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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 55 records · Page 3

becquerel (bq) v0.7.0

Becquerel is a Python package for analyzing nuclear spectroscopic measurements. The core functionalities are reading and writing different spectrum file types, fitting spectral features, rebinning spectrum counts to different bin edges, performing detector calibrations and interpreting measurement results. It also includes tools for visualizing radiation spectra and fits of different spectral features, as well as convenient access to tabulated nuclear data both from remote servers and local caches. It relies heavily on the standard scientific Python stack of numpy, scipy, matplotlib, pandas, and numba. It is intended to be general-purpose enough that it can be useful to anyone from an undergraduate taking a laboratory course to the advanced researcher.

Bandstra, Mark [Lawrence Berkeley National Laborat↗

Constraints on Neutrino Oscillation Parameters from Neutrinos and Antineutrinos with Machine Learning

NOvA is a two detector, long baseline neutrino oscillation experiment measuring the oscillations of muon neutrinos from the \numi neutrino beam over a baseline of \SI{810}{km}. The experiment uses four oscillation channels, $\numu \rightarrow \numu$, $\numubar \rightarrow \numubar$, $\numu \rightarrow \nue$, and $\numubar \rightarrow \nuebar$, with a peak neutrino energy of \SI{1.8}{GeV}. This dissertation describes the analysis of these channels using a dataset of $13.6\times10^{20}$ protons on target neutrino beam mode and $12.5\times10^{20}$ protons on target antineutrino beam mode. The analysis makes use of improvements in the treatment of systematic uncertainties and machine learning techniques to reconstruct neutrino interactions. A technique for decorrelating systematic errors using principle component analysis was utilized to reduce and optimize neutrino cross section and beam related uncertainties. The improved machine learning algorithms make use of convolutional ne ural net works for neutrino event classification, particle classification, and instance segmentation. The selection of neutrino signal events utilizing the neutrino event classifier shows an efficiency of 63\% for the selection of electron neutrinos in neutrino beam mode and 75\% for electron antineutrinos in antineutrino beam mode. Using this algorithm, 82 appearing electron neutrino candidates and 33 appearing electron antineutrino candidates were observed with expected backgrounds of 26.8 and 14.0 respectively. In addition, 211 surviving muon neutrino candidates and 105 muon antineutrino candidates were identified with a purity of more than 96\% using the same neutrino event classifier. Fitting these data to the three flavor neutrino oscillation model, using constraints on \thetaonetwo, \thetaonethree, and \dmsqonetwo from solar and reactor neutrino experiments, the oscillation parameters are measured to be $\sintwothree = 0.57^{+0.04}_{-0.03}$, $\dmsqthreetwo = \SI[parse-numbers= false]{+ 2.41\pm0.07 \times 10^{-3}}{eV^2}$, and $\dcp=0.82^{+0.27}_{-0.87}\pi$ with a preference for the normal neutrino mass hierarchy. Leading systematic uncertainties for these measurements come from detector calibration and neutrino interaction models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Reaction Rate Distribution Measurements in ZPPR-15

Small metal foils were irradiated in ZPPR-15 to measure distributions for 239 Pu(n,f), 235 U(n,f), 238 U(n,f), 238 U(n,γ), 115 In(n,n’) and 115 In(n,γ) reaction rates in ZPPR-15. The measured data were reported as basic reaction rate distributions for individual foils, cell-averaged reaction rate distributions and spectral indices or reaction rate ratios. All of the measured data were analyzed and tabulated in such a manner that the data can be readily compared with computed values. The published uncertainties for ZPPR-15 the reaction rate measurements include the statistical uncertainties in the measurements, reproducibility uncertainty and small uncertainties related to corrections for items such as foil compositions and post-irradiation decay between reactor shutdown and foil measurement. There are additional uncertainty components related to detector calibration that are not included in the published uncertainties. A full uncertainty analysis was performed for each foil measurement and for quantities derived from the basic foil measurements. The significant uncertainties were quantified, and a total uncertainty was derived for each measured value. The ZPPR-15 experimental records were used to create detailed as-built Monte Carlo models for the foil reaction rate measurements in ZPPR-15 loadings 123, 134 and 203 and for the fission chamber measurements of 237 Np and 242 Pu fission rates in ZPPR-15 loading 141. Because there were many foils distributed in the ZPPR-15 assembly and because an individual foil occupies a negligible volume in the ZPPR-15 assembly, direct Monte Carlo calculations of the measured foil reaction rates would require an impractical computational effort. The as-built Monte Carlo models and related files were prepared for conversion to deterministic models that can be calculated with realistic computational effort.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Early Career: Constraining the Electromagnetic Shower Energy Scale at LArTPC Neutrino Detectors Near and Far (Final Scientific/Technical Report)

