Caloscore official repository

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

Data

Results are presented using the Fast Calorimeter Data Challenge dataset and are available for download on zenodo:

• Dataset 1
• Dataset 2
• Dataset 3

Run the training scripts with

cd scripts
python train.py  --config CONFIG --model MODEL

• MODEL options are: subVPSDE/VESDE/VPSDE

• CONFIG options are [config_dataset1.json/config_dataset2.json/config_dataset3.json]

Sampling from the learned score function

python plot_caloscore.py  --nevts N  --sample  --config CONFIG --model MODEL

Creating the plots shown in the paper

python plot_caloscore.py  --config CONFIG --model MODEL --nslices 1