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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Involving the new generations in particle physics endeavours

Since 1984 INFN and University of Pisa scientists performing experiments at Fermilab have been running a two-month summer training program for Italian students at the lab. In 1984 the program involved only a few physics students from the University of Pisa, but it was later extended to other INFN groups and to engineering students. Since 2004 the program has been supported in part by the US Department of Energy (DOE) in the frame of an exchange agreement with INFN and has been run by the Cultural Association of Italians at Fermilab (CAIF). In 2007 the Sant’Anna School of Advanced Studies (Pisa) established an agreement with Fermilab to share the cost of four engineering students each year. In the almost 40 years of its history, the program has hosted at Fermilab approximately 550 Italian students from more than 20 Italian universities and from some non-Italian universities. In addition, in the years 2010-2019, with the support of the Italian National Institute of Astrophyics (INAF), the Italian Space Agency (ASI), and CAIF, 30 students were hosted in other US laboratories and universities. The Fermilab training programs spanned from data analysis to design and construction of particle detectors and accelerator components, R/D on superconductive elements, theory of accelerators, and analysis of astrophysical data. At the other US laboratories the offered training was on Space Science. In 2015 the University of Pisa endorsed the program as one of its own Summer Schools. The interns are enrolled as Pisa students for the duration of the internship. They are required to write summary reports published in the Fermilab and University of Pisa web pages. Upon positive evaluation by a University board, students are acknowledged 6 ECTS credits. The entire program is expected to expand further under CAIF management. An agreement has been signed between ASI and CAIF, for ASI to support yearly three two-months fellowships in US space science. In the following we inform on student recruiting, training programs, and final evaluation

Barzi, E.↗
NASA NTRS2001

POLAR/CEPPAD Data Analysis

This a report on the Comprehensive Energetic Particle Pitch Angle Distribution (CEPPAD) experiment of POLAR. Dr. Baker has been active in the design and calibration of the CEPPAD sensors and is now heavily involved in the analysis and interpretation of the data. Baker and his team have developed analysis and data display software and continue to support all aspects of the CEPPAD program.

Baker, D. N.↗
NASA NTRS1974

Analysis of ATS-5 data

Data from the particle detectors on ATS-5 in synchronous orbit and from the meridian line of magnetometers at a ground station are correlated for periods of well defined substorm activity. Specific substorm events are presented whose region of maximum perturbation can be accurately identified using current systems modelling techniques. It was found that the impulsive particle response at ATS-5 is correlated with changes in the auroral electrojet structure during the development of the substorm expansive phase. The response of the particle detectors appears to differ from event to event depending on the geometry of the disturbed region of the magnetosphere. It is concluded that the substorm disturbance typically begins at low latitude and propagates poleward in impulsive steps and that energetic electron enhancements are observed at ATS-5 when the poleward border of the electrojet intensifies in the latitude range of the ATS-5 field line.

Sharp, R. D.↗
DOE OSTI2022

DOE Advanced Gas Reactor Fuel Development and Qualification Program Overview

AGR-3/4 post-irradiation examination and data analysis AGR-5/6/7 PIE and safety testing Supplemental fuel microanalysis and method development Fuel oxidation testing Air/moisture Ingress Experiment (AMIX) system development (deployed in FY23) Single particle testing in FITT Data management and analysis Fuel performance modeling

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1989

Wave propagation effects of broadband electrostatic noise in the magnetotail

An analysis of the wave and particle data from ISEE 1 for 1978 yielded several examples of crossings between the lobe and the plasma sheet boundary layer (PSBL) which exhibited the signatures predicted by the theoretical analysis of the generation of broadband electrostatic noise (BEN) by ion beam instabilities. These signatures are a gradual rise in the upper frequency of BEN as the spacecraft approaches the plasma boundary layer, and a very rapid rise in the upper frequency near the crossing into the PSBL from the lobe. Several examples of crossings are presented that exhibit both signatures, as well as a case of crossings in which the gradual frequency rise signature is absent but the rapid rise is present. This case exhibits a BEN in the range expected for the low-frequency ion-ion two-stream and the high-frequency Buneman instability.