This is the final scientific/technical report associated with the award "Early Career: Constraining the Electromagnetic Shower Energy Scale at LArTPC Neutrino Detectors Near and Far"; the primary research topics associated with the award are neutrino oscillation physics, reconstruction of neutrino interaction events using machine learning techniques, and detector calibration.

43 PARTICLE ACCELERATORS↗

SBND Shower Reconstruction with SPINE

The Short-Baseline Near Detector (SBND) is a liquid argon time projection chamber (LArTPC) neutrino detector in the Short-Baseline Neutrino (SBN) program at Fermilab. SBND is designed to investigate the Low-Energy Excess (LEE), an unexplained excess of electron-like events observed by previous short-baseline neutrino experiments that may point to physics beyond the Standard Model. In LArTPC detectors, precise shower reconstruction is essential for distinguishing electrons from photons, a key requirement for testing possible explanations of the LEE and improving $\nu_e$ event selection. In this poster, the reconstruction studies using the Scalable Particle Imaging with Neural Embeddings (SPINE), a machine learning based reconstruction framework for particle imaging detectors will be presented. SPINE combines sparse convolutional neural networks (CNN) and graph neural networks (GNN) to enable detailed reconstruction and characterization of neutrino interactions in LArTPC detectors. Shower calorimetry and kinematic reconstruction are performed in dedicated post-processing stages. Strong agreement between data and Monte Carlo simulation will be demonstrated, indicating high-precision detector calibration and reconstruction performance. The agreement between reconstructed and true electron shower energy will also be discussed, emphasizing the robustness of the shower reconstruction performance. These results demonstrate the unprecedented precision achievable with SPINE in SBND, highlighting their potential for future high-resolution neutrino measurements.

Fan, Castaly [Florida U.; Fermilab] (ORCID:0000000↗

Accelerated 133 Xe Quantification in Samples Containing Significant 133 mXe

The quantification of 133 Xe in the presence of its mother radionuclide 133 mXe requires the full quantification of both to perform the ingrowth correction for 133 Xe. Due to the nature of both of these radionuclides, the 133 mXe requires significantly more time to quantify by High Purity Germanium (HPGe) detectors due to lower production yields, lower gamma emission probabilities, and lower detection efficiencies. This work shows that 133 Xe and 133 mXe quantification can be accelerated by measuring the 133m:133 activity ratio for a large batch of material and applying this activity ratio to assays of lower activity subsamples of the same batch of material. Included in this report are derivations of the required decay correction equations, and experiments using actual samples to validate the performance of these equations. A detector calibration method is also shown that leverages this method as an alternative to existing calibration methods for 133 mXe quantification.

133mXe↗

A measurement of the Higgs boson mass in the diphoton decay channel in proton-proton collisions at $\sqrt{s}$ = 13 TeV

A measurement of the Higgs boson mass in the diphoton decay channel is performed using proton-proton collision data at a center-of-mass energy of 13 TeV. The data set recorded with the CMS detector between 2016 and 2018 is used, corresponding to an integrated luminosity of 138 fb$^{-1}$. A refined detector calibration and new analysis techniques are employed to improve the precision of the results compared to earlier measurements. The Higgs boson mass is measured to be $m_\mathrm{H}$ = 125.13 $\pm$ 0.15 GeV = 125.13 $\pm$ 0.10 (stat) $\pm$ 0.12 (syst) GeV. In addition, a combination with the mass measurement at center-of-mass energies of 7 and 8 TeV in the diphoton final state is performed resulting in $m_\mathrm{H}$ = 125.06 $\pm$ 0.14 GeV = 125.06 $\pm$ 0.09 (stat) $\pm$ 0.11 (syst) GeV.

