Simulation-based proof-of-concept demonstrates neutron identification and reconstruction of direction and energy using blips from inelastic scattering in LArTPCs.
Understanding the energy resolution of liquid argon neutrino detectors
5 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
abstract
Available estimates for the energy resolution of DUNE vary by as much as a factor of four. To address this controversy, and to connect the resolution to the underlying physical processes, we build an independent simulation pipeline for neutrino events in liquid argon, combining the public tools GENIE and FLUKA. Using this pipeline, we first characterize the channels of non-hermeticity of DUNE, including subthreshold particles, charge recombination, and nuclear breakup. Particular attention is paid to the role of neutrons, which are responsible for a large fraction of missing energy in all channels. Next, we determine energy resolution, by quantifying event-to-event stochastic fluctuations in missing energy. This is done for several sets of assumptions about the reconstruction performance, including those available in the literature. The resulting migration matrices, connecting true and reconstructed neutrino energies, are presented. Finally, we quantify the impact of different improvements on the experimental performance. For example, we show that dropping particle identification information degrades the resolution by a factor of two, while omitting charge deposits from de-excitation gammas worsens it by about 25%. In the future, this framework can be used to assess the impact of cross section uncertainties on the oscillation sensitivity.
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Supervised ML classification of neutrino events by interaction channel prior to energy reconstruction improves accuracy and sensitivity by 10-20% in simulated DUNE analyses while remaining robust to generator mismodeling.
Combining charge and light signals in LArTPCs yields better sub-GeV energy reconstruction, 70% electron neutrino-antineutrino separation efficiency, and about 20-degree direction improvement for antineutrinos via neutron isolation algorithms.
Inelasticity and neutron multiplicity distributions differ between neutrino and antineutrino charged-current events in liquid scintillator, enabling quantitative discrimination for atmospheric oscillation studies.
citing papers explorer
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Neutron Reconstruction via Blips in Liquid Argon Time Projection Chambers
Simulation-based proof-of-concept demonstrates neutron identification and reconstruction of direction and energy using blips from inelastic scattering in LArTPCs.
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Improving Neutrino Oscillation Measurements through Event Classification
Supervised ML classification of neutrino events by interaction channel prior to energy reconstruction improves accuracy and sensitivity by 10-20% in simulated DUNE analyses while remaining robust to generator mismodeling.
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Enhanced Reconstruction of Sub-GeV Neutrinos Charged Current Interactions in LArTPC
Combining charge and light signals in LArTPCs yields better sub-GeV energy reconstruction, 70% electron neutrino-antineutrino separation efficiency, and about 20-degree direction improvement for antineutrinos via neutron isolation algorithms.
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Atmospheric Neutrino Charged-Current Interactions at Large Liquid-Scintillator Detectors: I. Physics of Neutrino-Antineutrino Discrimination
Inelasticity and neutron multiplicity distributions differ between neutrino and antineutrino charged-current events in liquid scintillator, enabling quantitative discrimination for atmospheric oscillation studies.
- The High W Challenge: Robust Neutrino Energy Estimators for LArTPCs