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arXiv 2406.13638physics.data-anastro-ph.IMhep-exphysics.ins-det
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XENONnT WIMP 搜寻:信号与背景建模及统计推断

XENONnT WIMP Search: Signal & Background Modeling and Statistical Inference

XENON Collaboration, E. Aprile, J. Aalbers, K. Abe, S. Ahmed Maouloud, L. Althueser, B. Andrieu, E. Angelino, D. Antón Martin, F. Arneodo, L. Baudis, M. Bazyk, … 展开作者

XENON Collaboration, E. Aprile, J. Aalbers, K. Abe, S. Ahmed Maouloud, L. Althueser, B. Andrieu, E. Angelino, D. Antón Martin, F. Arneodo, L. Baudis, M. Bazyk, L. Bellagamba, R. Biondi, A. Bismark, K. Boese, A. Brown, G. Bruno, R. Budnik, 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, 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. Giacomobono, R. Glade-Beucke, L. Grandi, J. Grigat, H. Guan, M. Guida, P. Gyoergy, R. Hammann, A. Higuera, C. Hils, L. Hoetzsch, N. F. Hood, M. Iacovacci, Y. Itow, J. Jakob, F. Joerg, 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, 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, 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, J. Shi, M. Silva, H. Simgen, A. Takeda, P. -L. Tan, A. Terliuk, D. Thers, F. Toschi, G. Trinchero, C. D. Tunnell, F. Tönnies, K. Valerius, S. Vecchi, S. Vetter, F. I. Villazon Solar, G. Volta, C. Weinheimer, M. Weiss, D. Wenz, C. Wittweg, V. H. S. Wu, Y. Xing, D. Xu, Z. Xu, M. Yamashita, L. Yang, J. Ye, L. Yuan, G. Zavattini, M. Zhong

AI总结:

本文介绍 XENONnT 暗物质实验中 WIMP 核反冲搜寻的信号与背景建模方法及统计推断框架,并基于 1.1 吨·年曝光量给出无信号超出下的竞争性排除上限。

摘要:

XENONnT 实验搜寻弱相互作用大质量粒子(WIMP)暗物质与氙原子核的散射。具体而言,XENONnT 使用一台双相时间投影室,其液氙靶质量为 5.9 吨,通过同时探测闪烁信号和电离信号来重建能量、位置和反冲类型。利用 1.1 吨·年的曝光量(有效质量为 4.18 吨)对核反冲 WIMP 进行盲分析,未发现超出背景预期的信号超出,由此对 WIMP-核子弹性散射截面导出了具有竞争力的排除上限,WIMP 质量范围从 6 GeV/c² 一直延伸到 TeV/c² 量级。本工作详细介绍了该搜寻中所采用的建模与统计方法。借助刻度数据,我们对探测器响应进行建模,并据此导出背景模型和信号模型。文中讨论了这些模型的构建与验证,以及额外的纯数据驱动背景。我们还描述了统计推断框架,包括似然函数的定义和置信区间的构造。

英文摘要:

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 (4.18 t fiducial mass) 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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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