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NEXT Collaboration(Renner, J. et al), Martinez-Lema, G., Alvarez, V., Benlloch-Rodriguez, J. M., Botas, A., Carcel, S., et al. (2018). Initial results on energy resolution of the NEXT-White detector. J. Instrum., 13, P10020–14pp.
Abstract: One of the major goals of the NEXT-White (NEW) detector is to demonstrate the energy resolution that an electroluminescent high pressure xenon TPC can achieve for high energy tracks. For this purpose, energy calibrations with Cs-137 and Th-232 sources have been carried out as a part of the long run taken with the detector during most of 2017. This paper describes the initial results obtained with those calibrations, showing excellent linearity and an energy resolution that extrapolates to approximately 1% FWHM at Q(beta beta).
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NEXT Collaboration(Monrabal, F. et al), Laing, A., Alvarez, V., Benlloch-Rodriguez, J. M., Carcel, S., Carrion, J. V., et al. (2018). The NEXT White (NEW) detector. J. Instrum., 13, P12010–38pp.
Abstract: Conceived to host 5 kg of xenon at a pressure of 15 bar in the fiducial volume, the NEXT-White apparatus is currently the largest high pressure xenon gas TPC using electroluminescent amplification in the world. It is also a 1:2 scale model of the NEXT-100 detector for Xe-136 beta beta 0 nu decay searches, scheduled to start operations in 2019. Both detectors measure the energy of the event using a plane of photomultipliers located behind a transparent cathode. They can also reconstruct the trajectories of charged tracks in the dense gas of the TPC with the help of a plane of silicon photomultipliers located behind the anode. A sophisticated gas system, common to both detectors, allows the high gas purity needed to guarantee a long electron lifetime. NEXT-White has been operating since October 2016 at the Laboratorio Subterraneo de Canfranc (LSC), in Spain. This paper describes the detector and associated infrastructures, as well as the main aspects of its initial operation.
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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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