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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.

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 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.

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.

This paper reports on a measurement of electron-ion recombination in liquid argon in the ICARUS liquid argon time projection chamber (LArTPC). A clear dependence of recombination on the angle of the ionizing particle track relative to the drift electric field is observed. An ellipsoid modified box (EMB) model of recombination describes the data across all measured angles. These measurements are used for the calorimetric energy scale calibration of the ICARUS TPC, which is also presented. The impact of the EMB model is studied on calorimetric particle identification, as well as muon and proton energy measurements. Accounting for the angular dependence in EMB recombination improves the accuracy and precision of these measurements.

The ICARUS liquid argon time projection chamber (LArTPC) neutrino detector has been taking physics data since 2022 as part of the Short-Baseline Neutrino (SBN) Program. This paper details the equalization of the response to charge in the ICARUS time projection chamber (TPC), as well as data-driven tuning of the simulation of ionization charge signals and electronics noise. The equalization procedure removes non-uniformities in the ICARUS TPC response to charge in space and time. This work leverages the copious number of cosmic ray muons available to ICARUS at the surface. The ionization signal shape simulation applies a novel procedure that tunes the simulation to match what is measured in data. The end result of the equalization procedure and simulation tuning allows for a comparison of charge measurements in ICARUS between Monte Carlo simulation and data, showing good performance with minimal residual bias between the two.

A detailed understanding of inclusive muon neutrino charged-current interactions on argon is crucial to the study of neutrino oscillations in current and future experiments using liquid argon time projection chambers. To that end, we report a comprehensive set of differential cross section measurements for this channel that simultaneously probe the leptonic and hadronic systems by dividing the channel into final states with and without protons. Measurements of the proton kinematics and proton multiplicity of the final state are also presented. For these measurements, we utilize data collected with the MicroBooNE detector from 6.4\\(\\times10^{20}\\) protons on target from the Fermilab Booster Neutrino Beam at a mean neutrino energy of approximately 0.8 GeV. We present in detail the cross section extraction procedure, including the unfolding, and model validation that uses data to model comparisons and the conditional constraint formalism to detect mismodeling that may introduce biases to extracted cross sections that are larger than their uncertainties. The validation exposes insufficiencies in the overall model, motivating the inclusion of an additional data-driven reweighting systematic to ensure the accuracy of the unfolding. The extracted results are compared to a number of event generators and their performance is discussed with a focus on the regions of phase-space that indicate the greatest need for modeling improvements.

We present a novel methodology to search for intranuclear neutron-antineutron transition (\\(n\\rightarrow\\bar{n}\\)) followed by \\(\\bar{n}\\)-nucleon annihilation within an \\(^{40}\\)Ar nucleus, using the MicroBooNE liquid argon time projection chamber (LArTPC) detector. A discovery of \\(n\\rightarrow\\bar{n}\\) transition or a new best limit on the lifetime of this process would either constitute physics beyond the Standard Model or greatly constrain theories of baryogenesis, respectively. The approach presented in this paper makes use of deep learning methods to select \\(n\\rightarrow\\bar{n}\\) events based on their unique features and differentiate them from cosmogenic backgrounds. The achieved signal and background efficiencies are (70.22\\(\\pm\\)6.04)\\% and (0.0020\\(\\pm\\)0.0003)\\%, respectively. A demonstration of a search is performed with a data set corresponding to an exposure of \\(3.32 \\times10^{26}\\,\\)neutron-years, and where the background rate is constrained through direct measurement, assuming the presence of a negligible signal. With this approach, no excess of events over the background prediction is observed, setting a demonstrative lower bound on the \\(n\\rightarrow\\bar{n}\\) lifetime in \\(^{40}\\)Ar of \\(\\tau_{\\textrm{m}} \\gtrsim 1.1\\times10^{26}\\,\\)years, and on the free \\(n\\rightarrow\\bar{n}\\) transition time of \\(\\tau_{\\textrm{\\nnbar}} \\gtrsim 2.6\\times10^{5}\\,\\)s, each at the \\(90\\%\\) confidence level. This analysis represents a first-ever proof-of-principle demonstration of the ability to search for this rare process in LArTPCs with high efficiency and low background.

A significant challenge in measurements of neutrino oscillations is reconstructing the incoming neutrino energies. While modern fully-active tracking calorimeters such as liquid argon time projection chambers in principle allow the measurement of all final state particles above some detection threshold, undetected neutrons remain a considerable source of missing energy with little to no data constraining their production rates and kinematics. We present the first demonstration of tagging neutrino-induced neutrons in liquid argon time projection chambers using secondary protons emitted from neutron-argon interactions in the MicroBooNE detector. We describe the method developed to identify neutrino-induced neutrons and demonstrate its performance using neutrons produced in muon-neutrino charged current interactions. The method is validated using a small subset of MicroBooNE's total dataset. The selection yields a sample with \\(60\\%\\) of selected tracks corresponding to neutron-induced secondary protons.