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This upload contains the datasets used in arXiv:2302.11594. The file g4-showers_950k_10x10_train_val_test.pt contains the 760k training, 95k validation and 95k test showers as well as their incident energies. It should be loaded as follows: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - import torch list_tensors = torch.load(args.file_path) for (idx, tensor) in enumerate(list_tensors): [showers_train, showers_val, showers_test, inc_energies_train, inc_energies_val, inc_energies_test] = list_tensors - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - The file g4-showers_665k_10x10_test.pt contains 665k additional showers that were used for the classifier scaling studies, in addition to the 95k test showers from the file g4-showers_950k_10x10_train_val_test.pt. It should be loaded as follows: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - import torch list_tensors = torch.load("g4-showers_950k_10x10_train_val_test.pt") [showers_geant, inc_energies_geant] = list_tensors - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - A detailed description of how the datasets were simulated can be found in the paper.
Deep Generative Modeling, High Energy Physics
Deep Generative Modeling, High Energy Physics
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