A dataset of quark and gluon jets generated with Pythia 8, originally used in Energy Flow Networks: Deep Sets for Particle Jets and available through the EnergyFlow Python package. Generation parameters are listed below: Pythia 8.226, \(\sqrt{s}=14\,\text{TeV} \) Quarks (uds only) from WeakBosonAndParton:qg2gmZq, gluons from WeakBosonAndParton:qqbar2gmZg with the Z decaying to neutrinos FastJet 3.3.0, anti-ki jets with R=0.4 \(p_T^\text{jet}\in[500,550]\,\text{GeV},\,|y^\text{jet} |<1.7\) Each file is in compressed NumPy format and can be accessed in python using np.load. There are two arrays in each file X: (100000,M,4), exactly 50k quark and 50k gluon jets, randomly sorted, where M is the max multiplicity of the jets in that file (other jets have been padded with zero-particles), and the features of each particle are its pt, rapidity, azimuthal angle, and pdgid. y: (100000,), an array of labels for the jets where gluon is 0 and quark is 1. If you use this dataset, please cite this Zenodo record as well as the corresponding paper: P. T. Komiske, E. M. Metodiev, J. Thaler, Energy Flow Networks: Deep Sets for Particle Jets, JHEP 01 (2019) 121, arXiv:1810.05165. The data format is additionally described as part of the EnergyFlow documentation. For the corresponding dataset of Herwig jets, see this Zenodo record.

{"references": ["P. T. Komiske, E. M. Metodiev, J. Thaler, Energy Flow Networks: Deep Sets for Particle Jets, JHEP 01 (2019) 121, arXiv:1810.05165.", "P. T. Komiske, E. M. Metodiev, EnergyFlow, https://energyflow.network."]}