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Register a new userQuasielastic Electromagnetic Scattering Cross Sections and World Data Comparisons in the {fontfamily{qcr}selectfont GENIE} Monte Carlo Event Generator
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The usage of Monte Carlo neutrino event generators (MC$ u$EGs) is a norm within the high-energy $ u$ scattering community. The relevance of quasielastic (QE) energy regimes to $ u$ oscillation experiments implies that accurate calculations of $ u 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$ u$EGs utilize highly phenomenological, parameterized models of QE scattering cross sections. Moreover, a culture of validation of MC$ u$EGs against prolific electron ($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$ u$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 $Aleq12$ 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 $Aleq40$ systems while continuing to realize the factorization contained within the STAs multinucleon dynamics. Together, these developments promise to make future experiments such as DUNE more accurate in their assessment of MC$ u$EG systematics, $ u$ properties, and potentially empower the discovery of physics beyond the Standard Model.
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The extraction of neutrino mixing parameters from accelerator-based neutrino oscillation experiments relies on proper modeling of neutrino-nucleus scattering processes using neutrino-interaction event generators. Experimental tests of these generators are difficult due to the broad range of neutrino energies produced in accelerator-based beams and the low statistics of current experiments. Here we overcome these difficulties by exploiting the similarity of neutrino and electron interactions with nuclei to test neutrino event generators using high-precision inclusive electron scattering data. To this end, we revised the electron-scattering mode of the GENIE event generator ($e$-GENIE) to include electron-nucleus bremsstrahlung radiation effects and to use, when relevant, the exact same physics models and model parameters, as the standard neutrino-scattering version. We also implemented new models for quasielastic (QE) scattering and meson exchange currents (MEC) based on the theory-inspired SuSAv2 approach. Comparing the new $e$-GENIE predictions with inclusive electron scattering data, we find an overall adequate description of the data in the QE- and MEC-dominated lower energy transfer regime, especially when using the SuSAv2 models. Higher energy transfer-interactions, which are dominated by resonance production, are still not well modeled by $e$-GENIE.
Precision neutrino oscillation experiments of the future---of which DUNE is a prime example---require reliable event generator tools. The 1--4 GeV energy regime, in which DUNE will operate, is marked by the transition from the low-energy nuclear physics domain to that of perturbative QCD, resulting in rich and highly complex physics. Given this complexity, it is important to establish a validation procedure capable of disentangling the physical processes and testing each of them individually. Here, we demonstrate the utility of this approach by benchmarking the GENIE generator, currently used by all Fermilab-based experiments, against a broad set of inclusive electron-scattering data. This comparison takes advantage of the fact that, while electron-nucleus and neutrino-nucleus processes share a lot of common physics, electron scattering gives one access to precisely known beam energies and scattering kinematics. Exploring the kinematic parameter range relevant to DUNE in this manner, we observe patterns of large discrepancies between the generator and data. These discrepancies are most prominent in the pion-producing regimes and are present not only in medium-sized nuclei, including argon, but also in deuterium and hydrogen targets, indicating mismodeled hadronic physics. Several directions for possible improvement are discussed.
Martini et al. [Phys. Rev. C 94, 015501 (2016)] recently observed that when the produced-leptons mass plays an important role, the charged-current quasielastic cross section for muon neutrinos can be higher than that for electron neutrinos. Here I argue that this effect appears solely in the theoretical descriptions of nuclear effects in which nucleon knockout requires the energy and momentum transfers to lie in a narrow range of the kinematically allowed values.
We present a new strategy using artificial intelligence (AI) to build the first AI-based Monte Carlo event generator (MCEG) capable of faithfully generating final state particle phase space in lepton-hadron scattering. We show a blueprint for integrating machine learning strategies with calibrated detector simulations to build a vertex-level, AI-based MCEG, free of theoretical assumptions about femtometer scale physics. As the first steps towards this goal, we present a case study for inclusive electron-proton scattering using synthetic data from the PYTHIA MCEG for testing and validation purposes. Our quantitative results validate our proof of concept and demonstrate the predictive power of the trained models. The work suggests new venues for data preservation to enable future QCD studies of hadrons structure, and the developed technology can boost the science output of physics programs at facilities such as Jefferson Lab and the future Electron-Ion Collider.
We review the main software and computing challenges for the Monte Carlo physics event generators used by the LHC experiments, in view of the High-Luminosity LHC (HL-LHC) physics programme. This paper has been prepared by the HEP Software Foundation (HSF) Physics Event Generator Working Group as an input to the LHCC review of HL-LHC computing, which has started in May 2020.
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