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NEXT Collaboration(Woodruff, K. et al), Alvarez, V., Benlloch-Rodriguez, J. M., Carcel, S., Carrion, J. V., Diaz, J., et al. (2020). Radio frequency and DC high voltage breakdown of high pressure helium, argon, and xenon. J. Instrum., 15(4), P04022–15pp.
Abstract: Motivated by the possibility of guiding daughter ions from double beta decay events to single-ion sensors for barium tagging, the NEXT collaboration is developing a program of R&D to test radio frequency (RF) carpets for ion transport in high pressure xenon gas. This would require carpet functionality in regimes at higher pressures than have been previously reported, implying correspondingly larger electrode voltages than in existing systems. This mode of operation appears plausible for contemporary RF-carpet geometries due to the higher predicted breakdown strength of high pressure xenon relative to low pressure helium, the working medium in most existing RF carpet devices. In this paper we present the first measurements of the high voltage dielectric strength of xenon gas at high pressure and at the relevant RF frequencies for ion transport (in the 10MHz range), as well as new DC and RF measurements of the dielectric strengths of high pressure argon and helium gases at small gap sizes. We find breakdown voltages that are compatible with stable RF carpet operation given the gas, pressure, voltage, materials and geometry of interest.
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NEXT Collaboration(Haefner, J. et al), Benlloch-Rodriguez, J. M., Carcel, S., Carrion, J. V., Martin-Albo, J., Martinez-Vara, M., et al. (2023). Reflectance and fluorescence characteristics of PTFE coated with TPB at visible, UV, and VUV as a function of thickness. J. Instrum., 18(3), P03016–21pp.
Abstract: Polytetrafluoroethylene (PTFE) is an excellent diffuse reflector widely used in light collection systems for particle physics experiments. In noble element systems, it is often coated with tetraphenyl butadiene (TPB) to allow detection of vacuum ultraviolet scintillation light. In this work this dependence is investigated for PTFE coated with TPB in air for light of wavelengths of 200 nm, 260 nm, and 450 nm. The results show that TPB-coated PTFE has a reflectance of approximately 92% for thicknesses ranging from 5 mm to 10 mm at 450 nm, with negligible variation as a function of thickness within this range. A cross-check of these results using an argon chamber supports the conclusion that the change in thickness from 5 mm to 10 mm does not affect significantly the light response at 128 nm. Our results indicate that pieces of TPB-coated PTFE thinner than the typical 10 mm can be used in particle physics detectors without compromising the light signal.
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NEXT Collaboration(Renner, J. et al), Kekic, M., Martinez-Lema, G., Alvarez, V., Benlloch-Rodriguez, J. M., Carcel, S., et al. (2019). Energy calibration of the NEXT-White detector with 1% resolution near Q(beta beta) of Xe-136. J. High Energy Phys., 10(10), 230–13pp.
Abstract: Excellent energy resolution is one of the primary advantages of electroluminescent high-pressure xenon TPCs. These detectors are promising tools in searching for rare physics events, such as neutrinoless double-beta decay (beta beta 0 nu), which require precise energy measurements. Using the NEXT-White detector, developed by the NEXT (Neutrino Experiment with a Xenon TPC) collaboration, we show for the first time that an energy resolution of 1% FWHM can be achieved at 2.6 MeV, establishing the present technology as the one with the best energy resolution of all xenon detectors for beta beta 0 nu searches.
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NEXT Collaboration(Martinez-Lema, G. et al), Benlloch-Rodriguez, J. M., Carcel, S., Carrion, J. V., Diaz, J., Felkai, R., et al. (2021). Sensitivity of the NEXT experiment to Xe-124 double electron capture. J. High Energy Phys., 02(2), 203–25pp.
Abstract: Double electron capture by proton-rich nuclei is a second-order nuclear process analogous to double beta decay. Despite their similarities, the decay signature is quite different, potentially providing a new channel to measure the hypothesized neutrinoless mode of these decays. The Standard-Model-allowed two-neutrino double electron capture (2 nu EC EC) has been predicted for a number of isotopes, but only observed in Kr-78, Ba-130 and, recently, Xe-124. The sensitivity to this decay establishes a benchmark for the ultimate experimental goal, namely the potential to discover also the lepton-number-violating neutrinoless version of this process, 0 nu EC EC. Here we report on the current sensitivity of the NEXT-White detector to Xe-124 2 nu EC EC and on the extrapolation to NEXT-100. Using simulated data for the 2 nu EC EC signal and real data from NEXT-White operated with Xe-124-depleted gas as background, we define an optimal event selection that maximizes the NEXT-White sensitivity. We estimate that, for NEXT-100 operated with xenon gas isotopically enriched with 1 kg of Xe-124 and for a 5-year run, a sensitivity to the 2 nu EC EC half-life of 6 x 10(22) y (at 90% confidence level) or better can be reached.
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NEXT Collaboration(Kekic, M. et al), Benlloch-Rodriguez, J. M., Carcel, S., Carrion, J. V., Diaz, J., Felkai, R., et al. (2021). Demonstration of background rejection using deep convolutional neural networks in the NEXT experiment. J. High Energy Phys., 01(1), 189–22pp.
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.
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