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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Extracting the Quantum Hall Conductance from a Single Bulk Wave Function

In this work, we propose a new formula that extracts the quantum Hall conductance from a single (2+1)⁢ D gapped wave function. The formula applies to general many-body systems that conserve particle number, and is based on the concept of modular flow, i.e., unitary dynamics generated from the entanglement structure of the wave function. The formula is shown to satisfy all formal properties of the Hall conductance: it is odd under time reversal and reflection, even under charge conjugation, universal and topologically rigid in the thermodynamic limit. Further evidence for relating the formula to the Hall conductance is obtained from conformal field theory arguments. Finally, we numerically check the formula by applying it to a noninteracting Chern band where excellent agreement is obtained.

2-dimensional systems↗
DOE OSTI2024

Extracting Higher Central Charge from a Single Wave Function

A (2+1)D topologically ordered phase may or may not have a gappable edge, even if its chiral central charge c_ is vanishing. Recently, it was discovered that a quantity regarded as a "higher" version of chiral central charge gives a further obstruction beyond c_ to gapping out the edge. Here, in this Letter, we show that the higher central charges can be characterized by the expectation value of the partial rotation operator acting on the wave function of the topologically ordered state. This allows us to extract the higher central charge from a single wave function, which can be evaluated on a quantum computer. Our characterization of the higher central charge is analytically derived from the modular properties of edge conformal field theory, as well as the numerical results with the ν = 1/2 bosonic Laughlin state and the non-Abelian gapped phase of the Kitaev honeycomb model, which corresponds to U(1) 2 and Ising topological order, respectively. The Letter establishes a numerical method to obtain a set of obstructions to the gappable edge of (2+1)D bosonic topological order beyond c_, which enables us to completely determine if a (2+1)D bosonic Abelian topological order has a gappable edge or not. We also point out that the expectation values of the partial rotation on a single wave function put a constraint on the low-energy spectrum of the bulk-boundary system of (2+1)D bosonic topological order, reminiscent of the Lieb-Schultz-Mattis-type theorems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Nonperturbative Effects in Energy Correlators: From Characterizing Confinement Transition to Improving α s Extraction

Energy correlators provide a powerful observable to study fragmentation dynamics in QCD. We demonstrate that the leading nonperturbative corrections for projected N -point energy correlators are described by the same universal parameter for any N , which has already been determined from other event shape fits. Including renormalon-free nonperturbative corrections substantially improves theoretical predictions of energy correlators, notably the transition into the confining region at small angles. Nonperturbative corrections are shown to have a significant impact on α s extractions. Published by the American Physical Society 2024

Lee, Kyle (ORCID:0000000218272958)↗
DOE OSTI2024

Extracting off-diagonal order from diagonal basis measurements

Quantum gas microscopy has developed into a powerful tool to explore strongly correlated quantum systems. However, discerning phases with topological or off-diagonal long range order requires the ability to extract these correlations from site-resolved measurements. Here, we show that a multiscale complexity measure can pinpoint the transition to and from the bond ordered wave phase of the one-dimensional extended Hubbard model with an off-diagonal order parameter, sandwiched between diagonal charge and spin density wave phases, using only diagonal descriptors. We study the model directly in the thermodynamic limit using the recently developed variational uniform matrix product states algorithm, and draw our samples from degenerate ground states related by global spin rotations, emulating the projective measurements that are accessible in experiments. Our results will have important implications for the study of exotic phases using optical lattice experiments. Published by the American Physical Society 2024

1-dimensional systems↗
DOE OSTI2024

Extracting Topological Orders of Generalized Pauli Stabilizer Codes in Two Dimensions

