Abstract

The Circular Electron Positron Collider (CEPC) is a future experiment aimed at studying the properties of the Higgs boson with high precision. This requires excellent track reconstruction and particle identification (PID) performance, which is achieved in the 4th conceptual detector design of the CEPC experiments by combining a silicon tracker and a drift chamber. The drift chamber not only improves track reconstruction but also provides excellent PID with the cluster counting method. To evaluate the performance of this design accurately, a detailed simulation is necessary. In this paper, we present a refined drift chamber simulation by combining Geant4 and Garfield++. However, traditional waveform simulation using Garfield++ is extremely time-consuming, which motivates us to develop a fast waveform simulation method using a neural network. We validate the method using real data from the BESIII experiment. The results demonstrate the effectiveness of our approach and provide valuable insights for future experiments.

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