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Identified Hadron Production as a Function of Event Multiplicity and Transverse Spherocity in pp Collisions at $\sqrt{s}$ = 7 and 13 TeV with the ALICE Detector

This study reports on identified hadron production as a function of event multiplicity ($\langle\textrm{d}N_{\textrm{ch}}/\textrm{d}η\rangle$) and transverse spherocity ($S_\textrm{O}$ ) in proton-proton collisions at $\sqrt{s}$ = 7 and 13 TeV measured with the ALICE detector at the LHC. The particl...

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Detalles Bibliográficos
Autor principal: Vislavicius, Vytautas
Lenguaje:eng
Publicado: 2018
Materias:
Acceso en línea:http://cds.cern.ch/record/2310568
Descripción
Sumario:This study reports on identified hadron production as a function of event multiplicity ($\langle\textrm{d}N_{\textrm{ch}}/\textrm{d}η\rangle$) and transverse spherocity ($S_\textrm{O}$ ) in proton-proton collisions at $\sqrt{s}$ = 7 and 13 TeV measured with the ALICE detector at the LHC. The particle spectra and their ratios measured in high-multiplicity events show signatures of an expanding medium. Integrated particle yields as a function of multiplicity measured in pp collisions at $\sqrt{s}$ = 7 and 13 TeV are compared to those measured in p-Pb and Pb-Pb collisions. Hadrochemical composition of particles are found to be similar in different colliding systems under different $\sqrt{s}$, provided similar multiplicities are compared. This suggests that hadron yields are dominantly driven by $\langle\textrm{d}N_{\textrm{ch}}/\textrm{d}η\rangle$, and not the colliding system or center-of-mass energy. On the other hand, particle spectra measured in pp collisions at $\sqrt{s}$ = 13 TeV is harder than that at 7 TeV, when similar $\langle\textrm{d}N_{\textrm{ch}}/\textrm{d}η\rangle$ are compared. In addition, hadron production as a function of multiplicity is studied in the context of statistical, hydrodynamical and pQCD-inspired models. In order to disentangle the soft QCD component from the hard, high-multiplicity pp collisions at $\sqrt{s}$ = 13 TeV are studied as a function of transverse spherocity. It is found that the amount of flow-like effects in the data sample can be controlled using event shape observables.