Grabbe, Crockett↗
DOE OSTI2024

Simultaneous Unbinned Differential Cross-Section Measurement of Twenty-Four Z+jets Kinematic Observables with the ATLAS Detector

Z boson events at the Large Hadron Collider can be selected with high purity and are sensitive to a diverse range of QCD phenomena. As a result, these events are often used to probe the nature of the strong force, improve Monte Carlo event generators, and search for deviations from standard model predictions. All previous measurements of Z boson production characterize the event properties using a small number of observables and present the results as differential cross sections in predetermined bins. In this analysis, a machine learning method called omnifold is used to produce a simultaneous measurement of twenty-four Z +jets observables using 139 fb -1 of proton-proton collisions at √s =13 TeV collected with the ATLAS detector. Unlike any previous fiducial differential cross-section measurement, this result is presented unbinned as a dataset of particle-level events, allowing for flexible reuse in a variety of contexts and for new observables to be constructed from the twenty-four measured observables.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1991

The composition and plasma signature of a large dust impact on the Giotto spacecraft

At about 14,800 km from the Comet Halley nucleus, on the inbound leg, at least six of the sensors onboard the Giotto spacecraft observed an unusual, brief (about 30 to 500 ms) event: the ion-mass spectrometer data show a brief flow of energetic (up to several hundred electron volts) plasma consisting of protons, water group, and heavier ions. The Johnstone plasma analyzer data show a short burst of plasma, while the dust impact detector system data show an impact event in four of its detectors. The magnetometer signature of the event shows two brief dips in the field. The sudden change in the spacecraft attitude and spin rate observed by the camera at that same time has been interpreted as the result of a large (5 mg or more) dust-particle impact on the front bumper shield of the spacecraft. In addition, at about the same time the spacecraft star-tracker suffered damage. The report combines direct measurements of the composition and dynamics of a dust-impact plasma cloud, the dust particle mass, and the location of the impact on the spacecraft. Analysis of the data indicate that the impacting particle was water or ice-bearing, possibly loosely compared, and was composed of one or more of: carbon, nitrogen, and silicon.

Goldstein, R.↗
NASA NTRS2013

RUSHMAPS: Real-Time Uploadable Spherical Harmonic Moment Analysis for Particle Spectrometers

RUSHMAPS is a new onboard data reduction scheme that gives real-time access to key science parameters (e.g. moments) of a class of heliophysics science and/or solar system exploration investigation that includes plasma particle spectrometers (PPS), but requires moments reporting (density, bulk-velocity, temperature, pressure, etc.) of higher-level quality, and tolerates a lowpass (variable quality) spectral representation of the corresponding particle velocity distributions, such that telemetry use is minimized. The proposed methodology trades access to the full-resolution velocity distribution data, saving on telemetry, for real-time access to both the moments and an adjustable-quality (increasing quality increases volume) spectral representation of distribution functions. Traditional onboard data storage and downlink bandwidth constraints severely limit PPS system functionality and drive cost, which, as a consequence, drives a limited data collection and lower angular energy and time resolution. This prototypical system exploit, using high-performance processing technology at GSFC (Goddard Space Flight Center), uses a SpaceCube and/or Maestro-type platform for processing. These processing platforms are currently being used on the International Space Station as a technology demonstration, and work is currently ongoing in a new onboard computation system for the Earth Science missions, but they have never been implemented in heliospheric science or solar system exploration missions. Preliminary analysis confirms that the targeted processor platforms possess the processing resources required for realtime application of these algorithms to the spectrometer data. SpaceCube platforms demonstrate that the target architecture possesses the sort of compact, low-mass/power, radiation-tolerant characteristics needed for flight. These high-performing hybrid systems embed unprecedented amounts of onboard processing power in the CPU (central processing unit), FPGAs (field programmable gate arrays), and DSP (digital signal processing) elements. The fundamental computational algorithm de constructs 3D velocity distributions in terms of spherical harmonic spectral coefficients (which are analogous to a Fourier sine-cosine decomposition), but uses instead spherical harmonics Legendre polynomial orthogonal functions as a basis for the expansion, portraying each 2D angular distribution at every energy or, geometrically, spherical speed-shell swept by the particle spectrometer. Optionally, these spherical harmonic spectral coefficients may be telemetered to the ground. These will provide a smoothed description of the velocity distribution function whose quality will depend on the number of coefficients determined. Successfully implemented on the GSFC-developed processor, the capability to integrate the proposed methodology with both heritage and anticipated future plasma particle spectrometer designs is demonstrated (with sufficiently detailed design analysis to advance TRL) to show specific science relevancy with future HSD (Heliophysics Science Division) solar-interplanetary, planetary missions, sounding rockets and/or CubeSat missions.

