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XENONnT Analysis: Signal Reconstruction, Calibration and Event Selection

Authors :
XENON Collaboration
Aprile, E.
Aalbers, J.
Abe, K.
Maouloud, S. Ahmed
Althueser, L.
Andrieu, B.
Angelino, E.
Angevaare, J. R.
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.
Deisting, A.
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.
Koke, D.
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.
Merz, J.
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.
Publication Year :
2024

Abstract

The XENONnT experiment, located at the INFN Laboratori Nazionali del Gran Sasso, Italy, features a 5.9 tonne liquid xenon time projection chamber surrounded by an instrumented neutron veto, all of which is housed within a muon veto water tank. Due to extensive shielding and advanced purification to mitigate natural radioactivity, an exceptionally low background level of (15.8 $\pm$ 1.3) events/(tonne$\cdot$year$\cdot$keV) in the (1, 30) keV region is reached in the inner part of the TPC. XENONnT is thus sensitive to a wide range of rare phenomena related to Dark Matter and Neutrino interactions, both within and beyond the Standard Model of particle physics, with a focus on the direct detection of Dark Matter in the form of weakly interacting massive particles (WIMPs). From May 2021 to December 2021, XENONnT accumulated data in rare-event search mode with a total exposure of one tonne $\cdot$ year. This paper provides a detailed description of the signal reconstruction methods, event selection procedure, and detector response calibration, as well as an overview of the detector performance in this time frame. This work establishes the foundational framework for the `blind analysis' methodology we are using when reporting XENONnT physics results.<br />Comment: 27 pages, 23 figures

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2409.08778
Document Type :
Working Paper