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Charged current induced electron-proton scattering and the axial vector form factor

A. Fatima, M. Sajjad Athar*, and S. K. Singh

  • *Contact author: sajathar@gmail.com

Phys. Rev. D 114, 013004 – Published 14 July, 2026

DOI: https://doi.org/10.1103/bffn-fzgx

Abstract

We investigate the total scattering cross section (σ), the differential cross section (dσdQ2), the longitudinal [AL(Ee,Q2)] and perpendicular [AP(Ee,Q2)] spin asymmetries of the polarized target proton, as well as the longitudinal [PL(Ee,Q2)], perpendicular [PP(Ee,Q2)], and transverse [PT(Ee,Q2)] polarization components of the final neutron, in the weak charged current induced electron-proton scattering relevant to the future experiments at the Thomas Jefferson National Accelerator Facility (JLab) and Mainz Microtron (MAMI). The analysis is performed assuming time-reversal (T) invariance as well as without assuming T invariance, allowing for a nonvanishing transverse polarization component of the final nucleon, perpendicular to the production plane. Numerical results are presented for the above mentioned observables, and their sensitivities to the various parametrizations of the axial vector form factor g1(Q2) and a nonzero weak electric form factor g2(Q2) are examined. We find that the cross section depends strongly on the parametrizations used for the axial vector form factor. Moreover, the dipole parametrization of g1(Q2) with a higher value of the axial dipole mass MA simulates the apparent enhancement in σ obtained using the nondipole parametrizations like the z-expansion and Faddeev equation form. The cross sections are found to depend only weakly on the weak electric form factor g2(Q2), which is associated with the violation of G-invariance. On the contrary, the spin observables both AL,P(Ee,Q2) and PL,P(Ee,Q2) are found to be strongly dependent on g2(Q2). This study may be useful in the analysis of the neutrino oscillation experiments to provide an alternative constrain on the parametrization of axial vector form factor, which currently has large uncertainties.

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