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At least 163 records · Page 9

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DOE OSTI2018

Method and apparatus for precision phasor measurements through a medium-voltage distribution transformer

A means and method for measuring precise voltage phasors on medium-voltage alternating current (AC) distribution grids, using existing distribution transformers as voltage sensors. The errors introduced by the distribution transformers are minimized by taking into account the transformer's vector impedance, combined with measuring the transformer secondary current phasor. The invention includes a means and a method of measuring the distribution transformer's vector impedance.

McEachern, Alexander↗

DOE OSTI2011

Measurement of Charmless B to Vector-Vector decays at BaBar

The authors present results of B {yields} vector-vector (VV) and B {yields} vector-axial vector (VA) decays B{sup 0} {yields} {phi}X(X = {phi},{rho}{sup +} or {rho}{sup 0}), B{sup +} {yields} {phi}K{sup (*)+}, B{sup 0} {yields} K*K*, B{sup 0} {yields} {rho}{sup +}b{sub 1}{sup -} and B{sup +} {yields} K*{sup 0}{alpha}{sub 1}{sup +}. The largest dataset used for these results is based on 465 x 10{sup 6} {Upsilon}(4S) {yields} B{bar B} decays, collected with the BABAR detector at the PEP-II B meson factory located at the Stanford Linear Accelerator Center (SLAC). Using larger datasets, the BABAR experiment has provided more precise B {yields} VV measurements, further supporting the smaller than expected longitudinal polarization fraction of B {yields} {phi}K*. Additional B meson to vector-vector and vector-axial vector decays have also been studied with a view to shedding light on the polarization anomaly. Taking into account the available errors, we find no disagreement between theory and experiment for these additional decays.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2014

Early Results from the Q{sub weak} Experiment

A subset of results from the recently completed Jefferson Lab Q{sub weak} experiment are reported. This experiment, sensitive to physics beyond the Standard Model, exploits the small parity-violating asymmetry in elastic {vector e}p scattering to provide the first determination of the protons weak charge Q{sub w}{sup p}. The experiment employed a 180 {micro}A longitudinally polarized 1.16 GeV electron beam on a 35 cm long liquid hydrogen target. Scattered electrons corresponding to Q{sup 2} of 0.025 GeV{sup 2} were detected in eight Cerenkov detectors arrayed symmetrically around the beam axis. The goals of the experiment were to provide a measure of Q{sub w}{sup p} to 4.2 percent (combined statistical and systematic error), which implies a measure of sin2(thetaw) at the level of 0.3 percent, and to help constrain the vector weak quark charges C{sub 1u} and C{sub 1d}. The experimental method is described, with particular focus on the challenges associated with the worlds highest power LH{sub 2} target. The new constraints on C{sub 1u} and C{sub 1d} provided by the subset of the experiments data analyzed to date will also be shown, together with the extracted weak charge of the neutron.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2018

Exploring the capabilities of support vector machines in detecting silent data corruptions

As the exascale era approaches, the increasing capacity of high-performance computing (HPC) systems with targeted power and energy budget goals introduces significant challenges in reliability. Silent data corruptions (SDCs), or silent errors, are one of the major sources that corrupt the execution results of HPC applications without being detected. Here in this paper, we explore a set of novel SDC detectors – by leveraging epsilon-insensitive support vector machine regression – to detect SDCs that occur in HPC applications. The key contributions are threefold. (1) Our exploration takes temporal, spatial, and spatiotemporal features into account and analyzes different detectors based on different features. (2) We provide an in-depth study on the detection ability and performance with different parameters, and we optimize the detection range carefully. (3) Experiments with eight real-world HPC applications show that support-vector-machine-based detectors can achieve detection sensitivity (i.e., recall) up to 99% yet suffer a less than 1% false positive rate for most cases. Our detectors incur low performance overhead, 5% on average, for all benchmarks studied in this work.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2012

On the dosimetric effect and reduction of inverse consistency and transitivity errors in deformable image registration for dose accumulation

