Navegando IF - Instituto de Física por Autor "Adames, Márcio Rostirolla"
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ItemDesign, construction and operation of the ProtoDUNE-SP Liquid Argon TPC(2022) Abud, Adam Abed; Abi, Babaki; Acciarri, Roberto; Acero Ortega, Mario A.; Adames, Márcio Rostirolla; Adamov, George; Adams, David; Adinolfi, Marco; Gomes, Ricardo AvelinoThe ProtoDUNE-SP detector is a single-phase liquid argon time projection chamber (LArTPC) that was constructed and operated in the CERN North Area at the end of the H4 beamline. This detector is a prototype for the first far detector module of the Deep Underground Neutrino Experiment (DUNE), which will be constructed at the Sandford Underground Research Facility (SURF) in Lead, South Dakota, U.S.A. The ProtoDUNE-SP detector incorporates full-size components as designed for DUNE and has an active volume of 7 × 6 × 7.2 m3 . The H4 beam delivers incident particles with well-measured momenta and high-purity particle identification. ProtoDUNE-SP’s successful operation between 2018 and 2020 demonstrates the effectiveness of the single-phase far detector design. This paper describes the design, construction, assembly and operation of the detector components. ItemScintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC(2022) Abud, Adam Abed; Abi, Babak; Acciarri, Roberto; Acero Ortega, Mario A.; Adames, Márcio Rostirolla; Adamov, George; Adamowski, M.; Adams, David; Adinolfi, Marco; Aduszkiewicz, Antoni; Gomes, Ricardo AvelinoDUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6×6×6 m3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019–2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties. ItemSearching for solar KDAR with DUNE(2021) Abud, Adam Abed; Abi, Babak; Acero Ortega, Mario A.; Adames, Márcio Rostirolla; Adamov, George; Adams, David; Adinolfi, Marco; Aduszkiewicz, Antoni; Gomes, Ricardo AvelinoThe observation of 236 MeV muon neutrinos from kaon-decay-at-rest (KDAR) originating in the core of the Sun would provide a unique signature of dark matter annihila tion. Since excellent angle and energy reconstruction are necessary to detect this monoener getic, directional neutrino flux, DUNE with its vast volume and reconstruction capabilities, is a promising candidate for a KDAR neutrino search. In this work, we evaluate the proposed KDAR neutrino search strategies by realistically modeling both neutrino-nucleus interactions and the response of DUNE. We find that, although reconstruction of the neutrino energy and direction is difficult with current techniques in the relevant energy range, the superb energy resolution, angular resolution, and particle identification offered by DUNE can still permit great signal/background discrimination. Moreover, there are non-standard scenarios in which searches at DUNE for KDAR in the Sun can probe dark matter interactions. ItemSeparation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network(2022) Abud, Adam Abed; Abi, Babak; Acciarri, Roberto; Acero Ortega, Mario A.; Adames, Márcio Rostirolla; Adamov, George; Adamowski, M.; Adams, David; Adinolfi, Marco; Aduszkiewicz, Antoni; Gomes, Ricardo AvelinoLiquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neu trino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article pro poses an algorithm based on a convolutional neural network to perform the classification of energy deposits and recon structed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experi mental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation.