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Basque, V.

Publications and source records attributed to Basque, V..

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Measurement of ambient radon progeny decay rates and energy spectra in liquid argon using the MicroBooNE detector

We report measurements of radon progeny in liquid argon within the MicroBooNE time projection chamber (LArTPC). The presence of specific radon daughters in MicroBooNE’s 85 metric tons of active liquid argon bulk is probed with newly developed charge-based low-energy reconstruction tools and analysis techniques to detect correlated Bi 214 − Po 214 radioactive decays. Special datasets taken during periods of active radon doping enable new demonstrations of the calorimetric capabilities of single-phase neutrino LArTPCs for β and α particles with electron-equivalent energies ranging from 0.1 to 3.0 MeV. By applying Bi 214 − Po 214 detection algorithms to data recorded over a 46-day period, no statistically significant presence of radioactive Bi 214 is detected, and a limit on the activity is placed at < 0.35 mBq / kg at the 95% confidence level. This bulk Bi 214 radiopurity limit—the first ever reported for a liquid argon detector incorporating liquid-phase purification—is then further discussed in relation to the targeted upper limit of 1 mBq / kg on bulk Rn 222 activity for the DUNE neutrino detector. Published by the American Physical Society 2024

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Search for Heavy Neutral Leptons in Electron-Positron and Neutral-Pion Final States with the MicroBooNE Detector

We present the first search for heavy neutral leptons (HNLs) decaying into ν e + e − or ν π 0 final states in a liquid-argon time projection chamber using data collected with the MicroBooNE detector. The data were recorded synchronously with the NuMI neutrino beam from Fermilab’s main injector corresponding to a total exposure of 7.01 × 10 20 protons on target. We set upper limits at the 90% confidence level on the mixing parameter | U μ 4 | 2 in the mass ranges 10 ≤ m HNL ≤ 150 MeV for the ν e + e − channel and 150 ≤ m HNL ≤ 245 MeV for the ν π 0 channel, assuming | U e 4 | 2 = | U τ 4 | 2 = 0 . These limits represent the most stringent constraints in the mass range 35 < m HNL < 175 MeV and the first constraints from a direct search for ν π 0 decays. Published by the American Physical Society 2024

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Impact of cross-section uncertainties on supernova neutrino spectral parameter fitting in the Deep Underground Neutrino Experiment

A primary goal of the upcoming Deep Underground Neutrino Experiment (DUNE) is to measure the 𝒪⁡(10) MeV neutrinos produced by a Galactic core-collapse supernova if one should occur during the lifetime of the experiment. The liquid-argon-based detectors planned for DUNE are expected to be uniquely sensitive to the 𝜈 𝑒 component of the supernova flux, enabling a wide variety of physics and astrophysics measurements. A key requirement for a correct interpretation of these measurements is a good understanding of the energy-dependent total cross section 𝜎⁡(𝐸 𝜈 ) for charged-current 𝜈 𝑒 absorption on argon. In the context of a simulated extraction of supernova 𝜈 𝑒 spectral parameters from a toy analysis, we investigate the impact of 𝜎⁡(𝐸 𝜈 ) modeling uncertainties on DUNE’s supernova neutrino physics sensitivity for the first time. We find that the currently large theoretical uncertainties on 𝜎⁡(𝐸 𝜈 ) must be substantially reduced before the 𝜈𝑒 flux parameters can be extracted reliably; in the absence of external constraints, a measurement of the integrated neutrino luminosity with less than 10% bias with DUNE requires 𝜎⁡(𝐸 𝜈 ) to be known to about 5%. The neutrino spectral shape parameters can be known to better than 10% for a 20% uncertainty on the cross-section scale, although they will be sensitive to uncertainties on the shape of 𝜎⁡(𝐸 𝜈 ). A direct measurement of low-energy 𝜈𝑒-argon scattering would be invaluable for improving the theoretical precision to the needed level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Identification and reconstruction of low-energy electrons in the ProtoDUNE-SP detector

