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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Nucleon form factors and parton distributions in nonlocal chiral effective theory

In this work, we present a review of recent applications of nonlocal chiral effective theory to hadron structure studies. Starting from a nonlocal meson-baryon effective chiral Lagrangian, we show how the introduction of a correlation function representing the finite extent of hadrons regularizes the meson loop integrals and introduces momentum dependence in vertex form factors in a gauge invariant manner. We apply the framework to the calculation of nucleon electromagnetic form factors, unpolarized and polarized parton distributions, as well as transverse momentum dependent distributions and generalized parton distributions. Assuming that the nonlocal behavior is a general property of all interactions, we also discuss the application to the lepton anomalous magnetic moment in nonlocal QED.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1988

Data traffic reduction schemes for sparse Cholesky factorizations

Load distribution schemes are presented which minimize the total data traffic in the Cholesky factorization of dense and sparse, symmetric, positive definite matrices on multiprocessor systems with local and shared memory. The total data traffic in factoring an n x n sparse, symmetric, positive definite matrix representing an n-vertex regular 2-D grid graph using n (sup alpha), alpha is equal to or less than 1, processors are shown to be O(n(sup 1 + alpha/2)). It is O(n(sup 3/2)), when n (sup alpha), alpha is equal to or greater than 1, processors are used. Under the conditions of uniform load distribution, these results are shown to be asymptotically optimal. The schemes allow efficient use of up to O(n) processors before the total data traffic reaches the maximum value of O(n(sup 3/2)). The partitioning employed within the scheme, allows a better utilization of the data accessed from shared memory than those of previously published methods.

Naik, Vijay K.↗
DOE OSTI2020

Distributed-Memory Parallel Symmetric Nonnegative Matrix Factorization

We develop the first distributed-memory parallel implementation of Symmetric Nonnegative Matrix Factorization (SymNMF), a key data analytics kernel for clustering and dimensionality reduction. Our implementation includes two different algorithms for SymNMF, which give comparable results in terms of time and accuracy. The first algorithm is a parallelization of an existing sequential approach that uses solvers for non symmetric NMF. The second algorithm is a novel approach based on the Gauss-Newton method. It exploits second-order information without incurring large computational and memory costs. We evaluate the scalability of our algorithms on the Summit system at Oak Ridge National Laboratory, scaling up to 128 nodes (4,096 cores) with 70% efficiency. Additionally, we demonstrate our software on an image segmentation task.

Eswar, Srinivas↗
DOE OSTI2025

Generalized parton distributions and gravitational form factors at large momentum transfer

Within the soft collinear effective theory (SCET), we derive a factorization theorem which resums Sudakov logarithms (α s ln 2 ( –t)) n to all orders in the quark-in-quark generalized parton distribution (GPD) at large momentum transfer t, and perform a consistency check to one-loop. We show that the same Sudakov factor appears in the ‘Feynman’ contribution to the GPDs of the nucleon. Our result enables the resummation of all the large logarithms ln Q 2 and ln 2 t in exclusive processes with two hard scales Λ$^{2}_{QCD}$ ≪ |t| ≪ Q 2 . We also present a SCET power counting analysis of the Feynman contributions to the GPDs and show that the x-dependence of GPDs factorizes at large-t with controlled corrections. This in particular implies that any ratio of GPD moments such as the electromagnetic and gravitational form factors (GFF) is perturbatively calculable in this approximation. Furthermore, we identify a novel order α s power-law t-dependence in the GPD and the D-type GFF that will dominate over the standard order α$^{2}_{s}$ ‘leading twist’ asymptotic contribution in the phenomenologically relevant region of t.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1994

Improved load distribution in parallel sparse Cholesky factorization

Compared to the customary column-oriented approaches, block-oriented, distributed-memory sparse Cholesky factorization benefits from an asymptotic reduction in interprocessor communication volume and an asymptotic increase in the amount of concurrency that is exposed in the problem. Unfortunately, block-oriented approaches (specifically, the block fan-out method) have suffered from poor balance of the computational load. As a result, achieved performance can be quite low. This paper investigates the reasons for this load imbalance and proposes simple block mapping heuristics that dramatically improve it. The result is a roughly 20% increase in realized parallel factorization performance, as demonstrated by performance results from an Intel Paragon system. We have achieved performance of nearly 3.2 billion floating point operations per second with this technique on a 196-node Paragon system.