In this paper, we introduce an algorithm for extracting topological data from translation invariant generalized Pauli stabilizer codes in two-dimensional systems, focusing on the analysis of anyon excitations and string operators. The algorithm applies to Z d qudits, including instances where d is a nonprime number. This capability allows the identification of topological orders that differ from the Z d toric codes. It extends our understanding beyond the established theorem that Pauli stabilizer codes for Z p qudits (with p being a prime) are equivalent to finite copies of Z p toric codes and trivial stabilizers. The algorithm is designed to determine all anyons and their string operators, enabling the computation of their fusion rules, topological spins, and braiding statistics. The method converts the identification of topological orders into computational tasks, including Gaussian elimination, the Hermite normal form, and the Smith normal form of truncated Laurent polynomials. Furthermore, the algorithm provides a systematic approach for studying quantum error-correcting codes. We apply it to various codes, such as self-dual CSS quantum codes modified from the two-dimensional honeycomb color code and non-CSS quantum codes that contain the double semion topological order or the six-semion topological order. Published by the American Physical Society 2024

Physics↗
DOE OSTI2025

First Global Extraction of Generalized Parton Distributions from Experiment and Lattice Data with Next-to-Leading-Order Accuracy

We report the first global extraction of generalized parton distributions, GUMP 1.0, by combining deeply virtual Compton scattering and 𝜌-meson production data from Jefferson Lab and the Hadron-Electron Ring Accelerator with global fits of parton distribution functions, charge form factors, and lattice quantum chromodynamics simulations. Using a conformal moment space parametrization, we achieve a unified description across low- and high-𝑥 regions at next to leading order accuracy in perturbative corrections. The results provide state-of-the-art generalized parton distributions consistent with almost all known facts, enabling three-dimensional nucleon imaging in impact parameter space and, at the same time, establishing a benchmark for future theoretical and experimental studies of the nucleon structure.

Form factors↗
DOE OSTI2025

Signal selection and model-independent extraction of the neutrino neutral-current single 𝜋 + cross section with the T2K experiment

This article presents a study of single 𝜋 + production in neutrino neutral-current interactions (NC⁢1⁢𝜋 + ) using the FGD1 hydrocarbon target of the ND280 detector of the T2K experiment. We report the largest sample of such events selected by any experiment, providing the first new data for this channel in over four decades and the first using a sub-GeV neutrino flux. The signal selection strategy and its performance are detailed together with validations of a robust cross section extraction methodology. The measured flux-averaged integrated cross-section is 𝜎 = (6.07 ± 1.22) × 10 −41 cm 2 /nucleon, 1.3⁢𝜎 above the NEUT v5.4.0 expectation.

Neutrino detection↗
DOE OSTI2019

Efficient data extraction from neutron time-of-flight spin-echo raw data

Neutron spin-echo spectrometers with a position-sensitive detector and operating with extended time-of-flight-tagged wavelength frames are able to collect a comprehensive set of data covering a large range of wavevector and Fourier time space with only a few instrumental settings in a quasi-continuous way. Extracting all the information contained in the raw data and mapping them to a suitable physical space in the most efficient way is a challenge. This article reports algorithms employed in dedicated software, DrSpine (data reduction for spin echo), that achieves this goal and yields reliable representations of the intermediate scattering function S(Q, t) independent of the selected `binning'.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Extraction of Plutonium-Containing Microcrystals from Hanford Soil using a Focused Ion Beam for Single-Crystal X-ray Diffraction Analysis

Herein we report the successful use of a focused ion beam/scanning electron microscope (FIB/SEM) to prepare microsamples of radioactive single-crystals for X-ray diffraction analysis. This technique was used to extract and analyze crystalline Pu-containing particles as small as 28 µm3 from Hanford soil taken from the 216-Z-9 waste crib which were then crystallographically characterized using single-crystal X-ray diffraction (SCXRD) to confirm the cubic structure of PuO2. As a systematic proof of concept, the technique was first tested using UO2 crystals milled into cubic shapes with approximate volumes 4620, 1331, 125, 8 and 1 µm3, respectively, in order to empirically determine the crystal size limits for characterization by a laboratory-based diffractometer with a sealed tube Mo or Ag anode X-ray source and a charge-coupled device (CCD) detector.

microcrystals, Plutomium, focused ion beam/scannin↗
DOE OSTI2019

Inverse Regression for Extraction of Tumor Site from Cancer Pathology Reports

Pathology reports are the primary source of information for cancer diagnosis of millions of the cancer patients across the United States. Cancer registries label these reports every year. The coded labels incorporate pertinent information such as cancer location, behavior, and histology. This information when combined with clinical information, medical imaging and even genomic information have a great potential to fuel discoveries in cancer research. The coding process is manual and requires many human experts to label the large volume of pathology reports in a timely manner. In this study, we have developed a supervised inverse regression based auto-labeler to automate the task. The experiments were conducted on a set of 942 pathology reports with human expert labels as the ground truth. We observed that the inverse regression based auto-labeler consistently performed better than or comparable to the best performing state-of-the-art method. These results demonstrate the potential of inverse regression for reliable information extraction from the pathology reports.

