Andreev, Y. M. et al, Molina Bueno, L., & Tuzi, M. (2023). Measurement of the intrinsic hadronic contamination in the NA64-e high-purity e+/e- beam at CERN. Nucl. Instrum. Methods Phys. Res. A, 1057, 168776–8pp.
Abstract: We present the measurement of the intrinsic hadronic contamination at the CERN SPS H4 beamline configured to transport electrons and positrons at 100 GeV/c. The analysis, performed using data collected by the NA64-e experiment in 2022, is based on calorimetric measurements, exploiting the different interaction mechanisms of electrons and hadrons in the NA64 detector. We determined the contamination by comparing the results obtained using the nominal electron/positron beamline configuration with those from a dedicated setup, in which only hadrons impinged on the detector. We also obtained an estimate of the relative protons, antiprotons and pions yield by exploiting the different absorption probabilities of these particles in matter. We cross-checked our results with a dedicated Monte Carlo simulation for the hadron production at the primary T2 target, finding a good agreement with the experimental measurements.
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DUNE Collaboration(Abi, B. et al), Antonova, M., Barenboim, G., Cervera-Villanueva, A., De Romeri, V., Fernandez Menendez, P., et al. (2021). Searching for solar KDAR with DUNE. J. Cosmol. Astropart. Phys., 10(10), 065–28pp.
Abstract: The 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 annihilation. Since excellent angle and energy reconstruction are necessary to detect this monoenergetic, 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.
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DUNE Collaboration(Abud, A. A. et al), Amedo, P., Antonova, M., Barenboim, G., Benitez Montiel, C., Cervera-Villanueva, A., et al. (2023). Impact of cross-section uncertainties on supernova neutrino spectral parameter fitting in the Deep Underground Neutrino Experiment. Phys. Rev. D, 107(11), 112012–25pp.
Abstract: A primary goal of the upcoming Deep Underground Neutrino Experiment (DUNE) is to measure the Oo10 thorn MeV neutrinos produced by a Galactic core-collapse supernova if one should occur during the lifetime of the experiment. The liquid-argon-based detectors planned for DUNE are expected to be uniquely sensitive to the & nu;e component of the supernova flux, enabling a wide variety of physics and astrophysics measurements. A key requirement for a correct interpretation of these measurements is a good understanding of the energy-dependent total cross section & sigma;oE & nu; thorn for charged-current & nu;e absorption on argon. In the context of a simulated extraction of supernova & nu;e spectral parameters from a toy analysis, we investigate the impact of & sigma;oE & nu; thorn modeling uncertainties on DUNE's supernova neutrino physics sensitivity for the first time. We find that the currently large theoretical uncertainties on & sigma;oE & nu; thorn must be substantially reduced before the & nu;e flux parameters can be extracted reliably; in the absence of external constraints, a measurement of the integrated neutrino luminosity with less than 10% bias with DUNE requires & sigma;oE & nu; thorn to be known to about 5%. The neutrino spectral shape parameters can be known to better than 10% for a 20% uncertainty on the cross-section scale, although they will be sensitive to uncertainties on the shape of & sigma;oE & nu; thorn . A direct measurement of low-energy & nu;e-argon scattering would be invaluable for improving the theoretical precision to the needed level.
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DUNE Collaboration(Abud, A. A. et al), Amedo, P., Antonova, M., Barenboim, G., Cervera-Villanueva, A., De Romeri, V., et al. (2023). Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora. Eur. Phys. J. C, 83(7), 618–25pp.
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.
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DUNE Collaboration(Abud, A. A. et al), Amedo, P., Antonova, M., Barenboim, G., Cervera-Villanueva, A., De Romeri, V., et al. (2023). Highly-parallelized simulation of a pixelated LArTPC on a GPU. J. Instrum., 18(4), P04034–35pp.
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.
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