Rothberg, Edward↗
DOE OSTI2021

Developing Generic Prior Distributions for Common Cause Failure Alpha Factors and Causal Alpha Factors

This report is a revision of the original report, INL/LTD-17-43723. Distribution of the original report was to the Nuclear Regulatory Commission (NRC) only, and the report was not made available to the public. The original report was revised as this report for public distribution. This report presents the latest update of generic prior distributions for common cause failure (CCF) alpha factors, as well as the development of new generic prior distributions for CCF causal alpha factors. The history of CCF treatment and parameter estimations is reviewed. The existing process for developing generic prior distributions is reviewed and used to develop new priors for CCF alpha factors and causal alpha factors. For causal alpha factors, different priors are developed for the five different CCF cause groups: Component (GC), Design (GD), Environment (GE), Human (GH), and Other (GO). These generic prior distributions could be used in the Standardized Plant Analysis Risk (SPAR) models for CCF parameter estimation. The issues and preliminary thoughts regarding prior distribution development are documented. Potential future work is then proposed for improving the process of developing priors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1998

A Distributed Simulation Facility to Support Human Factors Research in Advanced Air Transportation Technology

A distributed real-time simulation of the civil air traffic environment developed to support human factors research in advanced air transportation technology is presented. The distributed environment is based on a custom simulation architecture designed for simplicity and flexibility in human experiments. Standard Internet protocols are used to create the distributed environment, linking all advanced cockpit simulator, all Air Traffic Control simulator, and a pseudo-aircraft control and simulation management station. The pseudo-aircraft control station also functions as a scenario design tool for coordinating human factors experiments. This station incorporates a pseudo-pilot interface designed to reduce workload for human operators piloting multiple aircraft simultaneously in real time. The application of this distributed simulation facility to support a study of the effect of shared information (via air-ground datalink) on pilot/controller shared situation awareness and re-route negotiation is also presented.

Amonlirdviman, Keith↗
DOE OSTI2024

Proton’s gluon GPDs at large skewness and gravitational form factors from near threshold heavy quarkonium photoproduction

We study the exclusive near threshold photoproduction of heavy quarkonium in the framework of the generalized parton distribution (GPD) factorization, taking the 𝐽/𝜓 production as an example. Because of the threshold kinematics, the Compton-like amplitudes are related to gluon GPDs at large skewness 𝜉, distinct from the common kinematics in asymptotic high energy where the skewness is typically small. We discuss the nature of large-𝜉 expansion of these amplitudes in terms of the moments of gluon GPDs in the large-𝜉 limit. Based on that, we propose several ways to extract the first few moments of the gluon GPDs from these amplitudes, with the leading ones corresponding to the gluonic gravitational or energy-momentum tensor form factors (GFFs). We apply these methods to analyze the recent near threshold 𝐽/𝜓 production measurements by the 𝐽/𝜓 007 experiment and GlueX Collaboration and find that the 𝜉 scaling of the measured differential cross sections is consistent with the asymptotic behavior. However, the current data are not accurate enough yet for a complete determination of the gluonic GFFs, and therefore we consider some prospects for better extractions in the future.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2012

Snow Dunes: A Controlling Factor of Melt Pond Distribution on Arctic Sea Ice

The location of snow dunes over the course of the ice-growth season 2007/08 was mapped on level landfast first-year sea ice near Barrow, Alaska. Landfast ice formed in mid-December and exhibited essentially homogeneous snow depths of 4-6 cm in mid-January; by early February distinct snow dunes were observed. Despite additional snowfall and wind redistribution throughout the season, the location of the dunes was fixed by March, and these locations were highly correlated with the distribution of meltwater ponds at the beginning of June. Our observations, including ground-based light detection and ranging system (lidar) measurements, show that melt ponds initially form in the interstices between snow dunes, and that the outline of the melt ponds is controlled by snow depth contours. The resulting preferential surface ablation of ponded ice creates the surface topography that later determines the melt pond evolution.

arctic↗
NASA NTRS2002

Materials Science Research Rack-1 Fire Suppressant Distribution Test Report

Fire suppressant distribution testing was performed on the Materials Science Research Rack-1 (MSRR-1), a furnace facility payload that will be installed in the U.S. Lab module of the International Space Station. Unlike racks that were tested previously, the MSRR-1 uses the Active Rack Isolation System (ARIS) to reduce vibration on experiments, so the effects of ARIS on fire suppressant distribution were unknown. Two tests were performed to map the distribution of CO2 fire suppressant throughout a mockup of the MSRR-1 designed to have the same component volumes and flowpath restrictions as the flight rack. For the first test, the average maximum CO2 concentration for the rack was 60 percent, achieved within 45 s of discharge initiation, meeting the requirement to reach 50 percent throughout the rack within 1 min. For the second test, one of the experiment mockups was removed to provide a worst-case configuration, and the average maximum CO2 concentration for the rack was 58 percent. Comparing the results of this testing with results from previous testing leads to several general conclusions that can be used to evaluate future racks. The MSRR-1 will meet the requirements for fire suppressant distribution. Primary factors that affect the ability to meet the CO2 distribution requirements are the free air volume in the rack and the total area and distribution of openings in the rack shell. The length of the suppressant flowpath and degree of tortuousness has little correlation with CO2 concentration. The total area of holes in the rack shell could be significantly increased. The free air volume could be significantly increased. To ensure the highest maximum CO2 concentration, the PFE nozzle should be inserted to the stop on the nozzle.

Wieland, P. O.↗