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Liquid argon is commonly used as a detector medium for neutrino physics and dark matter experiments in part due to its copious scintillation light production in response to its excitation and ionization by charged particle interactions. As argon scintillation appears in the vacuum ultraviolet (VUV) regime and is difficult to detect, wavelength-shifting materials are typically used to convert VUV light to visible wavelengths more easily detectable by conventional means. In this work, we examine the wavelength-shifting and optical properties of poly(ethylene naphthalate) (PEN), a recently proposed alternative to tetraphenyl butadiene (TPB), the most widely-used wavelength-shifter in argon-based experiments. In a custom cryostat system with well-demonstrated geometric and response stability, we use 128~nm argon scintillation light to examine various PEN-including reflective samples' light-producing capabilities, and study the stability of PEN when immersed in liquid argon. The best-performing PEN-including test reflector was found to produce 34% as much visible light as a TPB-including reference sample, with widely varying levels of light production between different PEN-including test reflectors. Plausible origins for these variations, including differences in optical properties and molecular orientation, are then identified using additional measurements. Unlike TPB-coated samples, PEN-coated samples did not produce long-timescale light collection increases associated with solvation or suspension of wavelength-shifting material in bulk liquid argon.

The liquid argon time projection chamber (LArTPC) detector technology has an excellent capability to measure properties of low-energy neutrinos produced by the sun and supernovae and to look for exotic physics at very low energies. In order to achieve those physics goals, it is crucial to identify and reconstruct signals in the waveforms recorded on each TPC wire. In this paper, we report on a novel algorithm based on a one-dimensional convolutional neural network (CNN) to look for the region-of-interest (ROI) in raw waveforms. We test this algorithm using data from the ArgoNeuT experiment in conjunction with an improved noise mitigation procedure and a more realistic data-driven noise model for simulated events. This deep-learning ROI finder shows promising performance in extracting small signals and gives an efficiency approximately twice that of the traditional algorithm in the low energy region of \\(\\sim\\)0.03-0.1 MeV. This method offers great potential to explore low-energy physics using LArTPCs.

We report the measurement of the final-state products of negative pion and muon nuclear capture at rest on argon by the LArIAT experiment at the Fermilab Test Beam Facility. We measure a population of isolated MeV-scale energy depositions, or blips, in 296 LArIAT events containing tracks from stopping low-momentum pions and muons. The average numbers of visible blips are measured to be 0.74 \\(\\pm\\) 0.19 and 1.86 \\(\\pm\\) 0.17 near muon and pion track endpoints, respectively. The 3.6\\(\\sigma\\) statistically significant difference in blip content between muons and pions provides the first demonstration of a new method of pion-muon discrimination in neutrino liquid argon time projection chamber experiments. LArIAT Monte Carlo simulations predict substantially higher average blip counts for negative muon (1.22 \\(\\pm\\) 0.08) and pion (2.34 \\(\\pm\\) 0.09) nuclear captures. We attribute this difference to Geant4's inaccurate simulation of the nuclear capture process.

We report the first electron neutrino cross section measurements on argon, based on data collected by the ArgoNeuT experiment running in the GeV-scale NuMI beamline at Fermilab. A flux-averaged \\(\\nu_e + \\overline{\\nu}_e\\) total and a lepton angle differential cross section are extracted using 13 \\(\\nu_e\\) and \\(\\overline{\\nu}_e\\) events identified with fully-automated selection and reconstruction. We employ electromagnetic-induced shower characterization and analysis tools developed to identify \\(\\nu_e/\\overline{\\nu}_e\\)-like events among complex interaction topologies present in ArgoNeuT data (\\(\\langle E_{\\bar{\\nu}_e} \\rangle = 4.3\\) GeV and \\(\\langle E_{\\nu_e} \\rangle = 10.5\\) GeV). The techniques are widely applicable to searches for electron-flavor appearance at short- and long-baseline using liquid argon time projection chamber technology. Notably, the data-driven studies of GeV-scale \\(\\nu_e/\\overline{\\nu}_e\\) interactions presented in this Letter probe an energy regime relevant for future DUNE oscillation physics.

Neutrino-nucleus cross section measurements are needed to improve interaction modeling to meet the precision needs of neutrino experiments in efforts to measure oscillation parameters and search for physics beyond the Standard Model. We review the difficulties associated with modeling neutrino-nucleus interactions that lead to a dependence on event generators in oscillation analyses and cross section measurements alike. We then describe data-driven model validation techniques intended to address this model dependence. The method relies on utilizing various goodness-of-fit tests and the correlations between different observables and channels to probe the model for defects in the phase space relevant for the desired analysis. These techniques shed light on relevant mis-modeling, allowing it to be detected before it begins to bias the cross section results. We compare more commonly used model validation methods which directly validate the model against alternative ones to these data-driven techniques and show their efficacy with fake data studies. These studies demonstrate that employing data-driven model validation in cross section measurements represents a reliable strategy to produce robust results that will stimulate the desired improvements to interaction modeling.

