126 research outputs found
Measurement of nuclear effects in neutrino interactions with minimal dependence on neutrino energy
We present a phenomenological study of nuclear effects in neutrino
charged-current interactions, using transverse kinematic imbalances in
exclusive measurements. Novel observables with minimal dependence on neutrino
energy are proposed to study quasielastic scattering, and especially resonance
production. They should be able to provide direct constraints on nuclear
effects in neutrino- and antineutrino-nucleus interactions.Comment: 7 pages, 9 figures, accepted version by PR
Reducing model bias in a deep learning classifier using domain adversarial neural networks in the MINERvA experiment
We present a simulation-based study using deep convolutional neural networks
(DCNNs) to identify neutrino interaction vertices in the MINERvA passive
targets region, and illustrate the application of domain adversarial neural
networks (DANNs) in this context. DANNs are designed to be trained in one
domain (simulated data) but tested in a second domain (physics data) and
utilize unlabeled data from the second domain so that during training only
features which are unable to discriminate between the domains are promoted.
MINERvA is a neutrino-nucleus scattering experiment using the NuMI beamline at
Fermilab. -dependent cross sections are an important part of the physics
program, and these measurements require vertex finding in complicated events.
To illustrate the impact of the DANN we used a modified set of simulation in
place of physics data during the training of the DANN and then used the label
of the modified simulation during the evaluation of the DANN. We find that deep
learning based methods offer significant advantages over our prior track-based
reconstruction for the task of vertex finding, and that DANNs are able to
improve the performance of deep networks by leveraging available unlabeled data
and by mitigating network performance degradation rooted in biases in the
physics models used for training.Comment: 41 page
Antineutrino Charged-Current Reactions on Hydrocarbon with Low Momentum Transfer
We report on multinucleon effects in low momentum transfer (\u3c 0.8 GeV/c) antineutrino interactions on plastic (CH) scintillator. These data are from the 2010-2011 antineutrino phase of the MINERvA experiment at Fermilab. The hadronic energy spectrum of this inclusive sample is well described when a screening effect at a low energy transfer and a two-nucleon knockout process are added to a relativistic Fermi gas model of quasielastic, Delta resonance, and higher resonance processes. In this analysis, model elements introduced to describe previously published neutrino results have quantitatively similar benefits for this antineutrino sample. We present the results as a double-differential cross section to accelerate the investigation of alternate models for antineutrino scattering off nuclei
Measurement of and charged current inclusive cross sections and their ratio with the T2K off-axis near detector
We report a measurement of cross section and the first measurements of the cross section
and their ratio
at (anti-)neutrino energies below 1.5
GeV. We determine the single momentum bin cross section measurements, averaged
over the T2K -flux, for the detector target material (mainly
Carbon, Oxygen, Hydrogen and Copper) with phase space restricted laboratory
frame kinematics of 500 MeV/c. The
results are and $\sigma(\nu)=\left( 2.41\
\pm0.022{\rm{(stat.)}}\pm0.231{\rm (syst.)}\ \right)\times10^{-39}^{2}R\left(\frac{\sigma(\bar{\nu})}{\sigma(\nu)}\right)=
0.373\pm0.012{\rm (stat.)}\pm0.015{\rm (syst.)}$.Comment: 18 pages, 8 figure
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