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(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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Gariazzo, S., Archidiacono, M., de Salas, P. F., Mena, O., Ternes, C. A., & Tortola, M. (2018). Neutrino masses and their ordering: global data, priors and models. J. Cosmol. Astropart. Phys., 03(3), 011–22pp.
Abstract: We present a full Bayesian analysis of the combination of current neutrino oscillation, neutrinoless double beta decay and Cosmic Microwave Background observations. Our major goal is to carefully investigate the possibility to single out one neutrino mass ordering, namely Normal Ordering or Inverted Ordering, with current data. Two possible parametrizations (three neutrino masses versus the lightest neutrino mass plus the two oscillation mass splittings) and priors (linear versus logarithmic) are exhaustively examined. We find that the preference for NO is only driven by neutrino oscillation data. Moreover, the values of the Bayes factor indicate that the evidence for NO is strong only when the scan is performed over the three neutrino masses with logarithmic priors; for every other combination of parameterization and prior, the preference for NO is only weak. As a by-product of our Bayesian analyses, we are able to (a) compare the Bayesian bounds on the neutrino mixing parameters to those obtained by means of frequentist approaches, finding a very good agreement; (b) determine that the lightest neutrino mass plus the two mass splittings parametrization, motivated by the physical observables, is strongly preferred over the three neutrino mass eigenstates scan and (c) find that logarithmic priors guarantee a weakly-to-moderately more efficient sampling of the parameter space. These results establish the optimal strategy to successfully explore the neutrino parameter space, based on the use of the oscillation mass splittings and a logarithmic prior on the lightest neutrino mass, when combining neutrino oscillation data with cosmology and neutrinoless double beta decay. We also show that the limits on the total neutrino mass Sigma m(nu) can change dramatically when moving from one prior to the other. These results have profound implications for future studies on the neutrino mass ordering, as they crucially state the need for self-consistent analyses which explore the best parametrization and priors, without combining results that involve different assumptions.
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Meloni, D., Morisi, S., & Peinado, E. (2011). Neutrino phenomenology and stable dark matter with A(4). Phys. Lett. B, 697(4), 339–342.
Abstract: We present a model based on the A(4) non-Abelian discrete symmetry leading to a predictive five-parameter neutrino mass matrix and providing a stable dark matter candidate. We found an interesting correlation among the atmospheric and the reactor angles which predicts theta(23) similar to pi/4for very small reactor angle and deviation from maximal atmospheric mixing for large theta(13). Only normal neutrino mass spectrum is possible and the effective mass entering the neutrinoless double beta decay rate is constrained to be vertical bar m(ee)vertical bar > 4 x 10(-4) eV.
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Alvarez Melcon, A. et al, & Gimeno, B. (2021). First results of the CAST-RADES haloscope search for axions at 34.67 μeV. J. High Energy Phys., 10(10), 075–16pp.
Abstract: We present results of the Relic Axion Dark-Matter Exploratory Setup (RADES), a detector which is part of the CERN Axion Solar Telescope (CAST), searching for axion dark matter in the 34.67 μeV mass range. A radio frequency cavity consisting of 5 sub-cavities coupled by inductive irises took physics data inside the CAST dipole magnet for the first time using this filter-like haloscope geometry. An exclusion limit with a 95% credibility level on the axion-photon coupling constant of g(a gamma) greater than or similar to 4 x 10(-13) GeV-1 over a mass range of 34.6738 μeV < m(a)< 34.6771 μeV is set. This constitutes a significant improvement over the current strongest limit set by CAST at this mass and is at the same time one of the most sensitive direct searches for an axion dark matter candidate above the mass of 25 μeV. The results also demonstrate the feasibility of exploring a wider mass range around the value probed by CAST-RADES in this work using similar coherent resonant cavities.
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