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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Energy Reconstruction and Calibration of the MicroBooNE LArTPC

The Liquid Argon Time Projection Chamber (LArTPC) is increasingly becoming the chosen technology for current and future precision neutrino oscillation experiments due to its superior capability in particle tracking and energy calorimetry. In LArTPCs, calorimetric information is critical for particle identification, which is the foundation for the neutrino cross-section and oscillation measurements as well as searches for beyond standard model physics. One of the primary challenges in employing LArTPC technology is characterizing its performance and quantifying the associated systematic uncertainties. MicroBooNE, the longest operating LArTPC to date, has performed numerous such measurements, including studies of detector physics and electromagnetic shower reconstruction. Here we present results on the operation and performance of the detector during its data taking, highlighting accomplishments toward calorimetric reconstruction, calibration, and detector physics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Air Exchange Rate Impact on Activity Equilibrium Factors and Inhalation Fractional Equilibrium Factors for Rn, Xe, Kr, Ar, Ne, and Their Progeny in Vapor Intrusion, Risk, and Dose Models

Exposure to the radioactive noble gasses, especially radon, is of high concern and poses a significant risk to humans in an indoor air environment as the second leading cause of lung cancer in the United States. To evaluate and minimize the risks posed by these gasses, it is important to understand their radiological and physical properties. The EPA’s Radon Vapor Intrusion Screening Level (RVISL) calculator calculates indoor air RVISLs based on target working levels (WLs), target excess lifetime cancer risk (ELCR), and annual dose limits for the actinon (Rn-219), thoron (Rn-220), and radon (Rn-222) decay series. The RVISLs are based on inhalation and submersion in gas cloud exposure routes for residential and commercial settings. The RVISLs are analogous to preliminary remediation goals (PRGs) and dose compliance concentrations (DCCs), where the isotope-specific values are in units of activity concentration (activity per unit volume). If the concentration of a parent isotope of radon or its progeny is found to exceed the RVISL, then further action to ensure cleanup of the contaminant may be necessary. In residential and commercial settings, the RVISLs will vary based on the air exchange rate present. The EPA’s Radionuclide PRG and DCC Calculators also assess the risk/dose from noble gases in the air due to household use of water like showering. In this study, a computational method in MATLAB was developed to determine the impact of the air exchange rate on the activity equilibrium factor (A eq ) and the inhalation fractional equilibrium factor (F eq ). Both factors are values that reflect the equilibrium concentrations of progeny to their parent in the air. These factors have a direct impact on the RVISL, PRG, and DCC calculations of WL, ELCR, and annual dose, respectively. This study builds on a previous report that only focused on actinon, thoron, and radon by revisiting the original A eq and F eq calculation methods, as well as including the values for the Rn-207, Rn-209, Rn-210, Rn-211, Rn-215, Rn-216, Rn-217, Rn-218, Rn-223, Ne-24, Ar-42, Ar-43, Ar-44, Kr-74, Kr-75, Kr-76, Kr-77, Kr-88, Kr-89, Xe-120, Xe-121, Xe-122, Xe-123, Xe-135m, and Xe-138 decay chains, which are not currently available in literature. The EPA’s RVISL calculator will be updated to include the new A eq and F eq values for the actinon, thoron, and radon decay chains, while the rest of the calculators will incorporate all the new A eq and F eq values as appropriate.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2023

The University of Virginia, Theoretical High Energy Physics (Final Technical Report)

We summarize research performed in the final reporting period of grant DE-SC0007984 for University of Virginia, Theoretical High Energy Physics. Progress was made on studying quantum mechanical effects in the showering of high energy particles inside a quark-gluon plasma, on the effects of extra dimensions on gravitational waves, and on expanding the use of what is known as the "worldline" formalism in quantum field theory.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Data analysis in the ICARUS (SBN FD) Cosmic Ray Tagging system

When a cosmic ray particle collides with the upper atmosphere, it creates a shower of particles that transverse down to the Earth’s surface. These cosmogenic particles provide a challenging background in neutrino experiments. The Short Baseline Neutrino (SBN) Program is composed of three Liquid Argon Time Projection Chambers (LArTPCs) that will help us understand the elusive neutrino. Together with a Cosmic Ray Tagger (CRT) system, the ICARUS detector serves as the Far Detector in the SBN Program. The CRT surrounds the detector medium and tags incoming particles allowing us to combat the high flux of comic rays we experience at ICARUS. In this poster, I will show some of the first data analyses done with the fully commissioned CRT system, including studies using CRT timing information and CRT hit reconstruction.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Muon Neutrino Reconstruction at ICARUS with Machine Learning

