Datasets for fitting trajectories of elementary particles using deep learning
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下载链接：
https://zenodo.org/record/7347562
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资源简介：
Training and testing datasets of simulated elementary particles, used for fitting the trajectories of elementary particles in dense materials immersed in a magnetic field using deep learning. Once decompressed, the directory structure is the following:
training (1,762,327 particles in total):
proton: 414,824 particles.
pion: 432,855 particles.
muon: 446,858 particles (muons and antimuons).
electron: 467,790 particles (electrons and positrons).
testing (1,759,491):
proton: 412,092 particles.
pion: 432,807 particles.
muon: 447,003 particles (muons and antimuons).
electron: 467,589 particles (electrons and positrons).
创建时间：
2023-11-06
