NEXT Collaboration(Jones, B. J. P. et al), Carcel, S., Carrion, J. V., Diaz, J., Martin-Albo, J., Martinez, A., et al. (2022). The dynamics of ions on phased radio-frequency carpets in high pressure gases and application for barium tagging in xenon gas time projection chambers. Nucl. Instrum. Methods Phys. Res. A, 1039, 167000–19pp.
Abstract: Radio-frequency (RF) carpets with ultra-fine pitches are examined for ion transport in gases at atmospheric pressures and above. We develop new analytic and computational methods for modeling RF ion transport at densities where dynamics are strongly influenced by buffer gas collisions. An analytic description of levitating and sweeping forces from phased arrays is obtained, then thermodynamic and kinetic principles are used to calculate ion loss rates in the presence of collisions. This methodology is validated against detailed microscopic SIMION simulations. We then explore a parameter space of special interest for neutrinoless double beta decay experiments: transport of barium ions in xenon at pressures from 1 to 10 bar. Our computations account for molecular ion formation and pressure dependent mobility as well as finite temperature effects. We discuss the challenges associated with achieving suitable operating conditions, which lie beyond the capabilities of existing devices, using presently available or near-future manufacturing techniques.
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Gomez-Cadenas, J. J., Martin-Albo, J., Menendez, J., Mezzetto, M., Monrabal, F., & Sorel, M. (2024). The search for neutrinoless double-beta decay. Riv. Nuovo Cimento, 46, 619–692.
Abstract: Neutrinos are the only particles in the Standard Model that could be Majorana fermions, that is, completely neutral fermions that are their own antiparticles. The most sensitive known experimental method to verify whether neutrinos are Majorana particles is the search for neutrinoless double-beta decay. The last 2 decades have witnessed the development of a vigorous program of neutrinoless double-beta decay experiments, spanning several isotopes and developing different strategies to handle the backgrounds masking a possible signal. In addition, remarkable progress has been made in the understanding of the nuclear matrix elements of neutrinoless double-beta decay, thus reducing a substantial part of the theoretical uncertainties affecting the particle-physics interpretation of the process. On the other hand, the negative results by several experiments, combined with the hints that the neutrino mass ordering could be normal, may imply very long lifetimes for the neutrinoless double-beta decay process. In this report, we review the main aspects of such process, the recent progress on theoretical ideas and the experimental state of the art. We then consider the experimental challenges to be addressed to increase the sensitivity to detect the process in the likely case that lifetimes are much longer than currently explored, and discuss a selection of the most promising experimental efforts.
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NEMO-3 Collaboration(Argyriades, J. et al), Diaz, J., Martin-Albo, J., Monrabal, F., Novella, P., Serra, L., et al. (2011). Spectral modeling of scintillator for the NEMO-3 and SuperNEMO detectors. Nucl. Instrum. Methods Phys. Res. A, 625(1), 20–28.
Abstract: We have constructed a GEANT4-based detailed software model of photon transport in plastic sontillator blocks and have used it to study the NEMO-3 and SuperNEMO calorimeters employed in experiments designed to search for neutnnoless double beta decay We compare our simulations to measurements using conversion electrons from a calibration source of (BI)-B-207 and show that the agreement is improved if wavelength-dependent properties of the calorimeter are taken into account In this article we briefly describe our modeling approach and results of our studies.
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NEXT Collaboration(Ferrario, P. et al), Laing, A., Lopez-March, N., Gomez-Cadenas, J. J., Alvarez, V., Carcel, S., et al. (2016). First proof of topological signature in the high pressure xenon gas TPC with electroluminescence amplification for the NEXT experiment. J. High Energy Phys., 01(1), 104–18pp.
Abstract: The NEXT experiment aims to observe the neutrinoless double beta decay of Xe-136 in a high-pressure xenon gas TPC using electroluminescence (EL) to amplify the signal from ionization. One of the main advantages of this technology is the possibility to reconstruct the topology of events with energies close to Q(beta beta). This paper presents the first demonstration that the topology provides extra handles to reject background events using data obtained with the NEXT-DEMO prototype. Single electrons resulting from the interactions of Na-22 1275 keV gammas and electron-positron pairs produced by conversions of gammas from the Th-228 decay chain were used to represent the background and the signal in a double beta decay. These data were used to develop algorithms for the reconstruction of tracks and the identification of the energy deposited at the end-points, providing an extra background rejection factor of 24.3 +/- 1.4 (stat.)%, while maintaining an efficiency of 66.7 +/- 1.% for signal events.
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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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