Purpose: Deformable image registration (DIR) is necessary for accurate dose accumulation between multiple radiotherapy image sets. DIR algorithms can suffer from inverse and transitivity inconsistencies. When using deformation vector fields (DVFs) that exhibit inverse-inconsistency and are nontransitive, dose accumulation on a given image set via different image pathways will lead to different accumulated doses. The purpose of this study was to investigate the dosimetric effect of and propose a postprocessing solution to reduce inverse consistency and transitivity errors. Methods: Four MVCT images and four phases of a lung 4DCT, each with an associated calculated dose, were selected for analysis. DVFs between all four images in each data set were created using the Fast Symmetric Demons algorithm. Dose was accumulated on the fourth image in each set using DIR via two different image pathways. The two accumulated doses on the fourth image were compared. The inverse consistency and transitivity errors in the DVFs were then reduced. The dose accumulation was repeated using the processed DVFs, the results of which were compared with the accumulated dose from the original DVFs. To evaluate the influence of the postprocessing technique on DVF accuracy, the original and processed DVF accuracy was evaluated on the lung 4DCT data on which anatomical landmarks had been identified by an expert. Results: Dose accumulation to the same image via different image pathways resulted in two different accumulated dose results. After the inverse consistency errors were reduced, the difference between the accumulated doses diminished. The difference was further reduced after reducing the transitivity errors. The postprocessing technique had minimal effect on the accuracy of the DVF for the lung 4DCT images. Conclusions: This study shows that inverse consistency and transitivity errors in DIR have a significant dosimetric effect in dose accumulation; Depending on the image pathway taken to accumulate the dose, different results may be obtained. A postprocessing technique that reduces inverse consistency and transitivity error is presented, which allows for consistent dose accumulation regardless of the image pathway followed.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2018

Identifying an efficient, thermally robust inorganic phosphor host via machine learning

Abstract Rare-earth substituted inorganic phosphors are critical for solid state lighting. New phosphors are traditionally identified through chemical intuition or trial and error synthesis, inhibiting the discovery of potential high-performance materials. Here, we merge a support vector machine regression model to predict a phosphor host crystal structure’s Debye temperature, which is a proxy for photoluminescent quantum yield, with high-throughput density functional theory calculations to evaluate the band gap. This platform allows the identification of phosphors that may have otherwise been overlooked. Among the compounds with the highest Debye temperature and largest band gap, NaBaB 9 O 15 shows outstanding potential. Following its synthesis and structural characterization, the structural rigidity is confirmed to stem from a unique corner sharing [B 3 O 7 ] 5– polyanionic backbone. Substituting this material with Eu 2+ yields UV excitation bands and a narrow violet emission at 416 nm with a full-width at half-maximum of 34.5 nm. More importantly, NaBaB 9 O 15 :Eu 2+ possesses a quantum yield of 95% and excellent thermal stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

B -meson decay constants from 2 + 1 -flavor lattice QCD with domain-wall light quarks and relativistic heavy quarks

We calculate the B-meson decay constants f B , f B s , and their ratio in unquenched lattice QCD using domain-wall light quarks and relativistic b quarks. We use gauge-field ensembles generated by the RBC and UKQCD collaborations using the domain-wall fermion action and Iwasaki gauge action with three flavors of light dynamical quarks. We analyze data at two lattice spacings of a ≈ 0.11, 0.086 fm with unitary pion masses as light as M π ≈ 290 MeV; this enables us to control the extrapolation to the physical light-quark masses and continuum. For the b quarks we use the anisotropic clover action with the relativistic heavy-quark interpretation, such that discretization errors from the heavy-quark action are of the same size as from the light-quark sector. We renormalize the lattice heavy-light axial-vector current using a mostly nonperturbative method in which we compute the bulk of the matching factor nonperturbatively, with a small correction, that is close to unity, in lattice perturbation theory. We also improve the lattice heavy-light current through O(α s a). We extrapolate our results to the physical light-quark masses and continuum using SU(2) heavy-meson chiral perturbation theory, and provide a complete systematic error budget. We obtain f B 0 = 199.5(12.6) MeV, f B + =195.6(14.9) MeV, f B s =235.4(12.2) MeV, f B s /f B 0 =1.197(50), and f B s /f B + =1.223(71), where the errors are statistical and total systematic added in quadrature. Finally, these results are in good agreement with other published results and provide an important independent cross-check of other three-flavor determinations of B-meson decay constants using staggered light quarks.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2012

A method to estimate the effect of deformable image registration uncertainties on daily dose mapping

