In this repository, the implementation of the studies presented in the paper: Score-based Generative Models for Calorimeter Shower Simulation.
Tensorflow 2.6.0 was used to implement all models, based on the score-model implementation from Score-Based Generative Modeling through Stochastic Differential Equations
Results are presented using the Fast Calorimeter Data Challenge dataset and are available for download on zenodo:
cd scripts
python train.py --config CONFIG --model MODEL
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MODEL options are: subVPSDE/VESDE/VPSDE
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CONFIG options are
[config_dataset1.json/config_dataset2.json/config_dataset3.json]
python plot_caloscore.py --nevts N --sample --config CONFIG --model MODEL
python plot_caloscore.py --config CONFIG --model MODEL --nslices 1