Figueroa-Vinas, Adolfo↗
NASA NTRS1973

Analysis and synthesis of coronal and interplanetary energetic particle, plasma, and magnetic field observations over three solar rotations.

In a previous paper (Krimigis et al., 1971), simultaneous observations in 1967 of solar particle events at low (less than 1 MeV) energies were presented. In the present paper, the full complement of simultaneous plasma, magnetic field, and energetic particle data is combined, and a complete analysis is made of all the events discussed in the original paper. The essential concept of 'collimated convection' is introduced, whereby the bulk velocity along the field lines of low-energy solar particles is independent of solar local plasma velocity, and the particles are strongly collimated along the field line with no transverse velocity component other than that of the field line itself. Collimated convection effects are shown to exist in small-scale convection and large-scale evolution of particle fluxes; the particle fluxes are, in turn, used to delineate the small-scale and large-scale evolution of the interplanetary magnetic field. Use of collimated convection is made in demonstrating a technique whereby energetic particle intensity profiles in the interplanetary medium can be related to equatorial high coronal magnetic field structures, by using the instantaneous solar wind velocity. This technique is applied in mapping particle intensities from Mariner 5 onto H alpha synoptic charts of chromospheric magnetic field structures for Carrington rotations 1523 to 1525.

Roelof, E. C.↗
NASA NTRS1990

Particle displacement tracking for PIV

A new Particle Imaging Velocimetry (PIV) data acquisition and analysis system, which is an order of magnitude faster than any previously proposed system has been constructed and tested. The new Particle Displacement Tracing (PDT) system is an all electronic technique employing a video camera and a large memory buffer frame-grabber board. Using a simple encoding scheme, a time sequence of single exposure images are time coded into a single image and then processed to track particle displacements and determine velocity vectors. Application of the PDT technique to a counter-rotating vortex flow produced over 1100 velocity vectors in 110 seconds when processed on an 80386 PC.

Wernet, Mark P.↗
NASA NTRS1977

Evaluation of Jupiter longitudes in System III/1965/

Commission 40 of the International Astronomical Union has adopted a new longitude system for Jupiter, labelled System III(1965), to replace the provisional System III(1957.0). The specification of the prime meridian and epoch for the new system differs slightly from that recently published. Its rotation rate implies a period of 9 hr 55 min 29.711 (plus or minus 0.04) sec, consistent with recent determinations from decimetric and decametric data. For both the new and older systems, equations are provided which are useful in the evaluation of longitudes for the analysis of Jupiter radio, particle, and field data from earth and spacecraft observations.

Seidelmann, P. K.↗
DOE OSTI2022

Non-Gaussianities in collider energy flux

The microscopic dynamics of particle collisions is imprinted into the statistical properties of asymptotic energy flux, much like the dynamics of inflation is imprinted into the cosmic microwave background. This energy flux is characterized by correlation functions < E(n → 1 )…E(n → k ) > of energy flow operators E(n → ). There has been significant recent progress in studying energy flux, including the calculation of multi-point correlation functions and their direct measurement inside high-energy jets at the Large Hadron Collider (LHC). In this paper, we build on these advances by defining a notion of “celestial non-gaussianity” as a ratio of the three-point function to a product of two-point functions. We show that this celestial non-gaussianity is under perturbative control within jets at the LHC, allowing us to cleanly access the non-gaussian interactions of quarks and gluons. We find good agreement between perturbative calculations of the non-gaussianity and a charged-particle-based analysis using CMS Open Data, and we observe a strong non-gaussianity peaked in the “flattened triangle” regime. The ability to robustly study three-point correlations is a significant step in advancing our understanding of jet substructure at the LHC. We anticipate that the celestial non-gaussianity, and its generalizations, will play an important role in the development of higher-order parton showers simulations and in the hunt for ever more subtle signals of potential new physics within jets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Investigating the Impacts of Aqueous-Phase Processing on Organic Aerosol Chemical Climatology Using ARM and ASR Observations

