DOI: 10.5281/zenodo.8085320
title: Simulated datasets for detector and particle flow reconstruction: CLIC detector

description: <strong>Data description</strong> 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 -&gt; ttbar, center of mass energy at 380 GeV p8_ee_qq_ecm380: ee -&gt; Z* -&gt; qqbar, center of mass energy at 380 GeV p8_ee_ZH_Htautau: ee -&gt; ZH -&gt; Higgs decaying to tau leptons, center of mass energy at 380 GeV p8_ee_WW_fullhad: ee -&gt; WW -&gt; W decaying hadronically, center of mass energy at 380 GeV p8_ee_tt_ecm380_PU10: ee -&gt; ttbar with on average 10 Poisson-distributed events from ee-&gt;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. <strong>Contents</strong> 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 <strong>Dataset semantics</strong> 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. <strong>Dataset characteristics</strong> 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. <strong>How can you use these data?</strong> The ROOT files can be directly loaded with the uproot Python library. <strong>Disclaimer</strong> 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.
description: Funding support for the development and generation of this dataset by Estonian Research Council (ETAG) grant PSG864. The full dataset is hosted at the Julich HPC, supported by the CoE RAISE project. CoE RAISE project has received funding from the European Union's Horizon 2020 – Research and Innovation Framework Programme H2020-INFRAEDI-2019-1 under grant agreement no. 951733.