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NEXT Collaboration(Novella, P. et al), Carcel, S., Carrion, J. V., Diaz, J., Martin-Albo, J., Martinez, A., et al. (2022). Measurement of the Xe-136 two-neutrino double-beta-decay half-life via direct background subtraction in NEXT. Phys. Rev. C, 105(5), 055501–8pp.
Abstract: We report a measurement of the half-life of the Xe-136 two-neutrino double-beta decay performed with a novel direct-background-subtraction technique. The analysis relies on the data collected with the NEXT-White detector operated with Xe-136-enriched and Xe-136-depleted xenon, as well as on the topology of double-electron tracks. With a fiducial mass of only 3.5 kg of Xe, a half-life of 2.34(-0.46)(+0.80) (stat)(-0.17)(+0.30) (sys) x 10(21) yr is derived from the background-subtracted energy spectrum. The presented technique demonstrates the feasibility of unique background-model-independent neutrinoless double-beta-decay searches.
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NEXT Collaboration(Novella, P. et al), Carcel, S., Carrion, J. V., Lopez, F., Lopez-March, N., Martin-Albo, J., et al. (2023). Demonstration of neutrinoless double beta decay searches in gaseous xenon with NEXT. J. High Energy Phys., 09(9), 190–35pp.
Abstract: The NEXT experiment aims at the sensitive search of the neutrinoless double beta decay in Xe-136, using high-pressure gas electroluminescent time projection chambers. The NEXT-White detector is the first radiopure demonstrator of this technology, operated in the Laboratorio Subterr & aacute;neo de Canfranc. Achieving an energy resolution of 1% FWHM at 2.6 MeV and further background rejection by means of the topology of the reconstructed tracks, NEXT-White has been exploited beyond its original goals in order to perform a neu-trinoless double beta decay search. The analysis considers the combination of 271.6 days of Xe-136-enriched data and 208.9 days of 136Xe-depleted data. A detailed background mod-eling and measurement has been developed, ensuring the time stability of the radiogenic and cosmogenic contributions across both data samples. Limits to the neutrinoless mode are obtained in two alternative analyses: a background-model-dependent approach and a novel direct background-subtraction technique, offering results with small dependence on the background model assumptions. With a fiducial mass of only 3.50 +/- 0.01 kg of Xe-136-enriched xenon, 90% C.L. lower limits to the neutrinoless double beta decay are found in the T-1/2(0 nu) > 5.5x10(23) -1.3x10(24) yr range, depending on the method. The presented techniques stand as a pro of-of-concept for the searches to be implemented with larger NEXT detectors.
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NEXT Collaboration(Novella, P. et al), Palmeiro, B., Simon, A., Sorel, M., Martinez-Lema, G., Alvarez, V., et al. (2018). Measurement of radon-induced backgrounds in the NEXT double beta decay experiment. J. High Energy Phys., 10(10), 112–27pp.
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.
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NEXT Collaboration(Novella, P. et al), Palmeiro, B., Sorel, M., Uson, A., Alvarez, V., Benlloch-Rodriguez, J. M., et al. (2019). Radiogenic backgrounds in the NEXT double beta decay experiment. J. High Energy Phys., 10(10), 051–26pp.
Abstract: Natural radioactivity represents one of the main backgrounds in the search for neutrinoless double beta decay. Within the NEXT physics program, the radioactivity- induced backgrounds are measured with the NEXT-White detector. Data from 37.9 days of low-background operations at the Laboratorio Subterraneo de Canfranc with xenon depleted in Xe-136 are analyzed to derive a total background rate of (0.84 +/- 0.02) mHz above 1000 keV. The comparison of data samples with and without the use of the radon abatement system demonstrates that the contribution of airborne-Rn is negligible. A radiogenic background model is built upon the extensive radiopurity screening campaign conducted by the NEXT collaboration. A spectral fit to this model yields the specific contributions of Co-60, K-40, Bi-214 and Tl-208 to the total background rate, as well as their location in the detector volumes. The results are used to evaluate the impact of the radiogenic backgrounds in the double beta decay analyses, after the application of topological cuts that reduce the total rate to (0.25 +/- 0.01) mHz. Based on the best-fit background model, the NEXT-White median sensitivity to the two-neutrino double beta decay is found to be 3.5 sigma after 1 year of data taking. The background measurement in a Q(beta beta)+/- 100 keV energy window validates the best-fit background model also for the neutrinoless double beta decay search with NEXT-100. Only one event is found, while the model expectation is (0.75 +/- 0.12) events.
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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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