Quasielastic Electromagnetic Scattering Cross Sections and World Data Comparisons in the {\fontfamily{qcr}\selectfont GENIE} Monte Carlo Event Generator

The usage of Monte Carlo neutrino event generators (MC$\nu$EGs) is a norm within the high-energy $\nu$ scattering community. The relevance of quasielastic (QE) energy regimes to $\nu$ oscillation experiments implies that accurate calculations of $\nu A$ cross sections in this regime will be a key contributor to reducing the systematic uncertainties affecting the extraction of oscillation parameters. In spite of this, many MC$\nu$EGs utilize highly phenomenological, parameterized models of QE scattering cross sections. Moreover, a culture of validation of MC$\nu$EGs against prolific electron ($e$) scattering data has been historically lacking. In this work, we implement new $e A$ cross sections obtained from nuclear ab initio approaches in GENIE, the primary MC$\nu$EG utilized by the FNAL community. In particular, we utilize results from Quantum MC methods which solve the many-body nuclear problem in the Short-Time Approximation (STA), allowing consistent retention of two-nucleon dynamics which are crucial to explain available nuclear electromagnetic (electroweak) data over a wide range of energy and momentum transfers. This new implementation in GENIE is fully tested against the world QE electromagnetic data, finding agreement with available data below $\sim2\,$GeV of beam energy with the aid of a scaling function formalism. The STA is currently limited to study $A\leq12$ nuclei, however, its semi-inclusive multibody identity components are exportable to other many-body computational techniques such as Auxiliary Field Diffusion MC which can reach $A\leq40$ systems while continuing to realize the factorization contained within the STA's multinucleon dynamics. Together, these developments promise to make future experiments such as DUNE more accurate in their assessment of MC$\nu$EG systematics, $\nu$ properties, and potentially empower the discovery of physics beyond the Standard Model.