This repository contains the code and results presented in arXiv:1909.01359.
CycleJet is a framework to create mappings between different categories of jets using CycleGANs. The model architecture is adapted from https://github.com/eriklindernoren/Keras-GAN/tree/master/cyclegan.
CycleJet is tested and supported on 64-bit systems running Linux.
Install CycleJet with Python's pip package manager:
git clone https://github.com/JetsGame/CycleJet.git
cd CycleJet
pip install .
To install the package in a specific location, use the "--target=PREFIX_PATH" flag.
This process will copy the cyclejet program to your environment python path.
We recommend the installation of the CycleJet package using a miniconda3
environment with the
configuration specified here.
CycleJet requires the following packages:
- python3
- numpy
- fastjet (compiled with --enable-pyext)
- matplotlib
- pandas
- keras
- tensorflow
- json
- gzip
- argparse
- scikit-image
- scikit-learn
- hyperopt (optional)
The final models presented in arXiv:1909.01359 are stored in:
- results/QCD_to_W: CycleJet which converts QCD <-> W jet.
- results/parton_to_delphes: CycleJet which converts partons <-> delphes.
All data used for the final models can be downloaded from the git-lfs repository at https://github.com/JetsGame/data.
In order to launch the code run:
cyclejet --output <output_folder> <runcard.yaml>
This will create a folder containing the result of the fit.
- S. Carrazza and F. A. Dreyer, "Lund jet images from generative and cycle-consistent adversarial networks," arXiv:1909.01359