Large neutrino liquid argon time projection chamber (LArTPC) experiments can broaden their physics reach by reconstructing and interpreting MeV-scale energy depositions, or blips, present in their data. We demonstrate new calorimetric and particle discrimination capabilities at the MeV energy scale using reconstructed blips in data from the MicroBooNE LArTPC at Fermilab. We observe a concentration of low energy (\\(<\\)3 MeV) blips around fiberglass mechanical support struts along the TPC edges with energy spectrum features consistent with the Compton edge of 2.614 MeV \\(^{208}\\)Tl decay \\(\\gamma\\) rays. These features are used to verify proper calibration of electron energy scales in MicroBooNE's data to few percent precision and to measure the specific activity of \\(^{208}\\)Tl in the fiberglass composing these struts, \\((11.7 \\pm 0.2 ~\\text{(stat)} \\pm 2.8~\\text{(syst)})~\\text{Bq/kg}\\). Cosmogenically-produced blips above 3 MeV in reconstructed energy are used to showcase the ability of large LArTPCs to distinguish between low-energy proton and electron energy depositions. An enriched sample of low-energy protons selected using this new particle discrimination technique is found to be smaller in data than in dedicated CORSIKA cosmic ray simulations, suggesting either incorrect CORSIKA modeling of incident cosmic fluxes or particle transport modeling issues in Geant4.

We present a novel electrical technique to measure the tension of wires in multi-wire drift chambers. We create alternating electric fields by biasing adjacent wires on both sides of a test wire with a superposition of positive and negative DC voltages on an AC signal (\\(V_{\\rm AC} \\pm V_{\\rm DC}\\)). The resulting oscillations of the wire will display a resonance at its natural frequency, and the corresponding change of the capacitance will lead to a measurable current. This scheme is scalable to multiple wires and therefore enables us to precisely measure the tension of a large number of wires in a short time. This technique can also be applied at cryogenic temperatures making it an attractive solution for future large time-projection chambers such as the DUNE detector. We present the concept, an example implementation and its performance in a real-world scenario and discuss the limitations of the sensitivity of the system in terms of voltage and wire length.

We report the first double-differential cross section measurement of neutral-current neutral pion (NC\\(\\pi^0\\)) production in neutrino-argon scattering, as well as single-differential measurements of the same channel in terms of final states with and without protons. The kinematic variables of interest for these measurements are the \\(\\pi^0\\) momentum and the \\(\\pi^0\\) scattering angle with respect to the neutrino beam. A total of 4971 candidate NC\\(\\pi^0\\) events fully-contained within the MicroBooNE detector are selected using data collected at a mean neutrino energy of \\(\\sim 0.8\\)~GeV from \\(6.4\\times10^{20}\\) protons on target from the Booster Neutrino Beam at the Fermi National Accelerator Laboratory. After extensive data-driven model validation to ensure unbiased unfolding, the Wiener-SVD method is used to extract nominal flux-averaged cross sections. The results are compared to predictions from commonly used neutrino event generators, which tend to overpredict the measured NC\\(\\pi^0\\) cross section, especially in the 0.2-0.5~GeV/c \\(\\pi^0\\) momentum range and at forward scattering angles. Events with at least one proton present in the final state are also underestimated. This data will help improve the modeling of NC\\(\\pi^0\\) production, which represents a major background in measurements of charge-parity violation in the neutrino sector and in searches for new physics beyond the Standard Model.

This Letter presents an investigation of low-energy electron-neutrino interactions in the Fermilab Booster Neutrino Beam by the MicroBooNE experiment, motivated by the excess of electron-neutrino-like events observed by the MiniBooNE experiment. This is the first measurement to use data from all five years of operation of the MicroBooNE experiment, corresponding to an exposure of \\(1.11\\times 10^{21}\\) protons on target, a \\(70\\%\\) increase on past results. Two samples of electron neutrino interactions without visible pions are used, one with visible protons and one without any visible protons. MicroBooNE data is compared to two empirical models that modify the predicted rate of electron-neutrino interactions in different variables in the simulation to match the unfolded MiniBooNE low energy excess. In the first model, this unfolding is performed as a function of electron neutrino energy, while the second model aims to match the observed shower energy and angle distributions of the MiniBooNE excess. This measurement excludes an electron-like interpretation of the MiniBooNE excess based on these models at \\(> 99\\%\\) CL\\(_\\mathrm{s}\\) in all kinematic variables.

We report the measurement of the differential cross section \\(d^{2}\\sigma (E_{\\nu})/ d\\cos(\\theta_{\\mu}) dP_{\\mu}\\) for inclusive muon-neutrino charged-current scattering on argon. This measurement utilizes data from 6.4\\(\\times10^{20}\\) protons on target of exposure collected using the MicroBooNE liquid argon time projection chamber located along the Fermilab Booster Neutrino Beam with a mean neutrino energy of approximately 0.8~GeV. The mapping from reconstructed kinematics to truth quantities, particularly from reconstructed to true neutrino energy, is validated within uncertainties by comparing the distribution of reconstructed hadronic energy in data to that of the model prediction in different muon scattering angle bins after applying a conditional constraint from the muon momentum distribution in data. The success of this validation gives confidence that the missing energy in the MicroBooNE detector is well-modeled within uncertainties in simulation, enabling the unfolding to a three-dimensional measurement over muon momentum, muon scattering angle, and neutrino energy. The unfolded measurement covers an extensive phase space, providing a wealth of information useful for future liquid argon time projection chamber experiments measuring neutrino oscillations. Comparisons against a number of commonly used model predictions are included and their performance in different parts of the available phase-space is discussed.