SEARCH · Engineering Papers

Results for “Particle data analysis”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16

All sources NASA NTRS DOE OSTI

DOE OSTI2025

ASCR Workshop Position Paper: Challenges and Opportunities in High Energy Physics

High energy particle physics and cosmology concern themselves with estimating fundamental parameters of nature, such as the masses and interactions of fundamental particles like the Higgs boson and the rate of expansion of the universe. In doing so, they analyze exabyte-scale datasets, some of the largest in all of science, and face many challenges in subsequent data analysis. These challenges are shared between the two disciplines, but we focus on particle physics to highlight one specific domain. In particle physics, the standard method for estimating parameters involves performing Monte Carlo (MC) integration as a function of both parameters of interest and nuisance parameters using an expensive simulator, counting the number of observed collision events (i.i.d. samples) from an experiment in the corresponding integration domains, and forming a Poisson likelihood function. This likelihood function is then used in a Frequentist manner to construct a maximum likelihood point estimate (MLE) and confidence set for the parameters. To sufficiently populate the high-dimensional integration domains, simulators consume billions of CPU-hours annually and produce hundreds of petabytes of intermediate output data. Several techniques have been developed to: optimize definitions of the integration domains so as to be maximally sensitive to a particular subset of parameters, efficiently estimate the integrals, and build robust surrogate models by interpolating between integral evaluations at different parameter points. One can view this whole endeavor as classical Simulation-Based Inference (SBI).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

End-to-End Pipeline for Trigger Detection on Hit and Track Graphs

There has been a surge of interest in applying deep learning in particle and nuclear physics to replace labor-intensive offline data analysis with automated online machine learning tasks. This paper details a novel AI-enabled triggering solution for physics experiments in Relativistic Heavy Ion Collider and future Electron-Ion Collider. The triggering system consists of a comprehensive end-to-end pipeline based on Graph Neural Networks that classifies trigger events versus background events, makes online decisions to retain signal data, and enables efficient data acquisition. Here, the triggering system first starts with the coordinates of pixel hits lit up by passing particles in the detector, applies three stages of event processing (hits clustering, track reconstruction, and trigger detection), and labels all processed events with the binary tag of trigger versus background events. By switching among different objective functions, we train the Graph Neural Networks in the pipeline to solve multiple tasks: the edge-level track reconstruction problem, the edge-level track adjacency matrix prediction, and the graph-level trigger detection problem. We propose a novel method to treat the events as track-graphs instead of hit-graphs. This method focuses on intertrack relations and is driven by underlying physics processing. As a result, it attains a solid performance (around 72% accuracy) for trigger detection and outperforms the baseline method using hit-graphs by 2% higher accuracy.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1983

Pioneer 11 observations of trapped particle absorption by Amalthea

The discovery of a microsignatury of trapped radiation in the Amalthea orbit as detected by Pioneer 11 in a flyby of Juptier in 1974 is reported and its implications for the radial diffusion coefficient in Jupiter's inner magnetosphere are discussed. A low energy telescope registered the absorption of low-energy protons as a function of the magnetic L shell durig inbound and outbound trajectories. Drift velocities of the 1 MeV particles were calculated. No correspondingly heightened effects were observed from high-energy electrons or heavier nuclei. Further analysis of the 0.5-8.7 MeV protons showed data to be consistent erosion of the particle drift shadows by a diffusion process. A limit was calculated for the highest diffusion coefficient value for the 1 MeV protons at the Amalthea orbit. The results indicate that the diffusion is driven by fluctuating electric or magnetic fields.

Mckibben, R. B.↗

DOE OSTI2020

Reconstruction of effective potential from statistical analysis of dynamic trajectories

The broad incorporation of microscopic methods is yielding a wealth of information on the atomic and mesoscale dynamics of individual atoms, molecules, and particles on surfaces and in open volumes. Analysis of such data necessitates statistical frameworks to convert observed dynamic behaviors to effective properties of materials. Here, we develop a method for the stochastic reconstruction of effective local potentials solely from observed structural data collected from molecular dynamics simulations (i.e., data analogous to those obtained via atomically resolved microscopies). Using the silicon vacancy defect in graphene as a model, we apply the statistical framework presented herein to reconstruct the free energy landscape from the calculated atomic displacements. Evidence of consistency between the reconstructed local potential and the trajectory data from which it was produced is presented, along with a quantitative assessment of the uncertainty in the inferred parameters.

74 ATOMIC AND MOLECULAR PHYSICS↗

NASA NTRS1985

The LDEF interplanetary dust experiment

Explorer 46 data and the Long Duration Exposure Facility (LDEF) interplanetary dust experiment are examined. Analysis of the Explorer 46 data reveals the existence of particles of 0.1 micron and a mass of 1 x 10 to the -16th gm, the injection of the submicron particles directly by a comet (injection mass of about 5000 tons), and a submicron particle lifetime of about three years. The applications of LDEF data to particles in hyperbolic orbits, particle swarms, morning-to-evening asymmetry, the effects of the earth's orbit eccentricity, and the presence of interstellar dust are discussed. The effects of space debris on data collection are considered.