FOS: Physical sciences↗

Measurement of the pion charge exchange differential cross section on Argon with the ProtoDUNE-SP detector

The Deep Underground Neutrino Experiment (DUNE) utilizes Liquid Argon Time Projection Chamber (LArTPC) technology in its pursuit of uncovering the origins of matter. As a crucial prototype for the DUNE far detector (FD) module, ProtoDUNE-SP at CERN Neutrino Platform Facility employs a hadron test beam with a momentum range of 0.3 to 7 GeV/c to study the detector response to particles that could be produced in the neutrino interactions at the DUNE FD. Furthermore, ProtoDUNE-SP is dedicated to testing event reconstruction and performing detector calibration under controlled conditions. Neutral pion reconstruction performance is an important benchmark of the calorimetric and tracking capability of LArTPC, and understanding neutral pion in LArTPC is crucial to characterize backgrounds to oscillation measurements and rare searches. To improve neutral pion reconstruction in LArTPC, a kinematic fitting algorithm is developed, achieving a 12% resolution in neutral pion energy in ProtoDUNE-SP. This enhancement enables the first measurements of the pion-argon charge exchange differential cross-section. By comparing these results with the current model, valuable constraints can be made to improve generator simulations in the future DUNE experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Searching for Sterile Neutrinos In the NOvA Experiment and Measurements of Hadronic Energy Response with NOvA Test Beam Data

The NOvA (NuMI Off-Axis electron neutrino Appearance) experiment is a long-baseline neutrino oscillation experiment composed of two functionally identical detectors: a 300-ton Near Detector and a 14-kton Far Detector, separated by 809 km and placed 14 mrad off the axis of the NuMI neutrino beam created at Fermilab. This configuration enables NOvA’s rich neutrino physics program, which includes measuring neutrino mixing parameters, determining the neutrino mass hierarchy, probing CP violation in the leptonic sector, studying neutrino cross sections, searching for sterile neutrinos, and more.\\ In this thesis I will present two independent analyses developed within the NOvA experiment. The first is a search for light sterile neutrino oscillations in the 3+1 framework using $\nu_\mu$-CC and NC samples from the NOvA Near and Far Detectors. Light sterile neutrinos are hypothetical neutral leptons that do not participate in the weak interactions but can mix with the three known active neutrinos: $\nu_e$, $\nu_\mu$, and $\nu_\tau$. Anomalous results, such as $\nu_e$/$\bar{\nu}e$ appearance in a $\nu_\mu$ ($\bar{\nu}_\mu$) beam observed by the MiniBooNE and LSND experiments, can be explained by the existence of sterile neutrinos. Thus, proving the existence of this type of neutrino is essential. The latest results of these searches in the NOvA experiment, along with contributions to this effort, will be presented.\\ The second is the first measurement of the pion energy response using data from the NOvA Test Beam experiment. The NOvA Test Beam experiment, deployed at Fermilab, uses a scaled-down 30-ton NOvA detector to analyze tagged beamline particles. The beamline can select and identify electrons, muons, pions, kaons, and protons with momenta ranging from 0.4 to 1.4 GeV/c. Pions are an important component of the hadronic system in neutrino interactions, and understanding how the detector responds to these particles is crucial for the validation of the simulation and the reduction of detector calibration uncertainties, which remain one of the largest systematic uncertainties in NOvA analyses.

Dueñas Tonguino, David Francisco [Cincinnati U.] (↗

Study of Nuclear Structure Functions at Jefferson Lab

This thesis presents a study of nuclear modification of quark distributions (the EMC effect) using inclusive electron-scattering data from Jefferson Lab Hall C, with emphasis on experiment E12-10-008 (XEM2). The analysis spans nuclei from light to heavy targets and combines measurements at multiple spectrometer settings to constrain EMC ratios over a broad range in Bjorken-x and Q2. A complete analysis framework was developed to extract charge-normalized and efficiency-corrected yields, including detector calibrations, beam-current calibration, density-loss corrections for cryogenic targets, background subtraction, radiative and Coulomb corrections, and systematic studies. Instrumental cross-checks, including HMS–SHMS comparisons and reconstruction studies, show that residual spectrometer differences are predominantly multiplicative in the kinematic region relevant to the EMC analysis. The extracted EMC ratios are broadly consistent with previous measurements while extending coverage across many nuclei. The EMC slope increases from light to heavy nuclei and shows signs of saturation at large A. After accounting for the dominant A dependence, the results are consistent with no isospin dependence, but also consistent with the predicted modification from the isovector model.