Dubey, Abhishek↗
DOE OSTI2019

Model-based Hyperparameter Optimization of Convolutional Neural Networks for Information Extraction from Cancer Pathology Reports on HPC

Finding optimal hyperparameters is necessary to identify the best performing deep learning models but the process is costly. In this paper, we applied model-based optimization, also known as Bayesian optimization, using the CANDLE framework implemented on a High-Performance Computing environment. As a use case we selected information extraction from cancer pathology reports using a multi-task convolutional neural network, and hierarchical convolutional attention network to be optimized. We utilized a synthesized text corpus of 8,000 training cases and 2,000 validation cases with four types of clinical task labels including primary cancer site, laterality, behavior, and histological grade. We demonstrated that hyperparameter optimization using the CANDLE framework is a feasible approach with respect to both scalability and clinical task performance.

Yoon, Hong-Jun↗
DOE OSTI2021

Battle of the Defaults: Extracting Performance Characteristics of HDF5 under Production Load

Popular parallel I/O libraries, such as HDF5, provide tuning parameters to obtain superior performance. However, the selection of effective parameters on production systems is complex due to the interdependence of I/O software and file system layers. Hence, application developers typically use the default parameters and often experience poor I/O performance. This work conducts a benchmarking-based analysis on the HDF5 behaviors with a wide variety of I/O patterns to extract performance characteristics under the production workload. To make the analysis well controlled, we exercise I/O benchmarks on POSIX-IO, MPI-IO, and HDF5 using the same I/O patterns and in the same jobs. To address high performance variability in production environments, we repeat the benchmarks across I/O patterns, storage devices, and time intervals. Based on the results, we identified consistent HDF5 behaviors that appropriate configurations and operations on dataset layout and file-metadata placement can improve performance significantly. We apply our findings and evaluate the tuned I/O library on two supercomputers: Summit and Cori. The results show that our tuned parameters can achieve more than 10× I/O performance speedup than that with default parameters on both systems, suggesting the effectiveness, stability, and generality of our solution.

Xie, Bing↗
DOE OSTI2018

A Comparison of Machine Learning Techniques to Extract Human Settlements from High Resolution Imagery

Two machine learning techniques were developed to extract human settlements from very high resolution (VHR) satellite images of 3 provinces in Afghanistan: Logar, Panjsher, and Wardak. The results were then compared with analyst verified reference data information known as the LandScan Settlement Layer (LandScan SL).[1] This study attempts to compare settlement mapping results from a support vector machine (SVM) classifier specifically integrated in a current settlement mapping framework and a deep learner utilizing a convolutional neural network (CNN) approach. By comparing the results from the SVM and the CNN to the reference data information we demonstrate that the CNN yields more accurate results overall, in terms of overall pixel cells, and the SVM performs more accurately in omission, based on derived statistics against the reference data information.

Weaver, Jeanette E↗
DOE OSTI2024

Efficient Extraction Of Building Elevation Attributes For Flood Risk Management Using Airborne LiDAR Data

In this paper, we address the need for extracting two key building elevation attributes—Lowest Adjacent Grade (LAG) and Highest Adjacent Grade (HAG)—which are crucial for effective flood risk management. Conventional methods, involving onsite surveying or the use of optical imagery-derived building footprints combined with Digital Elevation Models (DEMs), often face misalignment and time discrepancy issues due to varied remote sensing sources. We introduce a new, scalable method that exclusively relies on airborne LiDAR data to overcome these challenges. Our approach employs an object-based ground filtering technique, and the results were evaluated using two different DEMs and building footprint sets. The findings demonstrate that our single-source method, utilizing only airborne LiDAR data, significantly improves the accuracy of LAG and HAG calculations compared to traditional methods that use hand-digitized building footprints. The proposed approach offers a solution for comprehensive flood risk management endeavors.