The ICARUS T600 LArTPC detector successfully ran for three years at the underground LNGS laboratories, providing a first sensitive search for LSND-like anomalous electron neutrino appearance in the CNGS beam. After a significant overhauling at CERN, the T600 detector has been placed in its experimental hall at Fermilab, fully commissioned, and the first events observed with full detector readout. Regular data-taking began in May 2021 with neutrinos from the Booster Neutrino Beam (BNB) and neutrinos six degrees off-axis from the Neutrinos at the Main Injector (NuMI). Modern developments in machine learning have allowed for the development of an end-to-end machine learning-based event reconstruction for ICARUS data. This reconstruction folds in 3D voxel-level feature extraction using sparse convolutional neural networks and particle clustering using graph neural networks to produce outputs suitable for physics analyses. This poster will summarize the performance of a high-purity and high-efficiency end-to-end machine learning-based selection of muon neutrinos from the BNB and highlight studies of electromagnetic shower reconstruction from a neutral pion selection.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Cosmic Background Rejection of the ICARUS experiment at Fermilab

The Short Baseline Neutrino program at Fermilab aims to explore significant regions of parameter space, applicable to sterile neutrinos at the eV mass scale, as suggested by existing experimental anomalies. To this purpose it exploits Liquid Argon Time Projection Chamber detectors located along the Booster Neutrino Beamline to measure both νe appearance and νµ disappearance: the Short Baseline Neutrino Detector and the ICARUS-T600 detector at 110 and 600 m from the neutrino source, respectively. The ICARUS T-600 Far Detector, located at shallow depth, is surrounded by a Cosmic Ray Tagger system to mitigate the cosmic ray background. On average ~ 11 muon tracks are expected to cross the detector during the ~ 1 ms drift time. The cosmic ray tagger is composed of plastic scintillator bars, ensuring near 4π coverage of the detector aiming at tagging cosmic muons and thus reject 𝛾s produced by muon interactions in the surrounding materials that can generate an electromagnetic showers mimicking a νe signal. The system allows one to disentangle cosmic rays from particles originated in a neutrino interaction inside the detector by measuring their position and crossing time. A synchronization of the cosmic ray tagger with the ICARUS photon detection system with a nanosecond accuracy allows one to reject cosmic particles recorded during the beam spill and thus select an enriched sample of neutrino triggered events ahead of the event reconstruction. An overview of the cosmic ray tagger system as well as its role in the neutrino events identification and cosmic background rejection will be presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Search for Electron Neutrinos in Multiple Topologies with the MicroBooNE Experiment

This note presents the status of the measurement of electron neutrinos from the Fermilab Booster Neutrino Beamline (BNB) with the MicroBooNE experiment. The analysis is aimed at investigating the nature of the low energy excess of electromagnetic activity observed by the MiniBooNE experiment. The $ν_e$ event selection relies on topological and calorimetric information to characterise particles produced in these interactions, leveraging the Pandora multi-algorithm reconstruction framework as well as custom particle identification and pattern recognition tools. Results presented in this note use 5.88 × 10 20 protons on target of data collected between 2015 and 2018. These include the performance of particle identification tools for $\mu/p$ and $e/\gamma$ separation, along with electromagnetic shower calibration with the largest sample of $\pi^0$ events measured on argon. Progress towards the completion of this analysis is shown through the measurement of high-energy charged-current $ν_e$ interactions and their kinematic distributions using both inclusive (1eX) and exclusive (1$e$0$p$0$\pi$ and 1$e$N$p$0$\pi$) channels. Measurements of charged-current $ν_µ$ interactions aimed at constraining flux and cross-section systematic uncertainties are also shown. We present the analysis’ preliminary sensitivity of an electron-like signal hypothesis to the MiniBooNE excess which includes flux, cross-section, and detector systematic uncertainties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Study of $\pi^0$ Events in MicroBooNE and Applications to the Deep Learning LEE Search