This project improved understanding of how atmospheric aerosol particles form and evolve, with a focus on the role of water-driven (aqueous-phase) chemical reactions in the atmosphere. These processes occur in clouds, fog, and humid air and can significantly change the composition and properties of airborne particles, known as aerosols, which influence air quality and climate. By combining field measurements, laboratory experiments, and advanced analytical techniques, the project identified key chemical signatures that allow scientists to distinguish particles formed through aqueous processes from those formed in the gas phase. Observations from multiple environments, including wildfire smoke, urban regions, and cloud-influenced areas, show that aqueous chemistry is an important pathway for particle formation and aging. The project also developed new measurement approaches using uncrewed aerial systems (UAS) to capture how aerosol composition varies with altitude, providing critical insights into how particles interact with clouds. In addition, new data analysis frameworks were created to better interpret long-term aerosol measurements and improve characterization of particle sources and transformations. These results have been integrated into a global database of aerosol measurements and used to support atmospheric modeling efforts. Overall, the project provides important tools and knowledge to improve predictions of how aerosols affect climate and air quality, particularly through their interactions with radiation and clouds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2003

Toroidal wave frequency at L=6-10: AMPTE/CCE Observations and Comparison with Theoretical Model

Magnetospheric standing Alfven waves are guided along the ambient magnetic field and their frequency depends on the mass density of the plasma distributed along the field lines. These properties allow us to use Alfen waves to map time-dependent phenomena between space and ground and to estimate the mass density. In this paper we present a statistical study of the spatial variation of the fundamental frequency f(sub T1) of toroidal-mode standing Alfen waves in the L range from 6 to 10, where L indicates the maximum geocentric distance on the field line. The data used for this analysis are energetic particle flux anisotropy (proxy of transverse electric field) and magnetic field measurements from the Active Magnetospheric Particle Tracer Explorers Charge Composition Explorer (CCE) spacecraft. Using CCE data covering 4 years we obtained approximately 5000 20-min intervals containing a clear signature of toroidal waves. The median f(sub T1), is 6-10 mHz at L=7 and decreases to 4-8 mHz at L = . The frequency tends to be lower at noon than at midnight. The observed frequencies are compared with numerically derived frequencies using an empirical mass density model and a magnetic field model. We found a good agreement for 12-24 MLT but a large discrepancy near MLT= 3. This may indicate that the flux tubes at this local time are more heavily loaded than specified in the Gallagher et al. model.

Takahashi, Kazue↗
DOE OSTI2021

Novel usage of deep learning and high-performance computing in long-baseline neutrino oscillation experiments

