Offline tagging of radon-induced backgrounds in XENON1T and
applicability to other liquid xenon detectors
E. Aprile,J. Aalbers,K. Abe,S. Ahmed Maouloud,L. Althueser,B. Andrieu,E. Angelino,J. R. Angevaare,D. Antón Martin,F. Arneodo,L. Baudis,A. L. Baxter,M. Bazyk,L. Bellagamba,R. Biondi,A. Bismark,E. J. Brookes,A. Brown,G. Bruno,R. Budnik,T. K. Bui,J. M. R. Cardoso,A. P. Cimental Chavez,A. P. Colijn,J. Conrad,J. J. Cuenca-García,V. D'Andrea,L. C. Daniel Garcia,M. P. Decowski,C. Di Donato,P. Di Gangi,S. Diglio,K. Eitel,A. Elykov,A. D. Ferella,C. Ferrari,H. Fischer,T. Flehmke,M. Flierman,W. Fulgione,C. Fuselli,P. Gaemers,R. Gaior,M. Galloway,F. Gao,S. Ghosh,R. Glade-Beucke,L. Grandi,J. Grigat,H. Guan,M. Guida,R. Hammann,A. Higuera,C. Hils,L. Hoetzsch,N. F. Hood,M. Iacovacci,Y. Itow,J. Jakob,F. Joerg,A. Joy,Y. Kaminaga,M. Kara,P. Kavrigin,S. Kazama,M. Kobayashi,A. Kopec,F. Kuger,H. Landsman,R. F. Lang,L. Levinson,I. Li,S. Li,S. Liang,Y. T. Lin,S. Lindemann,M. Lindner,K. Liu,J. Loizeau,F. Lombardi,J. Long,J. A. M. Lopes,T. Luce,Y. Ma,C. Macolino,J. Mahlstedt,A. Mancuso,L. Manenti,F. Marignetti,T. Marrodán Undagoitia,K. Martens,J. Masbou,E. Masson,S. Mastroianni,A. Melchiorre,M. Messina,A. Michael,K. Miuchi,A. Molinario,S. Moriyama,K. Morå,Y. Mosbacher,M. Murra,J. Müller,K. Ni,U. Oberlack,B. Paetsch,J. Palacio,Y. Pan,Q. Pellegrini,R. Peres,C. Peters,J. Pienaar,M. Pierre,G. Plante,T. R. Pollmann,L. Principe,J. Qi,J. Qin,D. Ramírez García,M. Rajado,J. Shi,R. Singh,L. Sanchez,J. M. F. dos Santos,I. Sarnoff,G. Sartorelli,J. Schreiner,D. Schulte,P. Schulte,H. Schulze Eißing,M. Schumann,L. Scotto Lavina,M. Selvi,F. Semeria,P. Shagin,S. Shi,M. Silva,H. Simgen,A. Takeda,P. -L. Tan,A. Terliuk,D. Thers,F. Toschi,G. Trinchero,C. Tunnell,F. Tönnies,K. Valerius,S. Vecchi,S. Vetter,G. Volta,C. Weinheimer,M. Weiss,D. Wenz,C. Wittweg,T. Wolf,V. H. S. Wu,Y. Xing,D. Xu,Z. Xu,M. Yamashita,L. Yang,J. Ye,L. Yuan,G. Zavattini,M. Zhong,T. Zhu
arxiv（2024）
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摘要
This paper details the first application of a software tagging algorithm to
reduce radon-induced backgrounds in liquid noble element time projection
chambers, such as XENON1T and XENONnT. The convection velocity field in XENON1T
was mapped out using ^222Rn and ^218Po events, and the
root-mean-square convection speed was measured to be 0.30 ± 0.01 cm/s.
Given this velocity field, ^214Pb background events can be tagged
when they are followed by ^214Bi and ^214Po decays, or
preceded by ^218Po decays. This was achieved by propagating a point
cloud as directed by the velocity field, and searching for ^214Bi
and ^214Po decays or ^218Po decays within a volume
defined by the point cloud. In XENON1T, this tagging system achieved a
^214Pb background reduction of 6.2^+0.4_-0.9% with an
exposure loss of 1.8± 0.2 %. The tagging algorithm was also used to
produce a population of tagged events with a large enhancement in the
^214Pb fraction. We show that the performance can be improved in
XENONnT, and that the performance of such a software-tagging approach can be
expected to be further improved in a diffusion-limited scenario. Finally, a
similar method might be useful to tag the cosmogenic ^137Xe
background, which is relevant to the search for neutrinoless double-beta decay.
