发表机构
Chung-Ang University（中央大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究利用液内稀疏SiPM阵列保留局部光学信息，通过模拟训练的时间感知CNN重建缪子轨迹端点与正电子顶点，中位残差厘米级，验证了拓扑敏感重建的可行性。
AI 中文摘要
在闪烁体体积内部配备光传感器的液体闪烁体探测器，保留了在传统边界读出几何结构中大部分丢失的局部光学信息。我们证明，利用稀疏的三维硅光电倍增管晶格，这些信息足以用于带电粒子拓扑重建。在根据测量的光子计数分布验证Geant4探测器响应后，一个经过模拟训练、时间感知的卷积神经网络重建了穿透缪子的入射点和出射点，中位残差分别为1.91厘米和2.39厘米。重建的端点与宇宙射线缪子数据中由外部触发计数器定义的接受区域在几何上一致。同一框架还重建了模拟正电子起始径迹事件的生产顶点，中位残差约为4.5厘米。这些结果确立了在均匀液体闪烁体探测器中使用稀疏液内光传感器阵列进行拓扑敏感重建的可行性。
英文摘要
Liquid scintillator detectors instrumented with photosensors inside the scintillation volume preserve local optical information that is largely lost in conventional boundary-readout geometries. We demonstrate that this information is sufficient for charged-particle topology reconstruction using a sparse three-dimensional lattice of silicon photomultipliers. After validating the Geant4 detector response against measured photon-count distributions, a simulation-trained, time-informed convolutional neural network reconstructs the entry and exit points of through-going muons with median residuals of 1.91~cm and 2.39~cm, respectively. The reconstructed endpoints are geometrically consistent with acceptance regions defined by external trigger counters in cosmic-ray muon data. The same framework also reconstructs the production vertices of simulated positron starting-track events with a median residual of about 4.5~cm. These results establish the feasibility of topology-sensitive reconstruction using sparse in-liquid photosensor arrays in homogeneous liquid scintillator detectors.
Comments15 pages, 10 figures
