Alvarez, V., Herrero-Bosch, V., Esteve, R., Laing, A., Rodriguez, J., Querol, M., et al. (2019). The electronics of the energy plane of the NEXT-White detector. Nucl. Instrum. Methods Phys. Res. A, 917, 68–76.
Abstract: This paper describes the electronics of NEXT-White (NEW) detector PMT plane, a high pressure xenon TPC with electroluminescent amplification (HPXe-EL) currently operating at the Laboratorio Subterraneo de Canfranc (LSC) in Huesca, Spain. In NEXT-White the energy of the event is measured by a plane of photomultipliers (PMTs) located behind a transparent cathode. The PMTs are Hamamatsu R11410-10 chosen due to their low radioactivity. The electronics have been designed and implemented to fulfill strict requirements: an overall energy resolution below 1% and a radiopurity budget of 20 mBq unit(-1) in the chain of Bi-214. All the components and materials have been carefully screened to assure a low radioactivity level and at the same time meet the required front-end electronics specifications. In order to reduce low frequency noise effects and enhance detector safety a grounded cathode connection has been used for the PMTs. This implies an AC-coupled readout and baseline variations in the PMT signals. A detailed description of the electronics and a novel approach based on a digital baseline restoration to obtain a linear response and handle AC coupling effects is presented. The final PMT channel design has been characterized with linearity better than 0.4% and noise below 0.4 mV.
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Bayes, R., Laing, A., Soler, F. J. P., Cervera-Villanueva, A., Gomez-Cadenas, J. J., Hernandez, P., et al. (2012). Golden channel at a neutrino factory revisited: Improved sensitivities from a magnetized iron neutrino detector. Phys. Rev. D, 86(9), 093015–27pp.
Abstract: This paper describes the performance and sensitivity to neutrino mixing parameters of a Magnetised Iron Neutrino Detector at a Neutrino Factory with a neutrino beam created from the decay of 10 GeV muons. Specifically, it is concerned with the ability of such a detector to detect muons of the opposite sign to those stored (wrong-sign muons) while suppressing contamination of the signal from the interactions of other neutrino species in the beam. A new, more realistic simulation and analysis, which improves the efficiency of this detector at low energies, has been developed using the GENIE neutrino event generator and the GEANT4 simulation toolkit. Low-energy neutrino events down to 1 GeV were selected, while reducing backgrounds to the 10(-4) level. Signal efficiency plateaus of similar to 60% for nu(mu) and similar to 70% for (nu) over bar (mu) events were achieved starting at similar to 5 GeV. Contamination from the nu(mu) -> nu(tau) oscillation channel was studied for the first time and was found to be at the level between 1% and 4%. Full response matrices are supplied for all the signal and background channels from 1 GeV to 10 GeV. The sensitivity of an experiment involving a Magnetised Iron Neutrino Detector detector of 100 ktons at 2000 km from the Neutrino Factory is calculated for the case of sin(2)2 theta(13) similar to 10(-1). For this value of theta(13), the accuracy in the measurement of the CP-violating phase is estimated to be Delta delta(CP) similar to 3 degrees-5 degrees, depending on the value of delta(CP), the CP coverage at 5 sigma is 85% and the mass hierarchy would be determined with better than 5 sigma level for all values of delta(CP).
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NEXT Collaboration(Trindade, A. M. F. et al), Alvarez, V., Benlloch-Rodriguez, J. M., Botas, A., Carcel, S., Carrion, J. V., et al. (2018). Study of the loss of xenon scintillation in xenon-trimethylamine mixtures. Nucl. Instrum. Methods Phys. Res. A, 905, 22–28.
Abstract: This work investigates the capability of TMA ((CH3)(3)N) molecules to shift the wavelength of Xe VUV emission (160-188 nm) to a longer, more manageable, wavelength (260-350 nm). Light emitted from a Xe lamp was passed through a gas chamber filled with Xe-TMA mixtures at 800 Torr and detected with a photomultiplier tube. Using bandpass filters in the proper transmission ranges, no reemitted light was observed experimentally. Considering the detection limit of the experimental system, if reemission by TMA molecules occurs, it is below 0.3% of the scintillation absorbed in the 160-188 nm range. An absorption coefficient value for xenon VUV light by TMA of 0.43 +/- 0.03 cm(-1) Torr(-1) was also obtained. These results can be especially important for experiments considering TMA as a molecular additive to Xe in large volume optical time projection chambers.
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NEXT Collaboration(Azevedo, C. D. R. et al), Gomez-Cadenas, J. J., Alvarez, V., Benlloch-Rodriguez, J. M., Botas, A., Carcel, S., et al. (2018). Microscopic simulation of xenon-based optical TPCs in the presence of molecular additives. Nucl. Instrum. Methods Phys. Res. A, 877, 157–172.
Abstract: We introduce a simulation framework for the transport of high and low energy electrons in xenon-based optical time projection chambers (OTPCs). The simulation relies on elementary cross sections (electron-atom and electron-molecule) and incorporates, in order to compute the gas scintillation, the reaction/quenching rates (atom-atom and atom-molecule) of the first 41 excited states of xenon and the relevant associated excimers, together with their radiative cascade. The results compare positively with observations made in pure xenon and its mixtures with CO2 and CF4 in a range of pressures from 0.1 to 10 bar. This work sheds some light on the elementary processes responsible for the primary and secondary xenon-scintillation mechanisms in the presence of additives, that are of interest to the OTPC technology.
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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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