16 research outputs found

    First measurement of one pion production in charged current neutrino and antineutrino events on argon

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    This thesis presents a work done in the context of the Fermilab Neutrino Intensity Frontier. Total cross section and differential cross section measurements for one pion production in charged current (CC) neutrino and antineutrino on argon are presented. These measurements are performed using the Argon Neutrino Test (ArgoNeuT) detector exposed to the Fermilab Neutrino From The Main Injector (NuMI) beam operating in the low energy antineutrino mode. The results are reported in terms of outgoing muon angle and momentum, outgoing pion angle and angle between outgoing pion and muon at a mean neutrino energy of 9.6 GeV (neutrinos) and 3.6 GeV (antineutrinos), setting a reconstruction limit on the pion momentum of 100 MeV/c. The total cross sections, averaged over a flux, are found to be 8.31 +/- 0.91 (stat) +/- 1.03 (syst) x 10^{-38} cm^{2} per argon nuclei and 2.54 +/- 0.43 (stat) -0.45+0.50 (syst) x 10^{-37} cm^{2} per argon nuclei for antineutrino and neutrino respectively. This is the first time the CC one pion production cross section is measured on argon nuclei

    DUNE Offline Computing Conceptual Design Report

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    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

    No full text
    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

    Highly-parallelized simulation of a pixelated LArTPC on a GPU

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    The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10310^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype