Removal Energies and Final State Interaction in Lepton Nucleus Scattering

We investigate the binding energy parameters that should be used in modeling electron and neutrino scattering from nucleons bound in a nucleus within the framework of the impulse approximation. We discuss the relation between binding energy, missing energy, removal energy ($\epsilon$), spectral functions and shell model energy levels and extract updated removal energy parameters from ee$^{\prime}$p spectral function data. We address the difference in parameters for scattering from bound protons and neutrons. We also use inclusive e-A data to extract an empirical parameter $U_{FSI}( (\vec q_3+\vec k)^2)$ to account for the interaction of final state nucleons (FSI) with the optical potential of the nucleus. Similarly we use $V_{eff}$ to account for the Coulomb potential of the nucleus. With three parameters $\epsilon$, $U_{FSI}( (\vec q_3+\vec k)^2)$ and $V_{eff}$ we can describe the energy of final state electrons for all available electron QE scattering data. The use of the updated parameters in neutrino Monte Carlo generators reduces the systematic uncertainty in the combined removal energy (with FSI corrections) from $\pm$ 20 MeV to $\pm$ 5 MeV.Comment: 21 pages, 22 Figures, 11 Tables, Accepted for publication in Eur. Phys. J. C. 2019, all fits to Optical potential redone with respect to (q3+k)^

Comparison of optical potential for nucleons and Δ\Delta resonances

Precise modeling of neutrino interactions on nuclear targets is essential for neutrino oscillations experiments. The modeling of the energy of final state particles in quasielastic (QE) scattering and resonance production on bound nucleons requires knowledge of both the removal energy of the initial state bound nucleon as well as the average Coulomb and nuclear optical potentials for final state leptons and hadrons. We extract the average values of the real part of the nuclear optical potential for final state nucleons ($U_{opt}^{QE}$) as a function of the nucleon kinetic energy from inclusive electron scattering data on nuclear targets ($\bf_{6}^{12}C$+$\bf_{8}^{16}O$, $\bf_{20}^{40}Ca$+$\bf_{18}^{40}Ar$, $\bf_{3}^{6}Li$, $\bf_{18}^{27}Al$, $\bf_{26}^{56}Fe$, $\bf_{82}^{208}Pb$) in the QE region and compare to calculations. We also extract values of the average of the real part of the nuclear optical potential for a $\Delta(1232)$ resonance in the final state ($U^\Delta_{opt}$) within the impulse approximation. We find that $U^\Delta_{opt}$ is more negative than $U_{opt}^{QE}$ with $U^\Delta_{opt}\approx$1.5~$U_{opt}^{QE}$ for $\bf_{6}^{12}C$.Comment: 15 pages, 11 figures, 2 tables. Version 5 as published in Eur. Phys. Journal C 202

Pion-proton correlation in neutrino interactions on nuclei

In neutrino-nucleus interactions, a proton produced with a correlated pion might exhibit a left-right asymmetry relative to the lepton scattering plane even when the pion is absorbed. Absent in other proton production mechanisms, such an asymmetry measured in charged-current pionless production could reveal the details of the absorbed-pion events that are otherwise inaccessible. In this study, we demonstrate the idea of using final-state proton left-right asymmetries to quantify the absorbed-pion event fraction and underlying kinematics. This technique might provide critical information that helps constrain all underlying channels in neutrino-nucleus interactions in the GeV regime.Comment: 7 pages, 4 figure

Accelerating Machine Learning Inference with GPUs in ProtoDUNE Data Processing

We study the performance of a cloud-based GPU-accelerated inference server to speed up event reconstruction in neutrino data batch jobs. Using detector data from the ProtoDUNE experiment and employing the standard DUNE grid job submission tools, we attempt to reprocess the data by running several thousand concurrent grid jobs, a rate we expect to be typical of current and future neutrino physics experiments. We process most of the dataset with the GPU version of our processing algorithm and the remainder with the CPU version for timing comparisons. We find that a 100-GPU cloud-based server is able to easily meet the processing demand, and that using the GPU version of the event processing algorithm is two times faster than processing these data with the CPU version when comparing to the newest CPUs in our sample. The amount of data transferred to the inference server during the GPU runs can overwhelm even the highest-bandwidth network switches, however, unless care is taken to observe network facility limits or otherwise distribute the jobs to multiple sites. We discuss the lessons learned from this processing campaign and several avenues for future improvements.Comment: 13 pages, 9 figures, matches accepted versio

Neutron detection and application with a novel 3D-projection scintillator tracker in the future long-baseline neutrino oscillation experiments

Neutrino oscillation experiments require a precise measurement of the neutrino energy. However, the kinematic detection of the final-state neutron in the neutrino interaction is missing in current neutrino oscillation experiments. The missing neutron kinematic detection results in a smaller detected neutrino energy than the true neutrino energy. A novel 3D-projection scintillator tracker, which consists of roughly ten million active cubes covered with an optical reflector, is capable of measuring the neutron kinetic energy and direction on an event-by-event basis using the time-of-flight technique thanks to the fast timing, fine granularity, and high light yield. The ν¯μ interactions tend to produce neutrons in the final state. By measuring the neutron kinetic energy, the ν¯μ energy can be reconstructed better, allowing a tighter incoming neutrino flux constraint. This article shows the detector's ability to reconstruct neutron kinetic energy and the ν¯μ flux constraint achieved by selecting the charged-current interactions without mesons or protons in the final state.ISSN:1550-7998ISSN:0556-2821ISSN:1550-236

DUNE Offline Computing Conceptual Design Report

This document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment

DUNE Offline Computing Conceptual Design Report

This document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment