학술논문
XENONnT WIMP Search: Signal & Background Modeling and Statistical Inference
Document Type
Working Paper
Author
XENON Collaboration; Aprile, E.; Aalbers, J.; Abe, K.; Maouloud, S. Ahmed; Althueser, L.; Andrieu, B.; Angelino, E.; Martin, D. Antón; Arneodo, F.; Baudis, L.; Bazyk, M.; Bellagamba, L.; Biondi, R.; Bismark, A.; Boese, K.; Brown, A.; Bruno, G.; Budnik, R.; Cardoso, J. M. R.; Chávez, A. P. Cimental; Colijn, A. P.; Conrad, J.; Cuenca-García, J. J.; D'Andrea, V.; Garcia, L. C. Daniel; Decowski, M. P.; Di Donato, C.; Di Gangi, P.; Diglio, S.; Eitel, K.; Elykov, A.; Ferella, A. D.; Ferrari, C.; Fischer, H.; Flehmke, T.; Flierman, M.; Fulgione, W.; Fuselli, C.; Gaemers, P.; Gaior, R.; Galloway, M.; Gao, F.; Ghosh, S.; Giacomobono, R.; Glade-Beucke, R.; Grandi, L.; Grigat, J.; Guan, H.; Guida, M.; Gyoergy, P.; Hammann, R.; Higuera, A.; Hils, C.; Hoetzsch, L.; Hood, N. F.; Iacovacci, M.; Itow, Y.; Jakob, J.; Joerg, F.; Kaminaga, Y.; Kara, M.; Kavrigin, P.; Kazama, S.; Kobayashi, M.; Kopec, A.; Kuger, F.; Landsman, H.; Lang, R. F.; Levinson, L.; Li, I.; Li, S.; Liang, S.; Lin, Y. -T.; Lindemann, S.; Lindner, M.; Liu, K.; Loizeau, J.; Lombardi, F.; Long, J.; Lopes, J. A. M.; Luce, T.; Ma, Y.; Macolino, C.; Mahlstedt, J.; Mancuso, A.; Manenti, L.; Marignetti, F.; Undagoitia, T. Marrodán; Martens, K.; Masbou, J.; Masson, E.; Mastroianni, S.; Melchiorre, A.; Messina, M.; Michael, A.; Miuchi, K.; Molinario, A.; Moriyama, S.; Morå, K.; Mosbacher, Y.; Murra, M.; Müller, J.; Ni, K.; Oberlack, U.; Paetsch, B.; Pan, Y.; Pellegrini, Q.; Peres, R.; Peters, C.; Pienaar, J.; Pierre, M.; Plante, G.; Pollmann, T. R.; Principe, L.; Qi, J.; Qin, J.; García, D. Ramírez; Rajado, M.; Singh, R.; Sanchez, L.; Santos, J. M. F. dos; Sarnoff, I.; Sartorelli, G.; Schreiner, J.; Schulte, D.; Schulte, P.; Eißing, H. Schulze; Schumann, M.; Lavina, L. Scotto; Selvi, M.; Semeria, F.; Shagin, P.; Shi, S.; Shi, J.; Silva, M.; Simgen, H.; Takeda, A.; Tan, P. -L.; Terliuk, A.; Thers, D.; Toschi, F.; Trinchero, G.; Tunnell, C. D.; Tönnies, F.; Valerius, K.; Vecchi, S.; Vetter, S.; Solar, F. I. Villazon; Volta, G.; Weinheimer, C.; Weiss, M.; Wenz, D.; Wittweg, C.; Wu, V. H. S.; Xing, Y.; Xu, D.; Xu, Z.; Yamashita, M.; Yang, L.; Ye, J.; Yuan, L.; Zavattini, G.; Zhong, M.
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Subject
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Abstract
The XENONnT experiment searches for weakly-interacting massive particle (WIMP) dark matter scattering off a xenon nucleus. In particular, XENONnT uses a dual-phase time projection chamber with a 5.9-tonne liquid xenon target, detecting both scintillation and ionization signals to reconstruct the energy, position, and type of recoil. A blind search for nuclear recoil WIMPs with an exposure of 1.1 tonne-years yielded no signal excess over background expectations, from which competitive exclusion limits were derived on WIMP-nucleon elastic scatter cross sections, for WIMP masses ranging from 6 GeV/$c^2$ up to the TeV/$c^2$ scale. This work details the modeling and statistical methods employed in this search. By means of calibration data, we model the detector response, which is then used to derive background and signal models. The construction and validation of these models is discussed, alongside additional purely data-driven backgrounds. We also describe the statistical inference framework, including the definition of the likelihood function and the construction of confidence intervals.
Comment: 20 pages, 10 figures
Comment: 20 pages, 10 figures