Purpose: To develop a statistical sampling procedure for spatially-correlated uncertainties in deformable image registration and then use it to demonstrate their effect on daily dose mapping. Methods: Sequential daily CT studies are acquired to map anatomical variations prior to fractionated external beam radiotherapy. The CTs are deformably registered to the planning CT to obtain displacement vector fields (DVFs). The DVFs are used to accumulate the dose delivered each day onto the planning CT. Each DVF has spatially-correlated uncertainties associated with it. Principal components analysis (PCA) is applied to measured DVF error maps to produce decorrelated principal component modes of the errors. The modes are sampled independently and reconstructed to produce synthetic registration error maps. The synthetic error maps are convolved with dose mapped via deformable registration to model the resulting uncertainty in the dose mapping. The results are compared to the dose mapping uncertainty that would result from uncorrelated DVF errors that vary randomly from voxel to voxel. Results: The error sampling method is shown to produce synthetic DVF error maps that are statistically indistinguishable from the observed error maps. Spatially-correlated DVF uncertainties modeled by our procedure produce patterns of dose mapping error that are different from that due to randomly distributed uncertainties. Conclusions: Deformable image registration uncertainties have complex spatial distributions. The authors have developed and tested a method to decorrelate the spatial uncertainties and make statistical samples of highly correlated error maps. The sample error maps can be used to investigate the effect of DVF uncertainties on daily dose mapping via deformable image registration. An initial demonstration of this methodology shows that dose mapping uncertainties can be sensitive to spatial patterns in the DVF uncertainties.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2025

Electron-Proton Scattering Event Generation using Structured Tokenization

Recent work such as Omnijet-$\alpha$ has demonstrated that effective tokenization combined with transformer-based architectures can produce effective foundation models for jet physics. While tokenization may help models capture generalizable event characteristics, it also introduces discretization errors that may compromise the precision required for downstream physics analyses. As the number and complexity of the particle features grow, these errors are likely to grow proportionally. In this study, we investigate new tokenization strategies to improve the application of generative transformer models to \textsc{Pythia8} simulations of electron-proton scattering at the Electron-Ion Collider. Specifically, we propose a feature-based structured tokenization approach that utilizes multiple tokens per particle, improving expressivity, while reducing the total number of unique tokens needed. We evaluate this method against grid-based binning, K-means clustering, and vector-quantized variational auto-encoders on the event simulations. Our results show that feature-based structured tokenization reduces discretization error, leading to more accurate generative modeling of particle-level events.

Goldenberg, Steven [Thomas Jefferson National Acce↗

DOE OSTI2025

Electron-Proton Scattering Event Generation using Structured Tokenization

Goldenberg, Steven [Thomas Jefferson National Acce↗

DOE OSTI2017

Vector-model-supported approach in prostate plan optimization

Lengthy time consumed in traditional manual plan optimization can limit the use of step-and-shoot intensity-modulated radiotherapy/volumetric-modulated radiotherapy (S&S IMRT/VMAT). A vector model base, retrieving similar radiotherapy cases, was developed with respect to the structural and physiologic features extracted from the Digital Imaging and Communications in Medicine (DICOM) files. Planning parameters were retrieved from the selected similar reference case and applied to the test case to bypass the gradual adjustment of planning parameters. Therefore, the planning time spent on the traditional trial-and-error manual optimization approach in the beginning of optimization could be reduced. Each S&S IMRT/VMAT prostate reference database comprised 100 previously treated cases. Prostate cases were replanned with both traditional optimization and vector-model-supported optimization based on the oncologists' clinical dose prescriptions. A total of 360 plans, which consisted of 30 cases of S&S IMRT, 30 cases of 1-arc VMAT, and 30 cases of 2-arc VMAT plans including first optimization and final optimization with/without vector-model-supported optimization, were compared using the 2-sided t-test and paired Wilcoxon signed rank test, with a significance level of 0.05 and a false discovery rate of less than 0.05. For S&S IMRT, 1-arc VMAT, and 2-arc VMAT prostate plans, there was a significant reduction in the planning time and iteration with vector-model-supported optimization by almost 50%. When the first optimization plans were compared, 2-arc VMAT prostate plans had better plan quality than 1-arc VMAT plans. The volume receiving 35 Gy in the femoral head for 2-arc VMAT plans was reduced with the vector-model-supported optimization compared with the traditional manual optimization approach. Otherwise, the quality of plans from both approaches was comparable. Vector-model-supported optimization was shown to offer much shortened planning time and iteration number without compromising the plan quality.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2024

Behavior and mechanisms of Doppler wind lidar error in complex terrain: stable flow case study at Perdigão

