0584299 - ÚJF 2025 RIV IT eng C - Konferenční příspěvek (zahraniční konf.)
Robotková, Monika
Systematic exploration of multi-scale jet substructure in p+p collisions at s√=200 GeV by the STAR experiment.
Proceedings of Science. Vol. 438. Trieste: Sissa Medilab srl, 2024, č. článku 177. ISSN 1824-8039.
[International Conference on Hard and Elecctromagnetic Probes of High-Energy Nuclear Collisions /11./. Aschaffenburg (DE), 26.03.2023-31.03.2023]
Grant CEP: GA ČR GA23-07499S
Výzkumná infrastruktura: BNL-CZ III - 90234
Institucionální podpora: RVO:61389005
Klíčová slova: STAR experiment * multi-scale jet substructure * collisions
Obor OECD: Particles and field physics
https://doi.org/10.22323/1.438.0177

Jets are multi-scale objects that connect asymptotically free partons to confined hadrons. Jet substructure measurements in vacuum provide essential insight into the parton evolution and the ensuing non-perturbative processes. In this study, we use the SoftDrop grooming technique, based on the angular-ordered Cambridge/Aachen reclustering algorithm, to probe correlations between jet substructure variables. This technique provides a correspondence between experimental observables and QCD splitting functions in vacuum. Corrections for detector effects are carried out utilizing either a three dimensional correction procedure or a machine learning based framework called MultiFold, with the latter retaining the correlations across more jet substructure observables, in an unbinned way. In these proceedings, we explore ensemble-level and jet-by-jet correlations between variables such as the shared momentum faction (zg), splitting scale (kT), groomed mass fraction (μ), jet charge (Q) and groomed jet radius (Rg) for jets of varying momenta and radii in p+p collisions at √s = 200 GeV using the STAR detector. To study the evolution along the jet shower, we present splitting observables at the first, second, and third hard splits in the SoftDrop splitting history for various jet and initiator prong momenta. Finally, the measurements are compared to leading order Monte Carlo models, PYTHIA 6, PYTHIA 8 and HERWIG.
Trvalý link: https://hdl.handle.net/11104/0352229