We present a selection of events containing $\pi^0$ particles in the MicroBooNE detector. These events are used to understand the important pi0 background in the deep learning (DL) based electron low energy excess (e-LEE) analysis. The selection uses a new shower reconstruction algorithm based on tools in the DL reconstruction chain. We present the efficiency and energy resolution of the selection. We also present the planned use of these events in energy calibration using the reconstructed $\pi^0$ mass.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Identifying Neutrino Final States and Energies in MicroBooNE with New Deep-Learning Based LArTPC Reconstruction Frameworks

MicroBooNE, a Liquid Argon Time Projection Chamber (LArTPC) located in the $\nu_{\mu}$-dominated Booster Neutrino Beam at Fermilab, has been studying $\nu_{e}$ charged-current (CC) interaction rates to shed light on the MiniBooNE low energy excess. The LArTPC technology employed by MicroBooNE provides the capability to image neutrino interactions with mm-scale precision. Computer vision and other machine learning techniques are promising tools for image processing that could boost efficiencies for selecting $\nu_{e}$-CC and other rare signals, reduce cosmic and beam-induced backgrounds, and improve the reconstruction of neutrino energies. The MicroBooNE experiment has been at the forefront of developing and testing such techniques for use in physics analyses. In this poster we overview deep-learning based reconstruction methods. We will showcase the use of a recurrent neural network to estimate neutrino energies and present a new reconstruction framework that uses convolutional neural networks to locate neutrino interaction vertices, tag pixels with track and shower labels, and perform particle identification on reconstructed clusters. We will present studies characterizing the performance of these new tools and demonstrate their effectiveness through their use in an inclusive $\nu_{e}$-CC event selection.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

First search for an anomalous excess of charged-current $\nu_e$ interactions without visible pions using the full MicroBooNE dataset

This public note presents an investigation of low-energy electron-neutrino events in the Fermilab Booster Neutrino Beam by the MicroBooNE experiment. This search is motivated by the excess of low energy electromagnetic events observed by the MiniBooNE experiment and, more broadly, by the landscape of neutrino anomalies observed at short baselines. This is the first measurement to use all of the data collected by the MicroBooNE experiment, corresponding to $1.1\times 10^{21}$ protons on target. Two exclusive samples of electron neutrinos without visible pions are used, one with visible protons and one without any visible protons. MicroBooNE data is compared to two empirical models of the MiniBooNE low energy excess, one obtained by enhancing the electron-neutrino content as a function of the neutrino energy, and one representing the excess for the first time as a function of the kinematics of shower energy and angle. This measurement excludes an electron-like interpretation of the MiniBooNE excess based on these models at $\geq 99\%$ confidence level in all kinematic variables.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Search for anomalous neutral current coherent-like single-photon production in MicroBooNE

This note describes progress towards the first experimental search for neutrino-induced neutral current coherent single-photon production (NC coherent 1γ). The search makes use of data from the MicroBooNE’s 85-tonne active mass liquid argon time projection chamber detector, situated in Fermilab’s Booster Neutrino Beam, with an average neutrino energy of $\langle$E ν $\rangle$ ~ 0.8 GeV. A selection targeted on candidate neutrino interactions with a single photon-like electromagnetic shower in the final state and no visible vertex activity was developed to search for this rare NC coherent 1γ process.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Progress Towards an Expanded Search for Neutral-Current Delta Radiative Decays in MicroBooNE

In this note, we present progress toward an expanded search for neutral current Delta radiative decays (NC $\Delta \rightarrow N\gamma$) in MicroBooNE. We present sensitivities for several tests of the MiniBooNE Low Energy Excess (LEE) under NC $\Delta \rightarrow N\gamma$ scaling hypotheses, with significantly enhanced sensitivity relative to previous tests. These selections can also be used for additional single photon searches in the future, including searches which target more specific hadronic final states and particular regions of shower kinematic phase space.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

ADRIANO2 Calorimeter Performance from 2022 Test Beams

A novel high-granularity dual-readout calorimetric technique was developed as part of the T1604 collaboration. The ADRIANO2 Calorimeter Prototype consists of a pair of optically isolated, small sized tiles made of scintillating plastic and lead glass. Čerenkov light from the lead glass are exploited to for high resolution timing measurements, while high granularity from scintillating plastic can be used to probe the spatial component of the particle shower. This setup works for excellent energy resolution and particle detection for REDTOP as it is crucial for a calorimeter to detect the decay products of eta/eta-prime mesons. Measurements were collected on ADRIANO2 between February to December 2022 to evaluate the detector performance at Fermilab’s Test Beam Facility. The key metrics extracted from my analysis are the detector’s efficiency for various tile configuration and light-yield which will then be used as parameters for an upgraded REDTOP monte-carlo simulation campaign. An in-depth analysis of ADRIANO2 performance are detailed in this presentation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