Sharda, Abhyuday [Univ. of Tennessee, Knoxville, T↗

Optical calibration of the SNO+ detector in the water phase with deployed sources

SNO+ is a large-scale liquid scintillator experiment with the primary goal of searching for neutrinoless double beta decay, and is located approximately 2 km underground in SNOLAB, Sudbury, Canada. The detector acquired data for two years as a pure water Cherenkov detector, starting in May 2017. During this period, the optical properties of the detector were measured in situ using a deployed light diffusing sphere, with the goal of improving the detector model and the energy response systematic uncertainties. The measured parameters included the water attenuation coefficients, effective attenuation coefficients for the acrylic vessel, and the angular response of the photomultiplier tubes and their surrounding light concentrators, all across different wavelengths. Finally, the calibrated detector model was validated using a deployed tagged gamma source, which showed a 0.6% variation in energy scale across the primary target volume.

47 OTHER INSTRUMENTATION↗

Calibrating the DUNE LArTPC detectors for precision physics

The Deep Underground Neutrino Experiment (DUNE) is an international collaboration focused on studying neutrino oscillation over a long baseline (1300 km). DUNE will make use of a near detector and $\mathcal{O}$(GeV) neutrino beam originating at Fermilab in Batavia, IL, and a far detector operating 1.5 km underground at the Sanford Underground Research Facility in Lead, South Dakota. The near and far detectors will use the LArTPC (Liquid Argon Time Projection Chamber) technology to image neutrino interactions. In order to make precise physics measurements at DUNE, such as the amount of CP violation in the neutrino sector, it is essential to be able to accurately reconstruct particle energies and other kinematic quantities; this in turn necessitates an extensive calibration program for DUNE s LArTPC detectors. In this presentation, we describe the requirements for calibrating the DUNE detectors, emphasizing the challenges of massive multi-kiloton LArTPC detectors which are to operate for multiple years deep underground. A preliminary DUNE detector calibration program, including use of both dedicated calibration hardware and cosmogenic/beam-induced calibration sources, is presented. First results on detector calibration at the ProtoDUNE-SP prototype detector located at CERN, and associated impact on calibrations at the DUNE far detector, are also emphasized.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Electron and photon energy calibration with the ATLAS detector using LHC Run 2 data

This paper presents the electron and photon energy calibration obtained with the ATLAS detector using 140 fb -1 of LHC proton-proton collision data recorded at $\sqrt{s}$ = 13 TeV between 2015 and 2018. Methods for the measurement of electron and photon energies are outlined, along with the current knowledge of the passive material in front of the ATLAS electromagnetic calorimeter. The energy calibration steps are discussed in detail, with emphasis on the improvements introduced in this paper. The absolute energy scale is set using a large sample of Z-boson decays into electron-positron pairs, and its residual dependence on the electron energy is used for the first time to further constrain systematic uncertainties. The achieved calibration uncertainties are typically 0.05% for electrons from resonant Z-boson decays, 0.4% at E T ~ 10 GeV, and 0.3% at E T ~ 1 TeV; for photons at E T ~ 60 GeV, they are 0.2% on average. This is more than twice as precise as the previous calibration. The new energy calibration is validated using J/ψ → ee and radiative Z-boson decays.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Deep Learning for Pion Identification and Energy Calibration with the ATLAS Detector

Separating charged and neutral pions as well as calibrating the pion energy response is a core component of reconstruction in the ATLAS calorimeter. This note presents an investigation of deep learning techniques for these tasks, representing the signal in the ATLAS calorimeter layers as pixelated images. Deep learning approaches outperform the classification applied in the baseline local hadronic calibration and are able to improve the energy resolution for a wide range in particle momenta, especially for low energy pions. This work demonstrates the potential of deep-learning-based low-level hadronic calibrations to significantly improve the quality of particle reconstruction in the ATLAS calorimeter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