Simulation Resampling of the High Intensity Beam Experiment with Generative Adversarial Network [生成对抗网络法高强度束流实验束流模拟重采样]

作者：Cui J.-B.; Yu X.-Y.; Zhang Y.^*; Yuan Y.; Xing T.-Y.

来源：Nuclear Electronics & Detection Technology, 2022, 42(1): 35-40.

• Event Generation
• GAN
• Intense Beam Experiment
• Monte-Carlo Simulation
• Resampling

An end-to-end generative adversarial network (GAN) for the beam simulation resampling of high intensity beam experiment to generate beam data is introduced. The distribution and the relationship of high dimensional variables are reproduced with the significantly improvement of the generation time. This represents a promising method that could enable many applications with GAN in the simulation problem of particle physics experiments.

• 单位
  中国科学院大学; 郑州大学