MINERvA compares quasielastic-like cross sections at two neutrino beam energies and finds discrepancies pointing to overestimated final state interactions for protons and pions.
Charged-current neutrino-nucleus reactions within the SuSAv2-MEC approach
2 Pith papers cite this work. Polarity classification is still indexing.
abstract
We present a detailed study of charged-current (CC) neutrino-nucleus reactions in a fully relativis- tic framework and comparisons with recent experiments spanning an energy range from hundreds of MeV up to 100 GeV within the SuperScaling Approach, which is based on the analysis of electron- nucleus scattering data and has been recently improved with the inclusion of Relativistic Mean Field theory effects. We also evaluate and discuss the impact of two-particle two-hole meson-exchange currents (2p-2h MEC) on neutrino-nucleus interactions through the analysis of two-particle two-hole axial and vector contributions to weak response functions in a fully relativistic Fermi gas. The results show a fairly good agreement with experimental data over the whole range of neutrino energies.
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hep-ex 2years
2026 2verdicts
UNVERDICTED 2roles
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use method 1representative citing papers
ICARUS measures flux-averaged differential CCQE-like cross sections in lepton angle, opening angle, and transverse imbalance variables, finding general agreement with event generators but insufficient power to discriminate models.
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Comparisons of triple-differential cross sections for quasielastic-like $\nu_\mu$-hydrocarbon interactions using $\langle E_\nu\rangle \sim$ 3~GeV versus $\sim$ 6~GeV beams in MINERvA
MINERvA compares quasielastic-like cross sections at two neutrino beam energies and finds discrepancies pointing to overestimated final state interactions for protons and pions.
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Measurement of muon (anti-)neutrino charged-current quasielastic-like cross section using off-axis NuMI beam at ICARUS
ICARUS measures flux-averaged differential CCQE-like cross sections in lepton angle, opening angle, and transverse imbalance variables, finding general agreement with event generators but insufficient power to discriminate models.