Abstract: Convolutional neural networks (CNNs) are widely used state-of-the-art computer vision tools that are becoming increasingly popular in high-energy physics. In this paper, we attempt to understand the potential of CNNs for event classification in the NEXT experiment, which will search for neutrinoless double-beta decay in Xe-136. To do so, we demonstrate the usage of CNNs for the identification of electron-positron pair production events, which exhibit a topology similar to that of a neutrinoless double-beta decay event. These events were produced in the NEXT-White high-pressure xenon TPC using 2.6 MeV gamma rays from a Th-228 calibration source. We train a network on Monte Carlo-simulated events and show that, by applying on-the-fly data augmentation, the network can be made robust against differences between simulation and data. The use of CNNs offers significant improvement in signal efficiency and background rejection when compared to previous non-CNN-based analyses.

Abstract: NEXT-100 is an electroluminescent high-pressure xenon gas time projection chamber that will search for the neutrinoless double beta (0v beta beta) decay of Xe-136. The detector possesses two features of great value for 0v beta beta searches: energy resolution better than 1% FWHM at the Q value of Xe-136 and track reconstruction for the discrimination of signal and background events. This combination results in excellent sensitivity, as discussed in this paper. Material-screening measurements and a detailed Monte Carlo detector simulation predict a background rate for NEXT-100 of at most 4 x 10(-4) counts keV(-1) kg(-1) yr(-1). Accordingly, the detector will reach a sensitivity to the 0v beta beta-decay half-life of 2.8 x 10(25) years (90% CL) for an exposure of 100 kg.year, or 6.0 x 10(25) years after a run of 3 effective years.

Abstract: Next-generation neutrinoless double beta decay experiments aim for half-life sensitivities of similar to 10(27) yr, requiring suppressing backgrounds to < 1 count/tonne/yr. For this, any extra background rejection handle, beyond excellent energy resolution and the use of extremely radiopure materials, is of utmost importance. The NEXT experiment exploits differences in the spatial ionization patterns of double beta decay and single-electron events to discriminate signal from background. While the former display two Bragg peak dense ionization regions at the opposite ends of the track, the latter typically have only one such feature. Thus, comparing the energies at the track extremes provides an additional rejection tool. The unique combination of the topology-based background discrimination and excellent energy resolution (1% FWHM at the Q-value of the decay) is the distinguishing feature of NEXT. Previous studies demonstrated a topological background rejection factor of <similar to> 5 when reconstructing electron-positron pairs in the Tl-208 1.6 MeV double escape peak (with Compton events as background), recorded in the NEXT-White demonstrator at the Laboratorio Subterraneo de Canfranc, with 72% signal efficiency. This was recently improved through the use of a deep convolutional neural network to yield a background rejection factor of similar to 10 with 65% signal efficiency. Here, we present a new reconstruction method, based on the Richardson-Lucy deconvolution algorithm, which allows reversing the blurring induced by electron diffusion and electroluminescence light production in the NEXT TPC. The new method yields highly refined 3D images of reconstructed events, and, as a result, significantly improves the topological background discrimination. When applied to real-data 1.6 MeV e(-)e(+) pairs, it leads to a background rejection factor of 27 at 57% signal efficiency.

Abstract: The measurement of the internal Rn-222 activity in the NEXT-White detector during the so-called Run-II period with Xe-136-depleted xenon is discussed in detail, together with its implications for double beta decay searches in NEXT. The activity is measured through the alpha production rate induced in the fiducial volume by Rn-222 and its alpha-emitting progeny. The specific activity is measured to be (38.1 +/- 2.2 (stat.) +/- 5.9 (syst.)) mBq/m(3). Radon-induced electrons have also been characterized from the decay of the Bi-214 daughter ions plating out on the cathode of the time projection chamber. From our studies, we conclude that radon-induced backgrounds are sufficiently low to enable a successful NEXT-100 physics program, as the projected rate contribution should not exceed 0.1 counts/yr in the neutrinoless double beta decay sample.

Abstract: We present the design, data and results from the NEXT prototype for Double Beta and Dark Matter (NEXT-DBDM) detector, a high-pressure gaseous natural xenon electroluminescent time projection chamber (TPC) that was built at the Lawrence Berkeley National Laboratory. It is a prototype of the planned NEXT-100 Xe-136 neutrino-less double beta decay (0 nu beta beta) experiment with the main objectives of demonstrating near-intrinsic energy resolution at energies up to 662 keV and of optimizing the NEXT-100 detector design and operating parameters. Energy resolutions of similar to 1% FWHM for 662 keV gamma rays were obtained at 10 and 15 atm and similar to 5% FWHM for 30 keV fluorescence xenon X-rays. These results demonstrate that 0.5% FWHM resolutions for the 2459 keV hypothetical neutrino-less double beta decay peak are realizable. This energy resolution is a factor 7-20 better than that of the current leading 0 nu beta beta experiments using liquid xenon and thus represents a significant advancement. We present also first results from a track imaging system consisting of 64 silicon photo-multipliers recently installed in NEXT-DBDM that, along with the excellent energy resolution, demonstrates the key functionalities required for the NEXT-100 0 nu beta beta search.