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1. Wire-cell 3D pattern recognition techniques for neutrino event reconstruction in large LArTPCs: algorithm description and quantitative evaluation with MicroBooNE simulation

   https://doi.org/10.1088/1748-0221/17/01/P01037  

   Abratenko, P.; An, R.; Anthony, J.; Arellano, L.; Asaadi, J.; Ashkenazi, A.; Balasubramanian, S.; Baller, B.; Barnes, C.; Barr, G.; et al (January 2022, Journal of Instrumentation)

   Abstract Wire-Cell is a 3D event reconstruction package for liquid argon time projection chambers. Through geometry, time, and drifted charge from multiple readout wire planes, 3D space points with associated charge are reconstructed prior to the pattern recognition stage. Pattern recognition techniques, including track trajectory and d Q /d x (ionization charge per unit length) fitting, 3D neutrino vertex fitting, track and shower separation, particle-level clustering, and particle identification are then applied on these 3D space points as well as the original 2D projection measurements. A deep neural network is developed to enhance the reconstruction of the neutrino interaction vertex. Compared to traditional algorithms, the deep neural network boosts the vertex efficiency by a relative 30% for charged-current ν e interactions. This pattern recognition achieves 80–90% reconstruction efficiencies for primary leptons, after a 65.8% (72.9%) vertex efficiency for charged-current ν e (ν μ ) interactions. Based on the resulting reconstructed particles and their kinematics, we also achieve 15-20% energy reconstruction resolutions for charged-current neutrino interactions. 

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2. Measurement of the differential cross section for neutral pion production in charged-current muon neutrino interactions on argon with the MicroBooNE detector

   https://doi.org/10.1103/PhysRevD.110.092014  

   Abratenko, P; Alterkait, O; Andrade_Aldana, D; Arellano, L; Asaadi, J; Ashkenazi, A; Balasubramanian, S; Baller, B; Barr, G; Barrow, D; et al (November 2024, Physical Review D)

   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 

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3. Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

   https://doi.org/10.1140/epjc/s10052-022-10791-2  

   Abed Abud, A.; Abi, B.; Acciarri, R.; Acero, M. A.; Adames, M. R.; Adamov, G.; Adamowski, M.; Adams, D.; Adinolfi, M.; Aduszkiewicz, A.; et al (October 2022, The European Physical Journal C)

   Abstract Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation. 

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4. First Measurement of ${\nu }_e$ and ${\overline{\nu }}_e$ Charged-Current Single Charged-Pion Production Differential Cross Sections on Argon Using the MicroBooNE Detector

   https://doi.org/10.1103/sfrz-c8m9  

   Abratenko, P; Andrade_Aldana, D; Arellano, L; Asaadi, J; Ashkenazi, A; Balasubramanian, S; Baller, B; Barnard, A; Barr, G; Barrow, D; et al (August 2025, Physical Review Letters)

   Understanding electron neutrino interactions is crucial for measurements of neutrino oscillations and searches for new physics in neutrino experiments. We present the first measurement of the flux-averaged ${\nu }_e+{\overline{\nu }}_e$charged-current single charged-pion production cross section on argon using the MicroBooNE detector and data from the NuMI neutrino beam. The total cross section is measured to be $[0.93\pm 0.13(\mathrm{stat})\pm 0.27(\mathrm{syst}\left)\right]\times {10}^{-39}{\mathrm{cm}}^2/\mathrm{nucleon}$at a mean ${\nu }_e+{\overline{\nu }}_e$energy of 730 MeV. Differential cross sections are also reported in electron energy, electron and pion angles, and electron-pion opening angle. 

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5. Suppression of neutral-pion production in deep-inelastic scattering off nuclei with the CLAS detector

   https://doi.org/10.1103/kbhz-h4jv  

   Mineeva, T; Brooks, W K; El_Alaoui, A; Hakobyan, H; Joo, K; López, J A; Soto, O; Achenbach, P; Akbar, Z; Alvarado, J S; et al (September 2025, Physical Review C)

   We present the first threefold differential measurement for neutral-pion multiplicity ratios produced in semi-inclusive deep-inelastic electron scattering on carbon, iron, and lead nuclei normalized to deuterium from CLAS at Jefferson Lab. We found that the neutral-pion multiplicity ratio is maximally suppressed for the leading hadrons (energy fraction $z\to$1), suppression varying from 25% in carbon up to 75% in lead. An enhancement of the multiplicity ratio at low $z$and high $p_T^2$is observed, suggesting an interconnection between these two variables. This behavior is qualitatively similar to the previous twofold differential measurement of charged pions by the HERMES Collaboration and, recently, by CLAS Collaboration. The largest enhancement was observed at high $p_T^2$for heavier nuclei, namely, iron and lead, while the smallest enhancement was observed for the lightest nucleus, carbon. This behavior suggests a competition between partonic multiple scattering, which causes enhancement, and hadronic inelastic scattering, which causes suppression. 

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