arXiv · 2603.23549
Enhancing Neutrinoless Double-Beta Decay Sensitivity of Liquid-Xenon Time Projection Chamber with Augmented Convolutional Neural Network
Abstract
Dual-phase time projection chamber (TPC) that employs a multi-ton-scale liquid xenon (LXe) target mass is a pioneering detector technology to search for dark matter. Beyond its advantage in dark matter direct detection efforts, the natural xenon target allows it to search for the neutrinoless double-beta decay ($0\nu\beta\beta$) process, which would violate lepton number conservation and indicate that neutrinos are Majorana particles. However, such $0\nu\beta\beta$ searches have been limited by gamma-ray backgrounds originating from the detector materials. In this work, we designed an augmented convolutional neural network (A-CNN) model to extract additional event-topology information from detector data. Using simulation and calibration data from XENONnT, a leading LXe TPC experiment, our model achieved over 60% background rejection while maintaining 90% signal acceptance. This rejection power improves XENONnT's projected sensitivity of the $^{136}$Xe $0\nu\beta\beta$ search by about 40%. The implementation of A-CNN in the data analysis of future liquid xenon observatories, such as XLZD, will further enhance their sensitivities for $0\nu\beta\beta$ with $^{136}$Xe.
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E. Aprile, J. Aalbers, K. Abe, M. Adrover, S. Ahmed Maouloud, L. Althueser, B. Andrieu, E. Angelino, D. Antón Martin, S. R. Armbruster, F. Arneodo, L. Baudis, M. Bazyk, L. Bellagamba, R. Biondi, A. Bismark, K. Boese, R. M. Braun, G. Bruni, G. Bruno, R. Budnik, C. Cai, C. Capelli, J. M. R. Cardoso, A. P. Cimental Chávez, A. P. Colijn, J. Conrad, J. J. Cuenca-García, V. D'Andrea, L. C. Daniel Garcia, M. P. Decowski, A. Deisting, C. Di Donato, P. Di Gangi, S. Diglio, K. Eitel, S. el Morabit, R. Elleboro, A. Elykov, A. D. Ferella, C. Ferrari, H. Fischer, T. Flehmke, M. Flierman, R. Frankel, D. Fuchs, W. Fulgione, C. Fuselli, R. Gaior, F. Gao, R. Giacomobono, F. Girard, R. Glade-Beucke, L. Grandi, J. Grigat, H. Guan, M. Guida, P. Gyorgy, R. Hammann, A. Higuera, C. Hils, L. Hoetzsch, N. F. Hood, M. Iacovacci, Y. Itow, J. Jakob, F. Joerg, Y. Kaminaga, M. Kara, S. Kazama, P. Kharbanda, M. Kobayashi, D. Koke, K. Kooshkjalali, A. Kopec, H. Landsman, R. F. Lang, L. Levinson, A. Li, I. Li, S. Li, S. Liang, Z. Liang, Y. -T. Lin, S. Lindemann, M. Lindner, K. Liu, M. Liu, F. Lombardi, J. A. M. Lopes, G. M. Lucchetti, T. Luce, Y. Ma, C. Macolino, J. Mahlstedt, F. Marignetti, T. Marrodán Undagoitia, K. Martens, J. Masbou, S. Mastroianni. 2026-03-20. Enhancing Neutrinoless Double-Beta Decay Sensitivity of Liquid-Xenon Time Projection Chamber with Augmented Convolutional Neural Network. https://arxiv.org/abs/2603.23549
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