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Dataset . 2023
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Simulated datasets for detector and particle flow reconstruction: CLIC detector

Authors: Pata, Joosep;

Simulated datasets for detector and particle flow reconstruction: CLIC detector

Abstract

Datasets generated using Key4HEP and the CLIC detector 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: tt: ee->ttbar at 380 GeV qq: ee-> Z* -> qqbar at 380 GeV e+/e-: single electron with momentum between 1 and 100 GeV mu+/mu-: single muon with momentum between 1 and 100 GeV kaon0L: single K0L with momentum between 1 and 100 GeV neutron: single neutron with momentum between 1 and 100 GeV pi+/pi-: single charged pion with momentum between 1 and 100 GeV pi0: single neutral pion with momentum between 1 and 100 GeV gamma: single photon with momentum between 1 and 100 GeV The hard interaction has been generated with Pythia 8 (pythia.py, *.cmd), the detector simulation has been done with Geant4 (clic_steer.py), the reconstruction with Marlin interfaced via Key4HEP (clicRec_e4h_input.py), which includes PF reconstruction with Pandora (PandoraSettings.zip). The main steering scripts for generating the simulations are run_sim.sh (qq and tt) and run_sim_gun.sh (particle gun), which also contain the exact versions of the software and the detector.

Funding support by Estonian Research Council (ETAG) grant PSG864.

Keywords

high-energy physics, machine learning, reconstruction, particle physics, particle flow

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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