Single-jet datasets for particle reconstruction with deep learning

Training and test datasets used for [1]* . singleQuarkJet_train.root : N=60649 singleQuarkJet_test.root: N=38922 singleGluonJet_test.root: N=38295 The events are formed by a single initial state quark or gluon followed by parton shower generated in Pythia8 and then simulated using GEANT4 in a nearly-hermetic 6-layer calorimeter system as described in [1,2]. The branches in the ROOT files store features associated with cells, tracks, particles, pflow objects, jets, as well as edge lists for creating a graph representation of each event. *Note that subsets of N=50000 and N=30000 were used from the train and test samples, respectively, for the results in [1]. [1] Reconstructing particles in jets using set transformer and hypergraph prediction networks [2] Configurable Calorimeter Simulation for AI (COCOA)