Simulated datasets for detector and particle flow reconstruction: CLIC detector

Data description

Datasets generated using Key4HEP and the CLIC detector model suitable for particle flow reconstruction studies.

The datasets contain generator particles, reconstructed tracks and calorimeter hits, reconstructed Pandora PF particles and their respective links in the EDM4HEP format.

The following processes have been simulated with Pythia 8:

• p8_ee_tt_ecm380: ee -> ttbar, center of mass energy at 380 GeV
• p8_ee_qq_ecm380: ee -> Z* -> qqbar, center of mass energy at 380 GeV
• p8_ee_ZH_Htautau: ee -> ZH -> Higgs decaying to tau leptons, center of mass energy at 380 GeV
• p8_ee_WW_fullhad: ee -> WW -> W decaying hadronically, center of mass energy at 380 GeV
• p8_ee_tt_ecm380_PU10: ee -> ttbar with on average 10 Poisson-distributed events from ee->gg overlayed, center of mass energy at 380 GeV

The following single particle gun samples have been generated with ddsim:

• e+/e-: single electron with energy between 1 and 100 GeV
• mu+/mu-: single muon with energy between 1 and 100 GeV
• kaon0L: single K0L with energy between 1 and 100 GeV
• neutron: single neutron with energy between 1 and 100 GeV
• pi+/pi-: single charged pion with energy between 1 and 100 GeV
• pi0: single neutral pion with energy between 1 and 100 GeV
• gamma: single photon with energy between 1 and 100 GeV

The detector simulation has been done with Geant4, the reconstruction with Marlin interfaced via Key4HEP which includes PF reconstruction with Pandora, all using publicly available models and code.

Contents

This record includes the following files:

• *_10files.tar: small archives of 10 files for each data sample, suitable for testing
• dataset_full.txt: the full list of files, hosted at the Julich HPC courtesy of the Raise CoE project, ~2.5TB total
• *.cmd: the Pythia8 cards
• pythia.py: the pythia steering code for Key4HEP
• run_sim.sh: the steering script for generating, simulating and reconstructing a single file of 100 events from the p8_ee_tt_ecm380, p8_ee_qq_ecm380, p8_ee_ZH_Htautau, p8_ee_WW_fullhad datasets
• run_sim_pu.sh: the steering script for generating, simulating and reconstructing a single file of 100 events from the p8_ee_tt_ecm380_PU10 dataset
• run_sim_gun.sh: the steering script for generating the single-particle gun samples
• run_sim_gun_np.sh: the steering script for generating multi-particle gun samples (extensive datasets have not yet been generated)
• check_files.py: the main driver script that configures the full statistics and creates submission scripts for all the simulations
• PandoraSettings.zip: the settings used for Pandora PF reconstruction
• main19.cc: the Pythia8+HepMC driver code for generating the events with PU overlay
• clicRec_e4h_input.py: the steering configuration of the reconstruction modules in Key4HEP
• clic_steer.py: the steering configuration of the Geant4 simulation modules in Key4HEP
• clic-visualize.ipynb: an example notebook demonstrating how the dataset can be loaded and events visualized in Python
• visualization.mp4: an example visualization of the hits and generator particles of a single ttbar event from the dataset

Dataset semantics

Each file consists of event records. Each event contains structured branches of the relevant physics data. The branches relevant to particle flow reconstruction include:

• MCParticles: the ground truth generator particles
• ECALBarrel, ECALEndcap, ECALOther, HCALBarrel, HCALEndcap, HCALOther, MUON: reconstructed hits in the various calorimeter subsystems
• SiTracks_Refitted: the reconstructed tracks
• PandoraClusters: the calorimeter hits, clustered by Pandora to calorimeter clusters
• MergedRecoParticles: the reconstructed particles from the Pandora particle flow algorithm
• CalohitMCTruthLink: the links between MC particles and reconstructed calorimeter hits
• SiTracksMCTruthLink: the links between MC particles and reconstructed tracks

The full details of the EDM4HEP format are available here.

Dataset characteristics

The full dataset in dataset_full.txt consists of 43 tar files of up to 100GB each. The tar files contain in total 58068 files, 2.5TB in the ROOT EDM4HEP format.

The subset in *_10files.tar for consists of 150 files, 26GB in the ROOT EDM4HEP format.

How can you use these data?

The ROOT files can be directly loaded with the uproot Python library.

Disclaimer

These are simulated samples suitable for conceptual machine learning R&D and software performance studies. They have not been calibrated with respect to real data, and should not be used to derive physics projections about the detectors.

Neither CLIC nor CERN endorse any works, scientific or otherwise, produced using these data. All releases will have a unique DOI that you are requested to cite in any applications or publications.