Singer, S. F.↗

NASA NTRS2006

The Alpha Particle X-Ray Spectrometer (APXS): Results from Gusev Crater and Calibration Report

The chemical composition of rocks and soils on Mars analyzed during the Mars Exploration Rover Spirit Mission was determined by X-ray analyses with the Alpha Particle X-Ray Spectrometer (APXS). Details of the data analysis method and the instrument calibration are presented. Measurements performed on Mars to address geometry effects and background contributions are shown. Cross calibration measurements among several instrument sensors and sources are discussed. An unintentional swap of the two flight instruments is evaluated. New concentration data acquired during the first 470 sols of rover Spirit in Gusev Crater are presented. There are two geological regions, the Gusev plains and the Columbia Hills. The plains contain soils that are very similar to previous landing sites on Mars. A meteoritic component in the soil is identified. Rocks in the plains revealed thin weathering rinds. The underlying abraded rock was classified as primitive basalt. One of these rocks contained significant Br that is probably associated with vein-filling material of different composition. One of the trenches showed large subsurface enrichments of Mg, S, and Br. Disturbed soils and rocks in the Columbia Hills revealed different elemental compositions. These rocks are significantly weathered and enriched in mobile elements, such as P, S, Cl, or Br. Even abraded rock surfaces have high Br concentrations. Thus, in contrast to the rocks and soils in the Gusev Plains, the Columbia Hills material shows more significant evidence of ancient aqueous alteration.

Gellert, R.↗

NASA NTRS1996

Solar cycle dynamics of solar, magnetospheric, and heliospheric particles, and long-term atmospheric coupling: SAMPLEX

This report summarizes science analysis activities by the SAMPEX mission science team during the period during the period July 1, 1995 through July 1, 1996. Bibliographic entries for 1995 and 1996 to date (July 1996) are included. The SAMPEX science team was extremely active, with 20 articles published or submitted to refereed journals, 18 papers published in their entirety in Conference Proceedings, and 53 contributed papers, seminars, and miscellaneous presentations. The bibliography at the end of this report constitutes the primary description of the research activity. Science highlights are given under the major activity headings of anomalous cosmic rays, solar energetic particles, magnetospheric precipitating electrons, trapped H and He isotopes, and data analysis activities.

Mason, G. M.↗

NASA NTRS1987

Fluid particle motion and Lagrangian velocities for pulsatile flow through a femoral artery branch model

A flow visualization study using selective dye injection and frame by frame analysis of a movie provided qualitative and quantitative data on the motion of marked fluid particles in a 60 degree artery branch model for simulation of physiological femoral artery flow. Physical flow features observed included jetting of the branch flow into the main lumen during the brief reverse flow period, flow separation along the main lumen wall during the near zero flow phase of diastole when the core flow was in the downstream direction, and inference of flow separation conditions along the wall opposite the branch later in systole at higher branch flow ratios. There were many similarities between dye particle motions in pulsatile flow and the comparative steady flow observations.

Cho, Y. I.↗

DOE OSTI2021

A case study on parallel HDF5 dataset concatenation for high energy physics data analysis

In High Energy Physics (HEP), experimentalists generate large volumes of data that, when analyzed, helps us better understand the fundamental particles and their interactions. This data is often captured in many files of small size, creating a data management challenge for scientists. In order to better facilitate data management, transfer, and analysis on large scale platforms, it is advantageous to aggregate data further into a smaller number of larger files. However, this translation process can consume significant time and resources, and if performed incorrectly the resulting aggregated files can be inefficient for highly parallel access during analysis on large scale platforms. In this paper, we present our case study on parallel I/O strategies and HDF5 features for reducing data aggregation time, making effective use of compression, and ensuring efficient access to the resulting data during analysis at scale. We focus on NOvA detector data in this case study, a large-scale HEP experiment generating many terabytes of data. Here, the lessons learned from our case study inform the handling of similar datasets, thus expanding community knowledge related to this common data management task.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1993

Mass and spatial distribution of carbonaceous component in Comet Halley

Cometary grains containing large amounts of carbon and/or organic matter were discovered by in situ measurements of cometary dust composition during VEGA and GIOTTO fly-by missions. In accordance with the classification for the data of PUMA-1 and PUMA-2 mass-spectrometers on board the VEGA spacecraft, particles with a ratio of C to any rock-forming element (Mg, Si, Fe, Ca etc.) greater than 10, were categorized as CHON. There are 464 such particles in PUMA-1 data and 51 in PUMA-2 data. Application of cluster analysis to these grains revealed several distinct compositional classes, namely: (H,C,N,O), (H,C,N), (H,C), (H,C,O), (C,N), (C,O), (C,N,O), and (C). Similar classes were identified among particles analyzed by PIA. Also, about a third of all particles fell into groups (H) and (O) characterized by abundances of these elements beyond chemically reasonable limits.

