论文标题
使用深度学习算法改善MRPC检测器的时间分辨率
Improving the time resolution of the MRPC detector using deep-learning algorithms
论文作者
论文摘要
多间隙电阻板室（MRPC）将用作电磁阀大强度设备（实心）中的飞行时间（TOF）系统。 MRPC系统实验所需的时间分辨率为20 ps，以便对碰撞中创建的$π/k $进行3 $σ$分离。为了实现这一目标，将升级包括MRPC检测器，前端电子和读取系统在内的整个系统。基于新系统，提出了使用组合LSTM（COMLSTM）神经网络的时间重建算法。在宇宙射线测试中，通过该算法实现的最佳时间分辨率是16.8 PS，这在很大程度上提高了MRPC检测器的时序能力并很好地满足了固体的要求。
The multi-gap resistive plate chambers (MRPCs) will be used as the Time-of-Flight (ToF) system in the Solenoidal Large Intensity Device (SoLID). The time resolution required by the experiment for the MRPC system is 20 ps in order to make a 3 $σ$ separation of the $π/K$ created in the collisions. To achieve this goal, the whole system including the MRPC detector, the front-end electronics and the readout system will be upgraded. Based on the new system, a time reconstruction algorithm using a combined LSTM (ComLSTM) neural network is proposed. The best time resolution achieved with this algorithm in a cosmic ray test is 16.8 ps, which largely improves the timing ability of the MRPC detector and well satisfies the requirement of the SoLID.
