|
|
DUNE Collaboration(Abi, B. et al), Antonova, M., Barenboim, G., Cervera-Villanueva, A., De Romeri, V., Fernandez Menendez, P., et al. (2021). Supernova neutrino burst detection with the Deep Underground Neutrino Experiment. Eur. Phys. J. C, 81(5), 423–26pp.
Abstract: The Deep Underground Neutrino Experiment (DUNE), a 40-kton underground liquid argon time projection chamber experiment, will be sensitive to the electron-neutrino flavor component of the burst of neutrinos expected from the next Galactic core-collapse supernova. Such an observation will bring unique insight into the astrophysics of core collapse as well as into the properties of neutrinos. The general capabilities of DUNE for neutrino detection in the relevant few- to few-tens-of-MeV neutrino energy range will be described. As an example, DUNE's ability to constrain the nu(e) spectral parameters of the neutrino burst will be considered.
|
|
|
|
NEXT Collaboration(Haefner, J. et al), Carcel, S., Carrion, J. V., Lopez-March, N., Martin-Albo, J., Muñoz Vidal, J., et al. (2024). Demonstration of event position reconstruction based on diffusion in the NEXT-white detector. Eur. Phys. J. C, 84(5), 518–13pp.
Abstract: Noble element time projection chambers are a leading technology for rare event detection in physics, such as for dark matter and neutrinoless double beta decay searches. Time projection chambers typically assign event position in the drift direction using the relative timing of prompt scintillation and delayed charge collection signals, allowing for reconstruction of an absolute position in the drift direction. In this paper, alternate methods for assigning event drift distance via quantification of electron diffusion in a pure high pressure xenon gas time projection chamber are explored. Data from the NEXT-White detector demonstrate the ability to achieve good position assignment accuracy for both high- and low-energy events. Using point-like energy deposits from Kr-83m calibration electron captures (E similar to 45 keV), the position of origin of low-energy events is determined to 2 cm precision with bias <1 mm. A convolutional neural network approach is then used to quantify diffusion for longer tracks (E >= 1.5 MeV), from radiogenic electrons, yielding a precision of 3 cm on the event barycenter. The precision achieved with these methods indicates the feasibility energy calibrations of better than 1% FWHM at Q(beta beta) in pure xenon, as well as the potential for event fiducialization in large future detectors using an alternate method that does not rely on primary scintillation.
|
|
|
|
Cervera-Villanueva, A., Laing, A., Martin-Albo, J., & Soler, F. J. P. (2010). Performance of the MIND detector at a Neutrino Factory using realistic muon reconstruction. Nucl. Instrum. Methods Phys. Res. A, 624(3), 601–614.
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.
|
|
|
|
DUNE Collaboration(Abud, A. A. et al), Antonova, M., Barenboim, G., Cervera-Villanueva, A., De Romeri, V., Fernandez Menendez, P., et al. (2022). Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC. Eur. Phys. J. C, 82(7), 618–29pp.
Abstract: DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6 x 6 x 6 m(3) 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 7m 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.
|
|
|
|
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.
|
|