A numerical experiment is carried out investigating the magnitude of biases in ground-based lidar measurements in complex flow conditions. Biases assessed include those arising from flow curvature and from the interaction of turbulence with the wind field reconstruction (WFR) algorithms used by a WindCube lidars and anemometers. RANS-CFD and WRF-LES simulations were performed for the Perdig˜ao Field Experiment site for a range of atmospheric conditions. Virtual anemometer and lidar data were generated for four locations: two near exposed ridge tops and two in low-speed regions in the valley. The LES data at these four locations show that the scalar inflation terms (the relation between scalar and vector averaged wind speed) for virtual lidar and virtual cups agree very well with predictions using perturbation theory. While the lidar errors vary greatly with location and height, the contribution from the flow curvature tends to be larger than the differences arising from scalar inflation. For one lidar/mast pair near the ridge top, comparisons between simulations and measurements are carried out for a resonant mountain wave event on June 14th, 2017, and for the whole duration of the Perdigão campaign for winds perpendicular to the ridges. The lidar error during the mountain wave, a period of strong stability and low inversion height, is significantly larger than the campaign average. The sensitivity of the lidar error to atmospheric stability is confirmed by the RANS simulations, which suggests strong sensitivity of flow curvature error to stability conditions and to the shape of the wind speed profile near the top of the boundary layer.

17 WIND ENERGY↗

DOE OSTI2024

Machine learning in materials research: Developments over the last decade and challenges for the future

The number of studies that apply machine learning (ML) to materials science has been growing at a rate of approximately 1.67 times per year over the past decade. In this review, I examine this growth in various contexts. First, I present an analysis of the most commonly used tools (software, databases, materials science methods, and ML methods) used within papers that apply ML to materials science. The analysis demonstrates that despite the growth of deep learning techniques, the use of classical machine learning is still dominant as a whole. It also demonstrates how new research can effectively build upon past research, particular in the domain of ML models trained on density functional theory calculation data. Next, I present the progression of best scores as a function of time on the matbench materials science benchmark for formation enthalpy prediction. In particular, a dramatic improvement of 7 times reduction in error is obtained when progressing from feature-based methods that use conventional ML (random forest, support vector regression, etc.) to the use of graph neural network techniques. Finally, I provide views on future challenges and opportunities, focusing on data size and complexity, extrapolation, interpretation, access, and relevance.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Revealing the Formation Energy–Exfoliation Energy–Structure Correlation of MAB Phases Using Machine Learning and DFT

MAB phases are popular as high-temperature materials with high damage tolerance and excellent electrical conductivity that are used to exfoliate two-dimensional (2D) transition metal borides (MBenes); a promising material for developing next- generation nanodevices. In this report, we explore the correlation between the formation energy, exfoliation energy and structural factors of MAB phases using DFT and machine learning. In order to do so, we developed three different machine learning models based on the support vector machine, deep neural network, and random forest regressor to study the stability of the MAB phases by calculating their formation energies. Furthermore, our support vector machine and deep neural network models are capable of predicting the formation energies with mean absolute errors less than 0.1 eV/atom. We demonstrated that the stability of a MAB phase for a given transition metal decreases when the A element changes from Al to Tl. The density functional theory (DFT) re- vealed that M-A and M-B bond strength strongly correlates with the stability of MAB phases. In addition, the exfoliation possibility of 2D MBenes becomes higher when the A element changes from Al to Tl due to weakening of M-A and M-B bonds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Coherent manipulation of graph states composed of finite-energy Gottesman-Kitaev-Preskill-encoded qubits

Graph states are a central resource in measurement-based quantum information processing. In the photonic qubit architecture based on Gottesman-Kitaev-Preskill (GKP) encoding, the generation of high-fidelity graph states composed of realistic, finite-energy approximate GKP-encoded qubits thus constitutes a key task. We consider the finite-energy approximation of GKP-qubit states given by a coherent superposition of shifted finite-squeezed vacuum states, where the displacements are Gaussian distributed. We present an exact description of graph states composed of such approximate GKP qubits as a coherent superposition of a Gaussian ensemble of randomly displaced ideal GKP-qubit graph states. Using standard Gaussian dynamics, we track the transformation of the covariance matrix and the mean-displacement vector elements of the Gaussian distribution of the ensemble under tools such as GKP-Steane error-correction and fusion operations that can be used to grow large high-fidelity GKP-qubit graph states. The covariance matrix elements capture the noise in the graph state due to the finite-energy approximation of GKP qubits, while the mean displacements relate to the possible absolute shift errors on the individual qubits arising conditionally from the homodyne measurements that are a part of these tools. Our work thus pins down an exact coherent error model for graph states generated from truly finite-energy GKP qubits, which can shed light on their error-correction properties.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Probabilistic Error Bounds for Low-Rank Tensor Decompositions Used in Large-Scale Data Analysis Applications (LDRD Final Report)

