Summary of Global Extraction of the $\rm^{12}C$ Nuclear Electromagnetic Response Functions and Comparisons to Nuclear Theory and Neutrino/Electron Monte Carlo Generators at Nufact24

Abstract

We present a brief report (at the Nufact-2024 conference) summarizing a global extraction of the ${\rm ^{12}C}$ longitudinal (${\cal R}_L$) and transverse (${\cal R}_T$) nuclear electromagnetic response functions from an analysis of all available electron scattering data on carbon. Since the extracted response functions cover a large kinematic range they can be readily used for comparison to theoretical predictions as well as validation and tuning Monte Carlo (MC) generators for electron and neutrino scattering experiments. Comparisons to several theoretical approaches and MC generators are given in arXiv:2409.10637v1 [hep-ex]. We find that among all the theoretical models that were investigated, the ``Energy Dependent-Relativistic Mean Field'' (ED-RMF) approach provides the best description of both the Quasielastic (QE) and {\it nuclear excitation} response functions (leading to single nucleon final states) over all values of four-momentum transfer. he QE data are also well described by the "Short Time Approximation Quantum Monte Carlo" (STA-QMC) calculation which includes both single and two nucleon final states which presently is only valid for momentum transfer $0.3<{\bf q} < 0.65$ GeV and does not include nuclear excitations. An analytic extrapolation of STA-QMC to lower $\bf q$ has been implemented in the GENIE MC generator for $\rm^{4}He$ and a similar extrapolation for ${\rm ^{12}C}$ is under development. STA validity for ${\bf q} >$ 0.65 GeV requires the implementation of relativistic corrections. Both approaches have the added benefit that the calculations are also directly applicable to the same kinematic regions for neutrino scattering. In addition we also report on a universal fit to all electron scattering data that can be used in lieu of experimental data for validation of Monte Carlo generators (and is in the process of being implemented in GENIE).