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Gomez-Cadenas, J. J., Benlloch-Rodriguez, J. M., & Ferrario, P. (2016). Application of scintillating properties of liquid xenon and silicon photomultiplier technology to medical imaging. Spectroc. Acta Pt. B, 118, 6–13.
Abstract: We describe a new positron emission time-of-flight apparatus using liquid xenon. The detector is based in a liquid xenon scintillating cell. The cell shape and dimensions can be optimized depending on the intended application. In its simplest form, the liquid xenon scintillating cell is a box in which two faces are covered by silicon photomultipliers and the others by a reflecting material such as Teflon. It is a compact, homogenous and highly efficient detector which shares many of the desirable properties of monolithic crystals, with the added advantage of high yield and fast scintillation offered by liquid xenon. Our initial studies suggest that good energy and spatial resolution comparable with that achieved by lutetium oxyorthosilicate crystals can be obtained with a detector based in liquid xenon scintillating cells. In addition, the system can potentially achieve an excellent coincidence resolving time of better than 100 ps.
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NEXT Collaboration(Martinez-Lema, G. et al), Palmeiro, B., Botas, A., Laing, A., Renner, J., Simon, A., et al. (2018). Calibration of the NEXT-White detector using Kr-83m decays. J. Instrum., 13, P10014–21pp.
Abstract: The NEXT-White (NEW) detector is currently the largest radio-pure high-pressure xenon gas time projection chamber with electroluminescent readout in the world. It has been operating at Laboratorio Subterraneo de Canfranc (LSC) since October 2016. This paper describes the calibrations performed using Kr-83m decays during a long run taken from March to November 2017 (Run II). Krypton calibrations are used to correct for the finite drift-electron lifetime as well as for the dependence of the measured energy on the event transverse position which is caused by variations in solid angle coverage both for direct and reflected light and edge effects. After producing calibration maps to correct for both effects we measure an excellent energy resolution for 41.5 keV point-like deposits of (4.553 +/- 0.010 (stat.) +/- 0.324 (sys.)) % FWHM in the full chamber and (3.804 +/- 0.013 (stat.) +/- 0.112 (sys.)) % FWHM in a restricted fiducial volume. Using naive 1/root E scaling, these values translate into resolutions of (0.5916 +/- 0.0014 (stat.) +/- 0.0421 (sys.)) % FWHM and (0.4943 +/- 0.0017 (stat.) +/- 0.0146 (sys.)) % FWHM at the Q(beta beta) energy of xenon double beta decay (2458 keV), well within range of our target value of 1%.
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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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NEXT Collaboration(McDonald, A. D. et al), Alvarez, V., Benlloch-Rodriguez, J. M., Botas, A., Carcel, S., Carrion, J. V., et al. (2018). Demonstration of Single-Barium-Ion Sensitivity for Neutrinoless Double-Beta Decay Using Single-Molecule Fluorescence Imaging. Phys. Rev. Lett., 120(13), 132504–6pp.
Abstract: A new method to tag the barium daughter in the double-beta decay of Xe-136 is reported. Using the technique of single molecule fluorescent imaging (SMFI), individual barium dication (Ba++) resolution at a transparent scanning surface is demonstrated. A single-step photobleach confirms the single ion interpretation. Individual ions are localized with superresolution (similar to 2 nm), and detected with a statistical significance of 12.9 sigma over backgrounds. This lays the foundation for a new and potentially background-free neutrinoless double-beta decay technology, based on SMFI coupled to high pressure xenon gas time projection chambers.
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NEXT Collaboration(Ferrario, P. et al), Benlloch-Rodriguez, J. M., Kekic, M., Renner, J., Uson, A., Alvarez, V., et al. (2019). Demonstration of the event identification capabilities of the NEXT-White detector. J. High Energy Phys., 10(10), 052–20pp.
Abstract: In experiments searching for neutrinoless double-beta decay, the possibility of identifying the two emitted electrons is a powerful tool in rejecting background events and therefore improving the overall sensitivity of the experiment. In this paper we present the first measurement of the efficiency of a cut based on the different event signatures of double and single electron tracks, using the data of the NEXT-White detector, the first detector of the NEXT experiment operating underground. Using a Th-228 calibration source to produce signal-like and background-like events with energies near 1.6 MeV, a signal efficiency of 71.6 +/- 1.5(stat) +/- 0.3(sys) % for a background acceptance of 20.6 +/- 0.4(stat) +/- 0.3(sys)% is found, in good agreement with Monte Carlo simulations. An extrapolation to the energy region of the neutrinoless double beta decay by means of Monte Carlo simulations is also carried out, and the results obtained show an improvement in background rejection over those obtained at lower energies.
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