This report documents a research project on analyzing low-rank tensor models for data analysis that took place at Sandia National Laboratories from October 2023–September 2025. The focus of this work was to extend theoretical frameworks from statistics and probability theory for use with models for scalar, vector, and matrix data to models with tensor, or general multi-dimensional array, data. Through this work, we have provided a new set of tools for bounding errors on low-rank tensor models of both complete and sampled data. The remainder of this report is organized as follows. In Section 1, we describe the proposed work at the start of the project. Section 2 describes the research advances made as part of the project. Other research contributions in the form of conference presentations and software development is provided in Section 3. Workforce development at Sandia and Florida Atlantic University (via a subcontract on this project) is provided in Section 4.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Validation of the DESI DR2 measurements of baryon acoustic oscillations from galaxies and quasars

The Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2) galaxy and quasar clustering data represents a significant expansion of data from Data Release 1 (DR1), providing improved statistical precision in baryon acoustic oscillation (BAO) constraints across multiple tracers, including bright galaxies, luminous red galaxies, emission line galaxies, and quasars. In this paper, we validate the BAO analysis of DR2. We present the results of robustness tests on the blinded DR2 data and, after unblinding, consistency checks on the unblinded DR2 data. All results are compared with those obtained from a suite of mock catalogs that replicate the selection and clustering properties of the DR2 sample. We confirm the consistency of DR2 BAO measurements with DR1 while achieving a reduction in statistical uncertainties due to the increased survey volume and completeness. The combined BAO precision, including both statistical and systematic errors, improves from ∼0.52% in DR1 to 0.30% in DR2—a factor of 1.7 gain. We assess the impact of analysis choices, including different data vectors (correlation function vs power spectrum), modeling approaches and systematics treatments, and an assumption of the Gaussian likelihood, finding that our BAO constraints are stable across these variations and assumptions with a few minor refinements to the baseline setup of the DR1 BAO analysis. We summarize a series of pre-unblinding tests that confirmed the readiness of our analysis pipeline, the final systematic errors, and the DR2 BAO analysis baseline. The successful completion of these tests led to the unblinding of the DR2 BAO measurements, ultimately leading to the DESI DR2 cosmological analysis, with their implications for the expansion history of the Universe and the nature of dark energy presented in the DESI key paper (companion paper).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

Accuracy of Real-time Couch Tracking During 3-dimensional Conformal Radiation Therapy, Intensity Modulated Radiation Therapy, and Volumetric Modulated Arc Therapy for Prostate Cancer

Purpose: To evaluate the accuracy of real-time couch tracking for prostate cancer. Methods and Materials: Intrafractional motion trajectories of 15 prostate cancer patients were the basis for this phantom study; prostate motion had been monitored with the Calypso System. An industrial robot moved a phantom along these trajectories, motion was detected via an infrared camera system, and the robotic HexaPOD couch was used for real-time counter-steering. Residual phantom motion during real-time tracking was measured with the infrared camera system. Film dosimetry was performed during delivery of 3-dimensional conformal radiation therapy (3D-CRT), step-and-shoot intensity modulated radiation therapy (IMRT), and volumetric modulated arc therapy (VMAT). Results: Motion of the prostate was largest in the anterior-posterior direction, with systematic ( N-Ary-Summation ) and random ({sigma}) errors of 2.3 mm and 2.9 mm, respectively; the prostate was outside a threshold of 5 mm (3D vector) for 25.0%{+-}19.8% of treatment time. Real-time tracking reduced prostate motion to N-Ary-Summation =0.01 mm and {sigma} = 0.55 mm in the anterior-posterior direction; the prostate remained within a 1-mm and 5-mm threshold for 93.9%{+-}4.6% and 99.7%{+-}0.4% of the time, respectively. Without real-time tracking, pass rates based on a {gamma} index of 2%/2 mm in film dosimetry ranged between 66% and 72% for 3D-CRT, IMRT, and VMAT, on average. Real-time tracking increased pass rates to minimum 98% on average for 3D-CRT, IMRT, and VMAT. Conclusions: Real-time couch tracking resulted in submillimeter accuracy for prostate cancer, which transferred into high dosimetric accuracy independently of whether 3D-CRT, IMRT, or VMAT was used.

62 RADIOLOGY AND NUCLEAR MEDICINE↗