Long- and short-range correlations and their event-scale dependence in high-multiplicity pp collisions at $\boldsymbol{\sqrt{{\textit s}}}=13$ TeV

The ALICE collaboration Acharya, Shreyasi ; Adamova, Dagmar ; Adler, Alexander ; et al.
JHEP 05 (2021) 290, 2021.
Inspire Record 1840098 DOI 10.17182/hepdata.105588

Two-particle angular correlations are measured in high-multiplicity proton-proton collisions at $\sqrt{s} =13$ TeV by the ALICE Collaboration. The yields of particle pairs at short-($\Delta\eta$$\sim$ 0) and long-range ($1.6 < |\Delta\eta| < 1.8$) in pseudorapidity are extracted on the near-side ($\Delta\varphi$$\sim$ 0). They are reported as a function of transverse momentum ($p_{\mathrm T}$) in the range $1 <p_{\mathrm T}< 4$ GeV/$c$. Furthermore, the event-scale dependence is studied for the first time by requiring the presence of high-$p_{\rm T}$ leading particles and jets for varying $p_{\rm T}$ thresholds. The results demonstrate that the long-range "ridge" yield, possibly related to the collective behavior of the system, is present in events with high-$p_{\mathrm T}$ processes. The magnitudes of the short- and long-range yields are found to grow with the event scale. The results are compared to EPOS LHC and PYTHIA 8 calculations, with and without string-shoving interactions. It is found that while both models describe the qualitative trends in the data, calculations from EPOS LHC show a better quantitative agreement, in particular for the $p_{\rm T}$ and event-scale dependencies.

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Pseudorapidity densities of charged particles with transverse momentum thresholds in pp collisions at $\sqrt{s} = 5.02$ and $13$ TeV

The ALICE collaboration Acharya, Shreyasi ; Adamova, Dagmar ; Adler, Alexander ; et al.
Phys.Rev.D 108 (2023) 072008, 2023.
Inspire Record 2601279 DOI 10.17182/hepdata.144248

The pseudorapidity density of charged particles with minimum transverse momentum ($p_{\rm T}$) thresholds of 0.15, 0.5, 1, and 2 GeV$/c$ is measured in pp collisions at the centre of mass energies of $\sqrt{s} =$ 5.02 and 13 TeV with the ALICE detector. The study is carried out for inelastic collisions with at least one primary charged particle having a pseudorapidity ($\eta$) within $\pm0.8$ and $p_{\rm T}$ larger than the corresponding threshold. In addition, measurements without $p_{\rm T}$-thresholds are performed for inelastic and non-single-diffractive events as well as for inelastic events with at least one charged particle having $|\eta|<1$ in pp collisions at $\sqrt{s} =$ 5.02 TeV for the first time at the LHC. These measurements are compared to the PYTHIA 6, PYTHIA 8, and EPOS-LHC models. In general, the models describe the $\eta$ dependence of particle production well. However, discrepancies are observed for the highest transverse momentum threshold ($p_{\rm T}>2 {\rm\ GeV}/c$), highlighting the importance of such measurements for tuning event generators. The new measurements agree within uncertainties with results from the ATLAS and CMS experiments obtained at $\sqrt{s} = 13$ TeV.

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Pseudorapidity distributions of charged particles as a function of mid and forward rapidity mutiplicities in pp collisions at $\sqrt{s}$ = 5.02, 7 and 13 TeV

The ALICE collaboration Acharya, Shreyasi ; Adamova, Dagmar ; Adler, Alexander ; et al.
Eur.Phys.J.C 81 (2021) 630, 2021.
Inspire Record 1818157 DOI 10.17182/hepdata.106205

The multiplicity dependence of the pseudorapidity density of charged particles in proton-proton (pp) collisions at centre-of-mass energies $\sqrt{s}$ = 5.02, 7 and 13 TeV measured by ALICE is reported. The analysis relies on track segments measured in the midrapidity range ($|\eta| < 1.5$). Results are presented for inelastic events having at least one charged particle produced in the pseudorapidity interval $|\eta|<1$ ($\mathrm{INEL}_{>0}$). The multiplicity dependence of the pseudorapidy density of charged particles is measured with mid and forward rapidity multiplicity estimators, the latter being less affected by autocorrelations. A detailed comparison with predictions from the PYTHIA 8 and EPOS LHC event generators is also presented. Both generators provide a good description of the data.

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