Mención Internacional en el título de doctorDeep-learning methods are playing a crucial role in numerous scientific and industrialapplications. Over the past two decades, these techniques have helped in the collection,reconstruction, and analysis of large data samples in particle physics experiments. Themain topic of this PhD research is the study of deep-learning techniques in long-baselineneutrino oscillation experiments. Neutrinos are mysterious light elementary particles,and their investigation is essential to shed light on some of the remaining open questionsin physics. The work presented here describes an algorithm based on a convolutionalneural network developed to provide highly accurate and efficient selections of electronneutrino and muon neutrino interactions in the Deep Underground Neutrino Experiment(DUNE). With this algorithm, the electron neutrino (antineutrino) selection efficiencypeaks at 90% (94%) and exceeds 85% (90%) for reconstructed neutrino energies between2-5 GeV. The selection efficiency for muon neutrino (antineutrino) interactions is foundto have a maximum of 96% (97%) and exceeds 90% (95%) efficiency for reconstructedneutrino energies above 2 GeV. When considering all electron neutrino and antineutrinointeractions as signal (both those appearing from oscillations and those intrinsic tothe beam), a selection purity of 90% is achieved. These event selections are criticalto maximise the sensitivity of the experiment to CP-violating effects, key to furtherunderstand the matter-antimatter asymmetry of the Universe.In high-energy physics experiments, deep learning has also been explored for producingfast simulations and physically-motivated manipulations of simulated images. Some ofthose simulations, such as the light production and detection, are very computationallyexpensive and require novel methods to produce the necessary samples while controllingthe varied underlying physics model parameters. To do so, we invented the model-assistedgenerative adversarial network (MAGAN), first validated on simple generic case studiesand then successfully applied to the DUNE photon-detector simulation.Moreover, we also developed graph neural networks for 3D-voxel classification ofambiguities and optical crosstalk for a different particle physics experiment, most preciselyfor the proposed SuperFGD. This novel 3D-granular plastic-scintillator neutrino detectorwill be used to upgrade the near detector of the T2K neutrino oscillation experiment, and our method reports efficiencies and purities of 94-96% per event in the classificationof particle track voxels.Due to the growth and complexity of deep neural networks, researchers have beeninvestigating techniques to train those networks in a more computationally-efficient way.Many efforts have been made by the community to optimise deep-learning models byparallelising or distributing their training computation across multiple devices. In thisthesis, we study an approach based on data locality for those neural networks that cannotbenefit from scaling their computation due to a significant bottleneck in the data I/O.The research also includes a detailed study on the performance of deep neural networkson hardware accelerator boards.Los métodos de aprendizaje profundo son cada vez más utilizados en numerosas aplicacionescientíficas e industriales hoy en día. Durante las dos últimas décadas, estastécnicas se han empleado en la recolección, reconstrucción y análisis de la gran cantidadde datos generados por experimentos de física de partículas. El tema principal de estatesis doctoral es el uso de estos modelos de aprendizaje profundo en experimentos defísica de neutrinos, en concreto en los experimentos de larga distancia DUNE y T2K. Losneutrinos, partículas fundamentales neutras, de las más ligeras del Universo, pueden serclave para explicar algunas de las cuestiones todavía sin resolver en física fundamental.Entre las diferentes contribuciones que esta tesis ha hecho a su estudio, cabe destacar eldesarrollo de un algoritmo basado en una red de neuronas convolucional para seleccionarcon gran eficiencia y precisión las interacciones de neutrinos electrónicos y muónicos enel Deep Underground Neutrino Experiment (DUNE). La eficiencia de selección obtenidapara neutrinos (antineutrinos) electrónicos alcanza un máximo del 90% (94%) y supera el85% (90%) para neutrinos con energías reconstruidas en el rango 2-5 GeV. La selección deneutrinos (antineutrinos) muónicos tiene una eficiencia máxima del 96% (97%) y excedeel 90% (95%) para neutrinos con energías reconstruidas de más de 2 GeV. Considerandocomo señal todas las interacciones de neutrinos y antineutrinos electrónicos (procedentestanto de oscilaciones como intrínsecos en el haz inicial), se logra una pureza en la seleccióndel 90%. Dichas selecciones de eventos son fundamentales para maximizar la sensibilidaddel experimento a los efectos de violació...

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Classification Algorithm for Dark Matter Search using Skipper-CCD

In this project, I used ROOT framework with C++ for data analysis and Geant4 for simulating different particles’ interaction with the detector to study the characteristic of their tracks. I prepared the tagged dataset for machine learning training both the real experiment data taken in MINOS and simulation data from Geant4.

Chen, Meng-Wei↗
DOE OSTI2024

Imprinted Micelle Integration into a Commercial Platform (Progress Report)

PNNL has successfully integrated a commercial aerosol detector and the imprinted micelle technology. The integrated systems have been shown to have a limit of detection between 33-47 particles with several options for data analysis presented that vary on computational requirements. It is possible to integrate these systems and receive response data on the second time scale. While more work is needed, these technologies are compatible, which opens up a large field of air sampling looking for specific contaminates.

36 MATERIALS SCIENCE↗