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  1. 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 
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    Free, publicly-accessible full text available November 1, 2025
  2. 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 to6.86×1020protons 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 
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    Free, publicly-accessible full text available November 1, 2025
  3. Abstract

    SBND is the near detector of the Short-Baseline Neutrino program at Fermilab. Its location near to the Booster Neutrino Beam source and relatively large mass will allow the study of neutrino interactions on argon with unprecedented statistics. This paper describes the expected performance of the SBND photon detection system, using a simulated sample of beam neutrinos and cosmogenic particles. Its design is a dual readout concept combining a system of 120 photomultiplier tubes, used for triggering, with a system of 192 X-ARAPUCA devices, located behind the anode wire planes. Furthermore, covering the cathode plane with highly-reflective panels coated with a wavelength-shifting compound recovers part of the light emitted towards the cathode, where no optical detectors exist. We show how this new design provides a high light yield and a more uniform detection efficiency, an excellent timing resolution and an independent 3D-position reconstruction using only the scintillation light. Finally, the whole reconstruction chain is applied to recover the temporal structure of the beam spill, which is resolved with a resolution on the order of nanoseconds.

     
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    Free, publicly-accessible full text available October 1, 2025
  4. Abstract

    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$$60\%$$60%of selected tracks corresponding to neutron-induced secondary protons. At this purity, the integrated efficiency is 8.4% for neutrons that produce a detectable proton.

     
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    Free, publicly-accessible full text available October 1, 2025
  5. Understanding whether organisms will be able to adapt to human-induced stressors currently endangering their existence is an urgent priority. Globally, multiple species moult from a dark summer to white winter coat to maintain camouflage against snowy landscapes. Decreasing snow cover duration owing to climate change is increasing mismatch in seasonal camouflage. To directly test for adaptive responses to recent changes in snow cover, we repeated historical (1950s) field studies of moult phenology in mountain hares ( Lepus timidus ) in Scotland. We found little evidence that population moult phenology has shifted to align seasonal coat colour with shorter snow seasons, or that phenotypic plasticity prevented increases in camouflage mismatch. The lack of responses resulted in 35 additional days of mismatch between 1950 and 2016. We emphasize the potential role of weak directional selection pressure and low genetic variability in shaping the scope for adaptive responses to anthropogenic stressors. 
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  6. Abstract

    We present a novel methodology to search for intranuclear neutron-antineutron transition (n⟶) followed by-nucleon annihilation within an40Ar nucleus, using the MicroBooNE liquid argon time projection chamber (LArTPC) detector. A discovery of 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⟶events based on their unique features and differentiate them from cosmogenic backgrounds. The achieved signal and background efficiencies are (70.22 ± 6.04)% and (0.0020 ± 0.0003)%, respectively. A demonstration of a search is performed with a data set corresponding to an exposure of 3.32 ×1026neutron-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⟶lifetime in40Ar of τm≳ 1.1×1026years, and on the free n⟶transition time of τn⟶≳ 2.6×105s, 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.

     
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    Free, publicly-accessible full text available July 1, 2025
  7. We report the first double-differential neutrino-argon cross section measurement made simultaneously for final states with and without protons for the inclusive muon neutrino charged-current interaction channel. The proton kinematics of this channel are further explored with a differential cross section measurement as a function of the leading proton’s kinetic energy that extends across the detection threshold. These measurements use data collected with the MicroBooNE detector from6.4×1020protons on target from the Fermilab booster neutrino beam with a mean neutrino energy of0.8GeV. Extensive data-driven model validation utilizing the conditional constraint formalism is employed. This motivates enlarging the uncertainties with an empirical reweighting approach to minimize the possibility of extracting biased cross section results. The extracted nominal flux-averaged cross sections are compared to widely used event generator predictions revealing severe mismodeling of final states without protons for muon neutrino charged-current interactions, possibly from insufficient treatment of final state interactions. These measurements provide a wealth of new information useful for improving event generators which will enhance the sensitivity of precision measurements in neutrino experiments.

    Published by the American Physical Society2024 
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    Free, publicly-accessible full text available July 1, 2025
  8. 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 from6.4×1020protons 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.

    Published by the American Physical Society2024 
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    Free, publicly-accessible full text available July 1, 2025
  9. We present a first search for dark-trident scattering in a neutrino beam using a dataset corresponding to7.2×1020protons on target taken with the MicroBooNE detector at Fermilab. Proton interactions in the neutrino target at the main injector produceπ0andηmesons, which could decay into dark-matter (DM) particles mediated via a dark photonA. A convolutional neural network is trained to identify interactions of the DM particles in the liquid-argon time projection chamber (LArTPC) exploiting its imagelike reconstruction capability. In the absence of a DM signal, we provide limits at the 90% confidence level on the squared kinematic mixing parameterϵ2as a function of the dark-photon mass in the range10MA400MeV. The limits cover previously unconstrained parameter space for the production of fermion or scalar DM particlesχfor two benchmark models with mass ratiosMχ/MA=0.6and 2 and for dark fine-structure constants0.1αD1.

    Published by the American Physical Society2024 
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    Free, publicly-accessible full text available June 1, 2025