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High Energy Physics - Experiment

arXiv:2510.02258 (hep-ex)
[Submitted on 2 Oct 2025 (v1) , last revised 9 Oct 2025 (this version, v2)]

Title: Predicting the single-site and multi-site event discrimination power of dual-phase time projection chambers

Title: 预测双相时间投影室的单点和多点事件区分能力

Authors:A.B.M. Rafi Sazzad, Clarke A. Hardy, Xiang Dai, Jingke Xu, Brian G. Lenardo, Felicia Sutanto, Nicholas A. Antipa, Jeremy D. Koertzen, Prince John, Abraham Akinin, Teal J. Pershing
Abstract: Dual-phase xenon time projection chambers (TPCs) are widely used in searches for rare dark matter and neutrino interactions, in part because of their excellent position reconstruction capability in 3D. Despite their millimeter-scale resolution along the charge drift axis, xenon TPCs face challenges in resolving single-site (SS) and multi-site (MS) interactions in the transverse plane. In this paper, we build a generic TPC model with an idealized light-based signal readout, and use Fisher Information (FI) to study its theoretical capability of differentiating SS and MS events. We also demonstrate via simulation that this limit can be approached with conventional reconstruction algorithms like maximum likelihood estimation, and with a convolutional neural network classifier. The implications of this study on future TPC experiments will be discussed.
Abstract: 双相氙气时间投影室(TPCs)广泛用于稀有暗物质和中微子相互作用的搜索,部分原因是它们在三维空间中的优秀位置重建能力。 尽管在电荷漂移轴上具有毫米级的分辨率,氙气TPC在横向平面上分辨单点(SS)和多点(MS)相互作用方面面临挑战。 在本文中,我们构建了一个通用的TPC模型,采用理想化的基于光的信号读出,并使用费舍尔信息(FI)来研究其区分SS和MS事件的理论能力。 我们还通过模拟证明,这种极限可以通过传统的重建算法如最大似然估计以及卷积神经网络分类器来接近。 将讨论这项研究对未来TPC实验的影响。
Comments: 29 pages, 18 figures
Subjects: High Energy Physics - Experiment (hep-ex) ; Instrumentation and Detectors (physics.ins-det)
Cite as: arXiv:2510.02258 [hep-ex]
  (or arXiv:2510.02258v2 [hep-ex] for this version)
  https://doi.org/10.48550/arXiv.2510.02258
arXiv-issued DOI via DataCite
Journal reference: LLNL-JRNL-2011380

Submission history

From: Jingke Xu [view email]
[v1] Thu, 2 Oct 2025 17:41:15 UTC (2,071 KB)
[v2] Thu, 9 Oct 2025 21:53:53 UTC (2,045 KB)
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