Fomenkova, M.↗

DOE OSTI2024

Observation of Enhanced Long-Range Elliptic Anisotropies Inside High-Multiplicity Jets in p p Collisions at s = 13 TeV

A search for collective effects inside jets produced in proton-proton collisions is performed via correlation measurements of charged particles using the CMS detector at the CERN LHC. The analysis uses data collected at a center-of-mass energy of s = 13 TeV , corresponding to an integrated luminosity of 138 fb − 1 . Jets are reconstructed with the anti- k T algorithm with a distance parameter of 0.8 and are required to have transverse momentum greater than 550 GeV and pseudorapidity | η jet | < 1.6 . Two-particle correlations among the charged particles within the jets are studied as functions of the particles’ azimuthal angle and pseudorapidity separations ( Δ ϕ * and Δ η * ) in a jet coordinate basis, where particles’ η * , ϕ * are defined relative to the direction of the jet. The correlation functions are studied in classes of in-jet charged-particle multiplicity up to N ch j ≈ 100 . Fourier harmonics are extracted from long-range azimuthal correlation functions to characterize azimuthal anisotropy for | Δ η * | > 2 . For low- N ch j jets, the long-range elliptic anisotropic harmonic, v 2 * , is observed to decrease with N ch j . This trend is well described by Monte Carlo event generators. However, a rising trend for v 2 * emerges at N ch j ≳ 80 , hinting at a possible onset of collective behavior, which is not reproduced by the models tested. This observation yields new insights into the dynamics of jet evolution in the vacuum. © 2024 CERN, for the CMS Collaboration 2024 CERN

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Multimodal X-ray nano-spectromicroscopy analysis of chemically heterogeneous systems

Abstract Understanding the nanoscale chemical speciation of heterogeneous systems in their native environment is critical for several disciplines such as life and environmental sciences, biogeochemistry, and materials science. Synchrotron-based X-ray spectromicroscopy tools are widely used to understand the chemistry and morphology of complex material systems owing to their high penetration depth and sensitivity. The multidimensional (4D+) structure of spectromicroscopy data poses visualization and data-reduction challenges. This paper reports the strategies for the visualization and analysis of spectromicroscopy data. We created a new graphical user interface and data analysis platform named XMIDAS (X-ray multimodal image data analysis software) to visualize spectromicroscopy data from both image and spectrum representations. The interactive data analysis toolkit combined conventional analysis methods with well-established machine learning classification algorithms (e.g. nonnegative matrix factorization) for data reduction. The data visualization and analysis methodologies were then defined and optimized using a model particle aggregate with known chemical composition. Nanoprobe-based X-ray fluorescence (nano-XRF) and X-ray absorption near edge structure (nano-XANES) spectromicroscopy techniques were used to probe elemental and chemical state information of the aggregate sample. We illustrated the complete chemical speciation methodology of the model particle by using XMIDAS. Next, we demonstrated the application of this approach in detecting and characterizing nanoparticles associated with alveolar macrophages. Our multimodal approach combining nano-XRF, nano-XANES, and differential phase-contrast imaging efficiently visualizes the chemistry of localized nanostructure with the morphology. We believe that the optimized data-reduction strategies and tool development will facilitate the analysis of complex biological and environmental samples using X-ray spectromicroscopy techniques.

36 MATERIALS SCIENCE↗

NASA NTRS1984

Beta systems error analysis

The atmospheric backscatter coefficient, beta, measured with an airborne CO Laser Doppler Velocimeter (LDV) system operating in a continuous wave, focussed model is discussed. The Single Particle Mode (SPM) algorithm, was developed from concept through analysis of an extensive amount of data obtained with the system on board a NASA aircraft. The SPM algorithm is intended to be employed in situations where one particle at a time appears in the sensitive volume of the LDV. In addition to giving the backscatter coefficient, the SPM algorithm also produces as intermediate results the aerosol density and the aerosol backscatter cross section distribution. A second method, which measures only the atmospheric backscatter coefficient, is called the Volume Mode (VM) and was simultaneously employed. The results of these two methods differed by slightly less than an order of magnitude. The measurement uncertainties or other errors in the results of the two methods are examined.

