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Abstract The existence of three distinct neutrino flavours,ν_e,ν_μandν_τ, is a central tenet of the Standard Model of particle physics^1,2. Quantum-mechanical interference can allow a neutrino of one initial flavour to be detected sometime later as a different flavour, a process called neutrino oscillation. Several anomalous observations inconsistent with this three-flavour picture have motivated the hypothesis that an additional neutrino state exists, which does not interact directly with matter, termed as ‘sterile’ neutrino,ν_s(refs. ^3–9). This includes anomalous observations from the Liquid Scintillator Neutrino Detector (LSND)³experiment and Mini-Booster Neutrino Experiment (MiniBooNE)^4,5, consistent withν_μ → ν_etransitions at a distance inconsistent with the three-neutrino picture. Here we use data obtained from the MicroBooNE liquid-argon time projection chamber¹⁰in two accelerator neutrino beams to exclude the single light sterile neutrino interpretation of the LSND and MiniBooNE anomalies at the 95% confidence level (CL). Moreover, we rule out a notable portion of the parameter space that could explain the gallium anomaly^6–8. This is one of the first measurements to use two accelerator neutrino beams to break a degeneracy betweenν_eappearance and disappearance, which would otherwise weaken the sensitivity to the sterile neutrino hypothesis. We find no evidence for eitherν_μ → ν_eflavour transitions orν_edisappearance that would indicate non-standard flavour oscillations. Our results indicate that previous anomalous observations consistent withν_μ → ν_etransitions cannot be explained by introducing a single sterile neutrino state. 

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. The MicroBooNE data show reasonable agreement with the nominal prediction, with $p$values $\ge 26.7\%$when the two ${\nu }_e$samples are combined, though the prediction exceeds the data in limited regions of phase space. The data are further 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 electronlike interpretation of the MiniBooNE excess based on these models at $>99\%{\mathrm{CL}}_{\mathrm{s}}$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 mismodeling, 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. Published by the American Physical Society2025 

We report the first double-differential cross section measurement of neutral-current neutral pion ( $\mathrm{NC}{\pi }^0$) 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 $\mathrm{NC}{\pi }^0$events fully contained within the MicroBooNE detector are selected using data collected at a mean neutrino energy of $\sim 0.8\mathrm{GeV}$from $6.4\times {10}^{20}$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-singular-value-decomposition 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 $\mathrm{NC}{\pi }^0$cross section, especially in the $0.2–0.5\mathrm{GeV}/\mathrm{c}$ ${\pi }^0$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 $\mathrm{NC}{\pi }^0$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 present a search for long-lived particles (LLPs), produced in kaon decays, that decay to two muons inside the ICARUS neutrino detector. This channel would be a signal of hidden sector models that can address outstanding issues in particle physics such as the strong CP problem and the microphysical origin of dark matter. The search is performed with data collected in the Neutrinos at the Main Injector (NuMI) beam at Fermilab corresponding to $2.41\times {10}^{20}$protons-on-target. No new physics signal is observed, and we set world leading limits on heavy QCD axions, as well as for the Higgs portal scalar among dedicated searches. Limits are also presented in a model-independent way applicable to any new physics model predicting the process $K\to \pi +S(\to \mu \mu )$, for a LLP $S$. This result is the first search for new physics performed with the ICARUS detector at Fermilab. It paves the way for the future program of LLP searches at ICARUS. Published by the American Physical Society2025 

Abstract 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. 

Abstract 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. 

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 ( $<3\mathrm{MeV}$) blips around fiberglass mechanical support struts along the time projection chamber edges with energy spectrum features consistent with the Compton edge of 2.614 MeV ${}^{208}\mathrm{Tl}$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 ${}^{208}\mathrm{Tl}$in the fiberglass composing these struts, $(11.7\pm 0.2\left(\mathrm{stat}\right)\pm 3.1\left(\mathrm{syst}\right))\mathrm{Bq}/\mathrm{kg}$. 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 cosmic-ray simulations, suggesting either incorrect modeling of incident cosmic fluxes or particle transport modeling issues in eant4. Published by the American Physical Society2025 

We present a measurement of neutral pion production in charged-current interactions using data recorded with the MicroBooNE detector exposed to Fermilab’s booster neutrino beam. The signal comprises one muon, one neutral pion, any number of nucleons, and no charged pions. Studying neutral pion production in the MicroBooNE detector provides an opportunity to better understand neutrino-argon interactions, and is crucial for future accelerator-based neutrino oscillation experiments. Using a dataset corresponding to $6.86\times {10}^{20}$protons on target, we present single-differential cross sections in muon and neutral pion momenta, scattering angles with respect to the beam for the outgoing muon and neutral pion, as well as the opening angle between the muon and neutral pion. Data extracted cross sections are compared to generator predictions. We report good agreement between the data and the models for scattering angles, except for an over-prediction by generators at muon forward angles. Similarly, the agreement between data and the models as a function of momentum is good, except for an underprediction by generators in the medium momentum ranges, 200–400 MeV for muons and 100–200 MeV for pions. Published by the American Physical Society2024 

We present a deep learning-based method for estimating the neutrino energy of charged-current neutrino-argon interactions. We employ a recurrent neural network (RNN) architecture for neutrino energy estimation in the MicroBooNE experiment, utilizing liquid argon time projection chamber (LArTPC) detector technology. Traditional energy estimation approaches in LArTPCs, which largely rely on reconstructing and summing visible energies, often experience sizable biases and resolution smearing because of the complex nature of neutrino interactions and the detector response. The estimation of neutrino energy can be improved after considering the kinematics information of reconstructed final-state particles. Utilizing kinematic information of reconstructed particles, the deep learning-based approach shows improved resolution and reduced bias for the muon neutrino Monte Carlo simulation sample compared to the traditional approach. In order to address the common concern about the effectiveness of this method on experimental data, the RNN-based energy estimator is further examined and validated with dedicated data-simulation consistency tests using MicroBooNE data. We also assess its potential impact on a neutrino oscillation study after accounting for all statistical and systematic uncertainties and show that it enhances physics sensitivity. This method has good potential to improve the performance of other physics analyses. Published by the American Physical Society2024