A New Track Trigger for Characterization of the Antiproton-Induced Background in the Mu2e Experiment

The Mu2e experiment at Fermilab will enable the search for the neutrinoless muon to electron conversion in the field of an Al nucleus, a charged lepton flavor violating process. If observed, there would be a clear indication of physics beyond the Standard Model. Mu2e aims to reach a single event sensitivity of $3 /times 10^{-17}$, improving from the previous limit by 4 orders of magnitude. This improvement relies on the development of trigger selection systems, designed to discard data from background-induced events by placing kinematic, topological cuts on a particle’s reconstructed track. One of the largest sources of background Mu2e faces is proton-antiproton annihilation. These annihilations produce a 2 GeV shower of particles, among which there could be an electron that mimics the conversion electron signal, with an expected number of 0.010 ± 0.010. The large uncertainty on this number is dominated by the systematic uncertainty associated with the theoretical production model. To better characterize this background, we have developed an antiproton trigger selection by taking advantage of the track multiplicity and topology of these events. We discuss the steps taken in this development and the first performance study of this trigger, evaluating the signal efficiency and background rate. This trigger is essential to enable a data-driven analysis targeting the reduction of the systematic uncertainty of the antiproton-induced background in the Mu2e experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Interpreting and Accelerating Transformers for Jet Tagging

Attention-based transformers are ubiquitous in machine learning applications from natural language processing to computer vision. In high energy physics, one central application is to classify collimated particle showers in colliders based on the particle of origin, known as jet tagging. In this work, we study the interpretatbility and prospects for acceleration of Particle Transformer (ParT), a state-of-the-art model, leverages particle-level attention to improve jet-tagging performance. We analyzing ParT's attention maps and particle-pair correlations in the eta-phi plane, revealing intriguing features, such as a binary attention pattern that identifies critical substructure in jets. These insights enhance our understanding of the model's internal workings and learning process and hint at ways to improve its efficiency. Along these lines, we also explore low-rank attention, attention alternatives, and dynamic quantization to accelerate transformers for jet tagging. With quantization, we achieve a 50% reduction in model size and a 10% increase in inference speed without compromising accuracy. These combined efforts enhance both the performance and the interpretability of transformers in high-energy physics, opening avenues for more efficient and physics-driven model designs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Quantum Random Walk Simulator Using Ultrafast Optical Switches

Quantum random walk processes have many intriguing applications in high energy physics including the simulation of parton shower evolution. We will present the design and initial results of a fiber loop time-bin quantum walk architecture using the hardware platform already in operation at the Fermilab Quantum Network in which the state of the photon is defined by its time-of-arrival. The fiber loop consists of an unbalanced Mach-Zehnder interferometer implemented using an ultrafast electro-optical switch. The input switch controls the photon path within the interferometer, while the output switch will direct the photon back into the interferometer or to single photon detectors to measure the probability distribution of arrival times. Depending on which path the photon takes each pass through the loop, its wave function will interfere on these optical switches similar to quantum interference on a beam splitter. This work is an important step towards utilizing real-world advantages of quantum information protocols to solve problems in high energy physics.

Cameron, Andrew [Fermilab]↗
DOE OSTI2025

Geant4 Event Biasing and Fast Simulation

Geant4 offers advanced event biasing techniques to significantly accelerate simulations involving rare events. Various biasing methods, such as leading particle selection, cross-section biasing, radioactive decay enhancement, and bremsstrahlung splitting, enable efficient event sampling, though they require careful handling. Additionally, Geant4 provides a Fast Simulation Interface, allowing the replacement of standard processes in specific region and for selected particles, enabling faster execution or external code integration. Applications of fast simulation include electromagnetic shower modeling in calorimeters, machine learning inference, and offloading tasks to specialized hardware like GPUs, making Geant4 a powerful tool for computationally demanding simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