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Author DUNE Collaboration (Abud, A.A. et al); Amedo, P.; Antonova, M.; Barenboim, G.; Cervera-Villanueva, A.; De Romeri, V.; Fernandez Menendez, P.; Garcia-Peris, M.A.; Martin-Albo, J.; Martinez-Mirave, P.; Mena, O.; Molina Bueno, L.; Novella, P.; Pompa, F.; Rocabado Rocha, J.L.; Sorel, M.; Ternes, C.A.; Tortola, M.; Valle, J.W.F.
Title Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora Type Journal Article
Year 2023 Publication European Physical Journal C Abbreviated Journal Eur. Phys. J. C
Volume 83 Issue 7 Pages 618 - 25pp
Keywords
Abstract The Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/c charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1 +/- 0.6% and 84.1 +/- 0.6%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation.
Address (up) [Isenhower, L.] Abilene Christian Univ, Abilene, TX 79601 USA, Email: leigh.howard.whitehead@cern.ch
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1434-6044 ISBN Medium
Area Expedition Conference
Notes WOS:001061746600005 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5721
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Author DUNE Collaboration (Abud, A.A. et al); Amedo, P.; Antonova, M.; Barenboim, G.; Cervera-Villanueva, A.; De Romeri, V.; Garcia-Peris, M.A.; Martin-Albo, J.; Martinez-Mirave, P.; Mena, O.; Molina Bueno, L.; Novella, P.; Pompa, F.; Rocabado Rocha, J.L.; Sorel, M.; Tortola, M.; Tuzi, M.; Valle, J.W.F.; Yahlali, N.
Title Highly-parallelized simulation of a pixelated LArTPC on a GPU Type Journal Article
Year 2023 Publication Journal of Instrumentation Abbreviated Journal J. Instrum.
Volume 18 Issue 4 Pages P04034 - 35pp
Keywords Detector modelling and simulations II (electric fields, charge transport, multiplication, and induction, pulse formation, electron emission, etc); Simulation methods and programs; Nobleliquid detectors (scintillation, ionization, double-phase); Time projection Chambers (TPC)
Abstract 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 103 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.
Address (up) [Isenhower, L.] Abilene Christian Univ, Abilene, TX 79601 USA, Email: roberto@lbl.gov
Corporate Author Thesis
Publisher IOP Publishing Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1748-0221 ISBN Medium
Area Expedition Conference
Notes WOS:000986658100009 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5551
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Author DUNE Collaboration (Abud, A.A. et al); Amedo, P.; Antonova, M.; Barenboim, G.; Cervera-Villanueva, A.; De Romeri, V.; Garcia-Peris, M.A.; Martin-Albo, J.; Martinez-Mirave, P.; Mena, O.; Molina Bueno, L.; Novella, P.; Pompa, F.; Rocabado Rocha, J.L.; Sorel, M.; Tortola, M.; Valle, J.W.F.
Title Identification and reconstruction of low-energy electrons in the ProtoDUNE-SP detector Type Journal Article
Year 2023 Publication Physical Review D Abbreviated Journal Phys. Rev. D
Volume 107 Issue 9 Pages 092012 - 22pp
Keywords
Abstract Measurements of electrons from ?e interactions are crucial for the Deep Underground Neutrino Experiment (DUNE) neutrino oscillation program, as well as searches for physics beyond the standard model, supernova neutrino detection, and solar neutrino measurements. This article describes the selection and reconstruction of low-energy (Michel) electrons in the ProtoDUNE-SP detector. ProtoDUNE-SP is one of the prototypes for the DUNE far detector, built and operated at CERN as a charged particle test beam experiment. A sample of low-energy electrons produced by the decay of cosmic muons is selected with a purity of 95%. This sample is used to calibrate the low-energy electron energy scale with two techniques. An electron energy calibration based on a cosmic ray muon sample uses calibration constants derived from measured and simulated cosmic ray muon events. Another calibration technique makes use of the theoretically well-understood Michel electron energy spectrum to convert reconstructed charge to electron energy. In addition, the effects of detector response to low-energy electron energy scale and its resolution including readout electronics threshold effects are quantified. Finally, the relation between the theoretical and reconstructed low-energy electron energy spectra is derived, and the energy resolution is characterized. The low-energy electron selection presented here accounts for about 75% of the total electron deposited energy. After the addition of lost energy using a Monte Carlo simulation, the energy resolution improves from about 40% to 25% at 50 MeV. These results are used to validate the expected capabilities of the DUNE far detector to reconstruct low-energy electrons.
Address (up) [Isenhower, L.] Abilene Christian Univ, Abilene, TX 79601 USA, Email: zdjurcic@anl.gov;
Corporate Author Thesis
Publisher Amer Physical Soc Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2470-0010 ISBN Medium
Area Expedition Conference
Notes WOS:001010953400003 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5588
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Author DUNE Collaboration (Abud, A.A. et al); Antonova, M.; Barenboim, G.; Cervera-Villanueva, A.; De Romeri, V.; Fernandez Menendez, P.; Garcia-Peris, M.A.; Martin-Albo, J.; Martinez-Mirave, P.; Mena, O.; Molina Bueno, L.; Novella, P.; Pompa, F.; Sorel, M.; Ternes, C.A.; Tortola, M.; Valle, J.W.F.
Title Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network Type Journal Article
Year 2022 Publication European Physical Journal C Abbreviated Journal Eur. Phys. J. C
Volume 82 Issue 10 Pages 903 - 19pp
Keywords
Abstract Liquid 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 neutrino 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 proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental 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.
Address (up) [Isenhower, L.] Abilenexs Christian Univ, Abilene, TX 79601 USA, Email: tjyang@fnal.gov
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1434-6044 ISBN Medium
Area Expedition Conference
Notes WOS:000866503200001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5386
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Author Cervera-Villanueva, A.; Laing, A.; Martin-Albo, J.; Soler, F.J.P.
Title Performance of the MIND detector at a Neutrino Factory using realistic muon reconstruction Type Journal Article
Year 2010 Publication Nuclear Instruments & Methods in Physics Research A Abbreviated Journal Nucl. Instrum. Methods Phys. Res. A
Volume 624 Issue 3 Pages 601-614
Keywords Neutrino Factory; Detector; Neutrino oscillation
Abstract A Neutrino Factory producing an intense beam composed of v(e)((v) over bar (e)) and (v) over bar (mu)(v(mu)) from muon decays has been shown to have the greatest sensitivity to the two currently unmeasured neutrino mixing parameters theta(13) and delta(CP) Using the wrong-sign muon signal to measure v(e)-> v(mu)((v) over bar (e) ->(v) over bar (mu)) oscillations in a 50kt Magnetised Iron Neutrino Detector (MIND) sensitivity to delta(CP) could be maintained down to small values of theta(13) However the detector efficiencies used in these previous studies were calculated assuming perfect pattern recognition In this paper MIND is reassessed taking into account for the first time a realistic pattern recognition for the muon candidate Reoptimisation of the analysis utilises a combination of methods including a multivariate analysis similar to the one used in MINOS to maintain high efficiency while suppressing backgrounds ensuring that the signal selection efficiency and the background levels are comparable or better than the ones in previous analyses As a result MIND remains the most sensitive future facility for the discovery of CP violation from neutrino oscillations.
Address (up) [Laing, A.; Soler, F. J. P.] Univ Glasgow, Sch Phys & Astron, Glasgow, Lanark, Scotland
Corporate Author Thesis
Publisher Elsevier Science Bv Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0168-9002 ISBN Medium
Area Expedition Conference
Notes ISI:000285370600008 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ elepoucu @ Serial 309
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