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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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NEXT Collaboration(Cebrian, S. et al), Perez, J., Alvarez, V., Benlloch-Rodriguez, J., Botas, A., Carcel, S., et al. (2017). Radiopurity assessment of the energy readout for the NEXT double beta decay experiment. J. Instrum., 12, T08003–20pp.
Abstract: The “Neutrino Experiment with a Xenon Time-Projection Chamber” (NEXT) experiment intends to investigate the neutrinoless double beta decay of Xe-136, and therefore requires a severe suppression of potential backgrounds. An extensive material screening and selection process was undertaken to quantify the radioactivity of the materials used in the experiment. Separate energy and tracking readout planes using different sensors allow us to combine the measurement of the topological signature of the event for background discrimination with the energy resolution optimization. The design of radiopure readout planes, in direct contact with the gas detector medium, was especially challenging since the required components typically have activities too large for experiments demanding ultra-low background conditions. After studying the tracking plane, here the radiopurity control of the energy plane is presented, mainly based on gamma-ray spectroscopy using ultra-low background germanium detectors at the Laboratorio Subterraneo de Canfranc (Spain). All the available units of the selected model of photomultiplier have been screened together with most of the components for the bases, enclosures and windows. According to these results for the activity of the relevant radioisotopes, the selected components of the energy plane would give a contribution to the overall background level in the region of interest of at most 2.4 x 10(-4) counts keV(-1) kg(-1) y(-1), satisfying the sensitivity requirements of the NEXT experiment.
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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(Simon, A. et al), Felkai, R., Martinez-Lema, G., Sorel, M., Gomez-Cadenas, J. J., Alvarez, V., et al. (2018). Electron drift properties in high pressure gaseous xenon. J. Instrum., 13, P07013–23pp.
Abstract: Gaseous time projection chambers (TPC) are a very attractive detector technology for particle tracking. Characterization of both drift velocity and diffusion is of great importance to correctly assess their tracking capabilities. NEXT-White is a High Pressure Xenon gas TPC with electroluminescent amplification, a 1:2 scale model of the future NEXT-100 detector, which will be dedicated to neutrinoless double beta decay searches. NEXT-White has been operating at Canfranc Underground Laboratory (LSC) since December 2016. The drift parameters have been measured using Kr-83(m) for a range of reduced drift fields at two different pressure regimes, namely 7.2 bar and 9.1 bar. The results have been compared with Magboltz simulations. Agreement at the 5% level or better has been found for drift velocity, longitudinal diffusion and transverse diffusion.
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