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.
Cite
@article{arxiv.2005.03903,
title = {Improving the time resolution of the MRPC detector using deep-learning algorithms},
author = {Fuyue Wang and Dong Han and Yi Wang},
journal= {arXiv preprint arXiv:2005.03903},
year = {2020}
}