Source record↗

DOE OSTI2024

Multimodal Chemical Characterization of Brown Carbon in Atmosphere and Snowpack during SAIL Field Campaign Report

The main goal of this field project was to characterize the chemical and physical properties of light-absorbing particles (LAP) present in the atmosphere and snowpack. The specific field efforts included: 1) online measurement and sampling of light-absorbing particles using a Magee Scientific model AE33 aethalometer (AE33) and a time-resolved aerosol collector (TRAC); and 2) sampling of snowpack during observed events of LAP deposition on snow, confirmed by onsite U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility measurements and meteorological data. The ongoing research objectives of our follow-up sample and data analysis include: 1) Characterization of aerosol regimes and sources, identifying particle-type populations, mixing states, and atmospheric transformations based on correlative analysis of our detailed chemical imaging and chemical characterization measurements and real-time records from the second ARM Mobile Facility (AMF2) and other instruments available from the Surface Atmosphere Integrated Field Laboratory (SAIL) experiment; 2) Assessment of the optical and chemical properties of snowpack deposits to investigate how aerosol deposition influences snowpack lifetime.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2006

Simultaneous observation of the radiation environment inside and outside the ISS

The low-Earth orbit (LEO) radiation environment has been directly observed by the IV and EV charged particle directional spectrometers (CPDS) aboard the International Space Station (ISS). The EV instrument is mounted on the S0 truss of the ISS and consists of three separate silicon detector telescopes which are oriented in different directions. The IV instrument is a single silicon detector telescope located inside the US Laboratory module of the ISS. We report on the current state of the data analysis for these instruments, which includes the proton and He stopping particle spectra, relative CNO abundances, LET spectra, and measured dose rate as a function of time.

Lee, K. T.↗

DOE OSTI2020

Quantum Algorithms for Collider Physics (Final Report)

The goal of this project was to unite powerful analysis techniques in high-energy physics (HEP) with cutting-edge advances in quantum information science (QIS). Almost every event at the Large Hadron Collider (LHC) involves jets, collimated sprays of particles that are copiously produced in proton-proton collisions. Current LHC algorithms to identify and classify jets are constrained by the limits of classical computation. Quantum algorithms could fundamentally change how collider data is analyzed, by speeding up existing classical algorithms and by enabling new quantum jet representations. By exploiting the capabilities of quantum computation, this research confronted the challenge of data analysis in collider physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1983

Test results of modified electrical charged particle generator for application to fog dispersal

Modifications to a charged particle generator for use in fog dispersal applications were made and additional testing carried out. The modified nozzle, however, did not work as planned, and reported results are the unmodified nozzle. The addition of a positive displacement pump to supply the liquid water was highly successful. Measurements of the generator output current were made with a cylindrical collector system as well as with the needle probe used in previous studies. Measurements with the cylindrical collector and the needle probe showed identical agreement within the variability of the experiment. A high-voltage prove was purchased, and measurements of the corona voltage as well as the voltage variation in the charged particle jet were made. Electric fields in the vertical direction on the order of 1,000,000 v/m were measured. The voltage distribution along the centerline of the jet was compared with the numerical solutions of the Poisson equation and showed very good agreement. Velocity measurements using a pitot tube were made. The resulting measurements were compared with theoretical and other reported experimental results. The measured data showed the appropriate trends and agreed well with reported results. Based on the measured current-to-mass ratio from the charged particle generator, a calculation of the average droplet size was made. Droplet sizes were estimated to range between 0.8 and 0.4 microns. Using measured data, an analysis of the height to which the droplet can be dispersed by the charged particle generator was made. Although the mathematical model is highly simplified, the results indicated that particles would achieve heights on the order of 80 m.

Frost, W.↗

NASA NTRS2001

Retrieval of Polar Stratospheric Cloud Microphysical Properties from Lidar Measurements: Dependence on Particle Shape Assumptions

A retrieval algorithm has been developed for the microphysical analysis of polar stratospheric cloud (PSC) optical data obtained using lidar instrumentation. The parameterization scheme of the PSC microphysical properties allows for coexistence of up to three different particle types with size-dependent shapes. The finite difference time domain (FDTD) method has been used to calculate optical properties of particles with maximum dimensions equal to or less than 2 mu m and with shapes that can be considered more representative of PSCs on the scale of individual crystals than the commonly assumed spheroids. Specifically. these are irregular and hexagonal crystals. Selection of the optical parameters that are input to the inversion algorithm is based on a potential data set such as that gathered by two of the lidars on board the NASA DC-8 during the Stratospheric Aerosol and Gas Experiment 0 p (SAGE) Ozone Loss Validation experiment (SOLVE) campaign in winter 1999/2000: the Airborne Raman Ozone and Temperature Lidar (AROTEL) and the NASA Langley Differential Absorption Lidar (DIAL). The 0 microphysical retrieval algorithm has been applied to study how particle shape assumptions affect the inversion of lidar data measured in leewave PSCs. The model simulations show that under the assumption of spheroidal particle shapes, PSC surface and volume density are systematically smaller than the FDTD-based values by, respectively, approximately 10-30% and approximately 5-23%.

Reichardt, J.↗