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arXiv 2005.03903physics.ins-det
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使用深度学习算法提高MRPC检测器的时间分辨率

Improving the time resolution of the MRPC detector using deep-learning algorithms

Fuyue Wang, Dong Han, Yi Wang

摘要:

多间隙电阻板室(MRPC)将用作螺线管大强度设备(SoLID)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,以便对碰撞中产生的$π/K$进行3 $σ$分离。为了实现这一目标,整个系统,包括MRPC探测器,前端电子和读出系统将升级。基于新系统,提出了一种使用组合LSTM(ComLSTM)神经网络的时间重构算法。在宇宙线实验中,该算法的最佳时间分辨率为16.8ps,大大提高了MRPC探测器的计时能力,满足了SoLID的要求。

英文摘要:

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.

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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