L2LFlows: Generating High-Fidelity 3D Calorimeter Images
Authors/Creators
- 1. Universität Hamburg, University of Geneva, HES-SO Geneva
- 2. Rutgers University, Universität Heidelberg
- 3. Universität Hamburg
- 4. Rutgers University
- 5. Universität Hamburg, CDCS (Hamburg)
- 6. DESY (Hamburg)
- 7. DESY (Hamburg), CDCS (Hamburg)
Description
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:
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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
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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:
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import torch
list_tensors = torch.load("g4-showers_950k_10x10_train_val_test.pt")
[showers_geant, inc_energies_geant] = list_tensors
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A detailed description of how the datasets were simulated can be found in the paper.
Files
l2lflows_geant4_datasets.zip
Additional details
Related works
- Is described by
- Preprint: arXiv:2302.11594v1 (arXiv)