Measurements of electrons from 𝜈𝑒 interactions are crucial for the Deep Underground Neutrino Experiment (DUNE) neutrino oscillation program, as well as searches for physics beyond the standard model, supernova neutrino detection, and solar neutrino measurements. This article describes the selection and reconstruction of low-energy (Michel) electrons in the ProtoDUNE-SP detector. ProtoDUNE-SP is one of the prototypes for the DUNE far detector, built and operated at CERN as a charged particle test beam experiment. A sample of low-energy electrons produced by the decay of cosmic muons is selected with a purity of 95%. This sample is used to calibrate the low-energy electron energy scale with two techniques. An electron energy calibration based on a cosmic ray muon sample uses calibration constants derived from measured and simulated cosmic ray muon events. Another calibration technique makes use of the theoretically well-understood Michel electron energy spectrum to convert reconstructed charge to electron energy. In addition, the effects of detector response to low-energy electron energy scale and its resolution including readout electronics threshold effects are quantified. Finally, the relation between the theoretical and reconstructed low-energy electron energy spectra is derived, and the energy resolution is characterized. The low-energy electron selection presented here accounts for about 75% of the total electron deposited energy. After the addition of lost energy using a Monte Carlo simulation, the energy resolution improves from about 40% to 25% at 50 MeV. These results are used to validate the expected capabilities of the DUNE far detector to reconstruct low-energy electrons.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Observation of radon mitigation in MicroBooNE by a liquid argon filtration system

We report the MicroBooNE liquid argon time projection chamber (LArTPC) maintains a high level of liquid argon purity through the use of a filtration system that removes electronegative contaminants in continuously-circulated liquid, recondensed boil off, and externally supplied argon gas. We use the MicroBooNE LArTPC to reconstruct MeV-scale radiological decays. Using this technique we measure the liquid argon filtration system's efficacy at removing radon. This is studied by placing a 500 kBq 222 Rn source upstream of the filters and searching for a time-dependent increase in the number of radiological decays in the LArTPC. In the context of two models for radon mitigation via a liquid argon filtration system, a slowing mechanism and a trapping mechanism, MicroBooNE data supports a radon reduction factor of greater than 97% or 99.999%, respectively. Furthermore, a radiological survey of the filters found that the copper-based filter material was the primary medium that removed the 222 Rn. This is the first observation of radon mitigation in liquid argon with a large-scale copper-based filter and could offer a radon mitigation solution for future large LArTPCs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Cosmic ray muon clustering for the MicroBooNE liquid argon time projection chamber using sMask-RCNN

In this article, we describe a modified implementation of Mask Region-based Convolutional Neural Networks (Mask-RCNN) for cosmic ray muon clustering in a liquid argon TPC and applied to MicroBooNE neutrino data. Our implementation of this network, called sMask-RCNN, uses sparse submanifold convolutions to increase processing speed on sparse datasets, and is compared to the original dense version in several metrics. The networks are trained to use wire readout images from the MicroBooNE liquid argon time projection chamber as input and produce individually labeled particle interactions within the image. These outputs are identified as either cosmic ray muon or electron neutrino interactions. We find that sMask-RCNN has an average pixel clustering efficiency of 85.9% compared to the dense network's average pixel clustering efficiency of 89.1%. We demonstrate the ability of sMask-RCNN used in conjunction with MicroBooNE's state-of-the-art Wire-Cell cosmic tagger to veto events containing only cosmic ray muons. The addition of sMask-RCNN to the Wire-Cell cosmic tagger removes 70% of the remaining cosmic ray muon background events at the same electron neutrino event signal efficiency. Furthermore, this event veto can provide 99.7% rejection of cosmic ray-only background events while maintaining an electron neutrino event-level signal efficiency of 80.1%. In addition to cosmic ray muon identification, sMask-RCNN could be used to extract features and identify different particle interaction types in other 3D-tracking detectors.

47 OTHER INSTRUMENTATION↗