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Sorel, M. (2014). Expected performance of an ideal liquid argon neutrino detector with enhanced sensitivity to scintillation light. J. Instrum., 9, P10002–25pp.
Abstract: Scintillation light is used in liquid argon (LAr) neutrino detectors to provide a trigger signal, veto information against cosmic rays, and absolute event timing. In this work, we discuss additional opportunities offered by detectors with enhanced sensitivity to scintillation light, that is with light collection efficiencies of about 10(-3). We focus on two key detector performance indicators for neutrino oscillation physics: calorimetric neutrino energy reconstruction and neutrino/antineutrino separation in a non-magnetized detector. Our results are based on detailed simulations, with neutrino interactions modelled according to the GENIE event generator, while the charge and light responses of a large LAr ideal detector are described by the Geant4 and NEST simulation tools. A neutrino energy resolution as good as 3.3% RMS for 4 GeV electron neutrino charged-current interactions can in principle be obtained in a large detector of this type, by using both charge and light information. By exploiting muon capture in argon and scintillation light information to veto muon decay electrons, we also obtain muon neutrino identification efficiencies of about 50%, and muon antineutrino misidentification rates at the few percent level, for few-GeV neutrino interactions that are fully contained. We argue that the construction of large LAr detectors with sufficiently high light collection efficiencies is in principle possible.
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NEXT Collaboration(Simon, A. et al), Gomez-Cadenas, J. J., Alvarez, V., Benlloch-Rodriguez, J. M., Botas, A., Carcel, S., et al. (2017). Application and performance of an ML-EM algorithm in NEXT. J. Instrum., 12, P08009–22pp.
Abstract: The goal of the NEXT experiment is the observation of neutrinoless double beta decay in Xe-136 using a gaseous xenon TPC with electroluminescent amplification and specialized photodetector arrays for calorimetry and tracking. The NEXT Collaboration is exploring a number of reconstruction algorithms to exploit the full potential of the detector. This paper describes one of them: the Maximum Likelihood Expectation Maximization (ML-EM) method, a generic iterative algorithm to find maximum-likelihood estimates of parameters that has been applied to solve many different types of complex inverse problems. In particular, we discuss a bi-dimensional version of the method in which the photosensor signals integrated over time are used to reconstruct a transverse projection of the event. First results show that, when applied to detector simulation data, the algorithm achieves nearly optimal energy resolution (better than 0.5% FWHM at the Q value of 136Xe) for events distributed over the full active volume of the TPC.
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NEXT Collaboration(Serra, L. et al), Sorel, M., Alvarez, V., Carcel, S., Cervera-Villanueva, A., Diaz, J., et al. (2015). An improved measurement of electron-ion recombination in high-pressure xenon gas. J. Instrum., 10, P03025–21pp.
Abstract: We report on results obtained with the NEXT-DEMO prototype of the NEXT-100 high-pressure xenon gas time projection chamber (TPC), filled with pure xenon gas at 10 bar pressure and exposed to an alpha decay calibration source. Compared to our previous measurements with alpha particles, an upgraded detector and improved analysis techniques have been used. We measure event-by-event correlated fluctuations between ionization and scintillation due to electronion recombination in the gas, with correlation coefficients between -0.80 and -0.56 depending on the drift field conditions. By combining the two signals, we obtain a 2.8% FWHM energy resolution for 5.49 MeV alpha particles and a measurement of the optical gain of the electroluminescent TPC. The improved energy resolution also allows us to measure the specific activity of the radon in the gas due to natural impurities. Finally, we measure the average ratio of excited to ionized atoms produced in the xenon gas by alpha particles to be 0.561 +/- 0.045, translating into an average energy to produce a primary scintillation photon of W-ex = (39.2 +/- 3.2) eV.
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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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Renner, J., Cervera-Villanueva, A., Hernando, J. A., Izmaylov, A., Monrabal, F., Muñoz, J., et al. (2015). Improved background rejection in neutrinoless double beta decay experiments using a magnetic field in a high pressure xenon TPC. J. Instrum., 10, P12020–19pp.
Abstract: We demonstrate that the application of an external magnetic field could lead to an improved background rejection in neutrinoless double-beta (0 nu beta beta) decay experiments using a high-pressure xenon (HPXe) TPC. HPXe chambers are capable of imaging electron tracks, a feature that enhances the separation between signal events (the two electrons emitted in the 0 nu beta beta decay of Xe-136) and background events, arising chiefly from single electrons of kinetic energy compatible with the end-point of the 0 nu beta beta decay (Q(beta beta)). Applying an external magnetic field of sufficiently high intensity (in the range of 0.5-1 Tesla for operating pressures in the range of 5-15 atmospheres) causes the electrons to produce helical tracks. Assuming the tracks can be properly reconstructed, the sign of the curvature can be determined at several points along these tracks, and such information can be used to separate signal (0 nu beta beta) events containing two electrons producing a track with two different directions of curvature from background (single-electron) events producing a track that should spiral in a single direction. Due to electron multiple scattering, this strategy is not perfectly efficient on an event-by-event basis, but a statistical estimator can be constructed which can be used to reject background events by one order of magnitude at a moderate cost (about 30%) in signal efficiency. Combining this estimator with the excellent energy resolution and topological signature identification characteristic of the HPXe TPC, it is possible to reach a background rate of less than one count per ton-year of exposure. Such a low background rate is an essential feature of the next generation of 0 nu beta beta experiments, aiming to fully explore the inverse hierarchy of neutrino masses.
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