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Double Chooz collaboration(de Kerret, H. et al), & Novella, P. (2022). The Double Chooz antineutrino detectors. Eur. Phys. J. C, 82(9), 804–34pp.
Abstract: This article describes the setup and performance of the near and far detectors in the Double Chooz experiment. The electron antineutrinos of the Chooz nuclear power plant were measured in two identically designed detectors with different average baselines of about 400 m and 1050 m from the two reactor cores. Over many years of data taking the neutrino signals were extracted from interactions in the detectors with the goal of measuring a fundamental parameter in the context of neutrino oscillation, the mixing angle 013. The central part of the Double Chooz detectors was a main detector comprising four cylindrical volumes filled with organic liquids. From the inside towards the outside there were volumes con- taining gadolinium-loaded scintillator, gadolinium-free scintillator, a buffer oil and, optically separated, another liquid scintillator acting as veto system. Above this main detector an additional outer veto system using plastic scintillator strips was installed. The technologies developed in Double Chooz were inspiration for several other antineutrino detectors in the field. The detector design allowed implementation of efficient background rejection techniques including use of pulse shape information provided by the data acquisition system. The Double Chooz detectors featured remarkable stability, in particular for the detected photons, as well as high radiopurity of the detector components.
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DUNE Collaboration(Abud, A. A. et al), Antonova, M., Barenboim, G., Cervera-Villanueva, A., De Romeri, V., Fernandez Menendez, P., et al. (2022). Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network. Eur. Phys. J. C, 82(10), 903–19pp.
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.
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DUNE Collaboration(Abi, B. et al), Antonova, M., Barenboim, G., Cervera-Villanueva, A., De Romeri, V., Garcia-Peris, M. A., et al. (2020). Long-baseline neutrino oscillation physics potential of the DUNE experiment. Eur. Phys. J. C, 80(10), 978–34pp.
Abstract: The sensitivity of the Deep Underground Neutrino Experiment (DUNE) to neutrino oscillation is determined, based on a full simulation, reconstruction, and event selection of the far detector and a full simulation and parameterized analysis of the near detector. Detailed uncertainties due to the flux prediction, neutrino interaction model, and detector effects are included. DUNE will resolve the neutrino mass ordering to a precision of 5 sigma, for all delta CP values, after 2 years of running with the nominal detector design and beam configuration. It has the potential to observe charge-parity violation in the neutrino sector to a precision of 3 sigma (5 sigma) after an exposure of 5 (10) years, for 50% of all delta CP values. It will also make precise measurements of other parameters governing long-baseline neutrino oscillation, and after an exposure of 15 years will achieve a similar sensitivity to sin22 theta 13 to current reactor experiments.
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NEXT Collaboration(Renner, J. et al), Benlloch-Rodriguez, J., Botas, A., Ferrario, P., Gomez-Cadenas, J. J., Alvarez, V., et al. (2017). Background rejection in NEXT using deep neural networks. J. Instrum., 12, T01004–21pp.
Abstract: We investigate the potential of using deep learning techniques to reject background events in searches for neutrinoless double beta decay with high pressure xenon time projection chambers capable of detailed track reconstruction. The differences in the topological signatures of background and signal events can be learned by deep neural networks via training over many thousands of events. These networks can then be used to classify further events as signal or background, providing an additional background rejection factor at an acceptable loss of efficiency. The networks trained in this study performed better than previous methods developed based on the use of the same topological signatures by a factor of 1.2 to 1.6, and there is potential for further improvement.
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DUNE Collaboration(Abud, A. A. et al), Antonova, M., Barenboim, G., Cervera-Villanueva, A., De Romeri, V., Fernandez Menendez, P., et al. (2022). Design, construction and operation of the ProtoDUNE-SP Liquid Argon TPC. J. Instrum., 17(1), P01005–111pp.
Abstract: The 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 x 6 x 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.
Keywords: Noble liquid detectors (scintillation, ionization, double-phase); Photon detectors for UV; visible and IR photons (solid-state) (PIN diodes, APDs, Si-PMTs, G-APDs, CCDs, EBCCDs, EMCCDs, CMOS imagers, etc); Scintillators; scintillation and light emission processes (solid, gas and liquid scintillators); Time projection Chambers (TPC)
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Double Chooz collaboration(Abrahao, T. et al), & Novella, P. (2018). Novel event classification based on spectral analysis of scintillation waveforms in Double Chooz. J. Instrum., 13, P01031–26pp.
