisions reflects the local violation of P and CP symmetries in strong interactions and manifests as electric charge separation along the direction of the magnetic field created by the wounded nuclei. The experimental observables for the CME, such as the γ 112 correlator, the R Ψ$_2$ ⁡ (Δ⁢S) correlator, and the signed balance functions, however, are also subject to non-CME backgrounds, including those from resonance decays. A previous study showed that the CME observables are affected by the diagonal component of the spin density matrix, the ρ 00 for vector mesons. Here, in this work, we study the contributions from the other elements of the spin density matrix using a toy model and a multiphase transport model. We find that the real part of the ρ 1-1 component, Re ⁡ρ 1-1 , affects the CME observables in a manner opposite to that of the ρ 00 . All three aforementioned CME observables show a linear dependence on Re ⁡ρ 1-1 in the model calculations, supporting our analytical derivations. The rest elements of the spin density matrix do not contribute to the CME observables. The off-diagonal terms in the spin density matrix indicate spin coherence and may be nonzero in heavy-ion collisions due to local spin polarization or spin-spin correlations. Thus, Re ⁡ρ 1-1 , along with ρ 00 , could play a significant role in interpreting measurements in search of the CME.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

QCD critical point from the Nambu–Jona-Lasino model with a scalar-vector interaction

We study the critical point in the QCD phase diagram in the Nambu–Jona-Lasino (NJL) model by including a scalar-vector coupled interaction. We find that varying the strength of this interaction, which has no effect on the vacuum properties of QCD, can significantly affect the location of the critical point in the QCD phase diagram, particularly the value of the critical temperature. This provides a convenient way to use the NJL-based transport or hydrodynamic model to extract information about the QCD phase diagram from relativistic heavy-ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