Song, Hunsoo↗
DOE OSTI2025

The Upgrade of the SNS Extraction Kicker Power Supplies for the Proton Power Upgrade

The Proton Power Upgrade (PPU) project at the Spallation Neutron Source (SNS) aims to enhance the linear accelerator's power output from 1.4 to 2.8 megawatts. A critical focus lies on upgrading the Extraction Kicker Power Supplies to handle the amplified beam power. The existing capacitor charging power supplies lacked the capability to charge the Blumlein-type Pulse Forming Network (PFN) to the required 40 kV at a repetition rate of 60 Hz. To address this limitation, an initial solution involving the use of a resonant charging circuit was proposed. However, a challenge arose with a self-firing issue in the thyristor switch, which proved unsolvable within the given timeframe. Facing a critical decision point in the project, an alternative approach was explored: integrating a supplementary power supply to enhance the overall power capacity. This solution was tested and ultimately chosen as the path forward. To accommodate the additional power supply, the power distribution system had to undergo upgrades. Throughout this endeavor, a comprehensive examination of the system took place, with meticulous identification of key components. This paper delves into the technical challenges encountered during the process and the corresponding solutions that were implemented.

Tan, Yugang [ORNL] (ORCID:0000000155968252)↗
DOE OSTI2021

Progress in development of pulsed resonant charging power supply for the Spallation Neutron Source extraction kicker PFN system

A conceptual design of the pulsed resonant charging power supply (RCPS) for the beam extraction system of the Spallation Neutron Source (SNS) at the Oak Ridge National Laboratory (ORNL) was previously reported at the 2019 IEEE Pulsed Power & Plasma Science Conference (PPPS 2019) [1]. Development and testing of the prototype supply continued through the year to finalize the design ahead of the Proton Power Upgrade (PPU). Testing revealed reliability issues with the original resonant charging scheme related to the step-up transformer core. Additional components were incorporated into the system, and some of the original prototype components were replaced to improve performance and reliability of the power supply. This paper describes the changes in the resonant charging scheme, presents the results of testing of the improved prototype at full power level, and shows the final design of the RCPS.

Peplov, Vladimir↗
DOE OSTI2026

Development of Design for the STS Extraction Magnet System

The Oak Ridge National Laboratory STS Project will enhance the Spallation Neutron Source by adding a new neutron source. The upgrade includes a 30% increase in beam energy and a 50% boost in beam current, doubling the accelerator's power capability to 2.8 MW. The Ring-to-Second-Target Beam Transport (RTST) system is vital in directing high-energy proton beams to the new second target station. New magnets have to fit into a restricted space within the existing beamline to add the new extraction line. New, fast kicker magnets (Pulsed Dipole), a focusing quad with an aperture for both beamlines (Large Quad) and the replacement of existing 21Q40 Quads with 'Narrow Quads' having identical fields as the existing design are Fermilab's responsibility. The design of these magnets poses unique challenges, as in addition to the high requirements on the quality of magnetic fields, they are subject to major restrictions related to their dimensions.

Chernenok, V. [Fermilab] (ORCID:0009000778148215)↗
DOE OSTI2021

Extracting Resilience Metrics From Distribution Utility Data Using Outage and Restore Process Statistics

Resilience curves track the accumulation and restoration of outages during an event on an electric distribution grid. We show that a resilience curve generated from utility data can always be decomposed into an outage process and a restore process and that these processes generally overlap in time. We use many events in real utility data to characterize the statistics of these processes, and derive formulas based on these statistics for resilience metrics such as restore duration, customer hours not served, and outage and restore rates. The formulas express the mean value of these metrics as a function of the number of outages in the event. We also give a formula for the variability of restore duration, which allows us to predict a maximum restore duration with 95% confidence. Overall, we give a simple and general way to decompose resilience curves into outage and restore processes and then show how to use these processes to extract resilience metrics from standard distribution system data.

24 POWER TRANSMISSION AND DISTRIBUTION↗