Abstract: Liquid scintillators are a common choice for neutrino physics experiments, but their capabilities to perform background rejection by scintillation pulse shape discrimination is generally limited in large detectors. This paper describes a novel approach for a pulse shape based event classification developed in the context of the Double Chooz reactor antineutrino experiment. Unlike previous implementations, this method uses the Fourier power spectra of the scintillation pulse shapes to obtain event-wise information. A classification variable built from spectral information was able to achieve an unprecedented performance, despite the lack of optimization at the detector design level. Several examples of event classification are provided, ranging from differentiation between the detector volumes and an efficient rejection of instrumental light noise, to some sensitivity to the particle type, such as stopping muons, ortho-positronium formation, alpha particles as well as electrons and positrons. In combination with other techniques the method is expected to allow for a versatile and more efficient background rejection in the future, especially if detector optimization is taken into account at the design level.
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NEXT Collaboration(Mistry, K. et al), Carcel, S., Lopez-March, N., Martin-Albo, J., Novella, P., Querol, M., et al. (2024). Design, characterization and installation of the NEXT-100 cathode and electroluminescence regions. J. Instrum., 19(2), P02007–36pp.
Abstract: NEXT -100 is currently being constructed at the Laboratorio Subterraneo de Canfranc in the Spanish Pyrenees and will search for neutrinoless double beta decay using a high-pressure gaseous time projection chamber (TPC) with 100 kg of xenon. Charge amplification is carried out via electroluminescence (EL) which is the process of accelerating electrons in a high electric field region causing secondary scintillation of the medium proportional to the initial charge. The NEXT -100 EL and cathode regions are made from tensioned hexagonal meshes of 1 m diameter. This paper describes the design, characterization, and installation of these parts for NEXT -100. Simulations of the electric field are performed to model the drift and amplification of ionization electrons produced in the detector under various EL region alignments and rotations. Measurements of the electrostatic breakdown voltage in air characterize performance under high voltage conditions and identify breakdown points. The electrostatic deflection of the mesh is quantified and fit to a first -pr inciples mechanical model. Measurements were performed with both a standalone test EL region and with the NEXT-100 EL region before its installation in the detector. Finally, we describe the parts as installed in NEXT-100, following their deployment in Summer 2023.
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NEXT Collaboration(Haefner, J. et al), Benlloch-Rodriguez, J. M., Carcel, S., Carrion, J. V., Martin-Albo, J., Martinez-Vara, M., et al. (2023). Reflectance and fluorescence characteristics of PTFE coated with TPB at visible, UV, and VUV as a function of thickness. J. Instrum., 18(3), P03016–21pp.
Abstract: Polytetrafluoroethylene (PTFE) is an excellent diffuse reflector widely used in light collection systems for particle physics experiments. In noble element systems, it is often coated with tetraphenyl butadiene (TPB) to allow detection of vacuum ultraviolet scintillation light. In this work this dependence is investigated for PTFE coated with TPB in air for light of wavelengths of 200 nm, 260 nm, and 450 nm. The results show that TPB-coated PTFE has a reflectance of approximately 92% for thicknesses ranging from 5 mm to 10 mm at 450 nm, with negligible variation as a function of thickness within this range. A cross-check of these results using an argon chamber supports the conclusion that the change in thickness from 5 mm to 10 mm does not affect significantly the light response at 128 nm. Our results indicate that pieces of TPB-coated PTFE thinner than the typical 10 mm can be used in particle physics detectors without compromising the light signal.
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NEXT Collaboration(Woodruff, K. et al), Alvarez, V., Benlloch-Rodriguez, J. M., Carcel, S., Carrion, J. V., Diaz, J., et al. (2020). Radio frequency and DC high voltage breakdown of high pressure helium, argon, and xenon. J. Instrum., 15(4), P04022–15pp.
Abstract: Motivated by the possibility of guiding daughter ions from double beta decay events to single-ion sensors for barium tagging, the NEXT collaboration is developing a program of R&D to test radio frequency (RF) carpets for ion transport in high pressure xenon gas. This would require carpet functionality in regimes at higher pressures than have been previously reported, implying correspondingly larger electrode voltages than in existing systems. This mode of operation appears plausible for contemporary RF-carpet geometries due to the higher predicted breakdown strength of high pressure xenon relative to low pressure helium, the working medium in most existing RF carpet devices. In this paper we present the first measurements of the high voltage dielectric strength of xenon gas at high pressure and at the relevant RF frequencies for ion transport (in the 10MHz range), as well as new DC and RF measurements of the dielectric strengths of high pressure argon and helium gases at small gap sizes. We find breakdown voltages that are compatible with stable RF carpet operation given the gas, pressure, voltage, materials and geometry of interest.
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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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