Multi-strange baryon production at mid-rapidity in Pb-Pb collisions at sqrt(s_NN) = 2.76 TeV

The ALICE collaboration Abelev, Betty Bezverkhny ; Adam, Jaroslav ; Adamova, Dagmar ; et al.
Phys.Lett.B 728 (2014) 216-227, 2014.
Inspire Record 1243865 DOI 10.17182/hepdata.62098

The production of ${\rm\Xi}^-$ and ${\rm\Omega}^-$ baryons and their anti-particles in Pb-Pb collisions at $\sqrt{s_{\rm NN}}$ = 2.76 TeV has been measured using the ALICE detector. The transverse momentum spectra at mid-rapidity ($|y| < 0.5$) for charged $\rm\Xi$ and $\rm\Omega$ hyperons have been studied in the range $0.6 < p_{\rm T} < 8.0$ GeV/$c$ and $1.2 < p_{\rm T} < 7.0$ GeV/$c$, respectively, and in several centrality intervals (from the most central 0-10% to the most peripheral 60-80% collisions). These spectra have been compared with the predictions of recent hydrodynamic models. In particular, the Krak${\'o}$w and EPOS models give a satisfactory description of the data, with the latter covering a wider $p_{\rm T}$ range. Mid-rapidity yields, integrated over $p_{\rm T}$, have been determined. The hyperon-to-pion ratios are similar to those at RHIC: they rise smoothly with centrality up to $\langle N_{\rm part}\rangle$~150 and saturate thereafter. The enhancements (yields per participant nucleon relative to pp collisions) increase both with the strangeness content of the baryon and with centrality, but are less pronounced than at lower energies.

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Underlying Event measurements in pp collisions at sqrt(s) = 0.9 and 7 TeV with the ALICE experiment at the LHC

The ALICE collaboration Abelev, Betty ; Abrahantes Quintana, Arian ; Adamova, Dagmar ; et al.
JHEP 07 (2012) 116, 2012.
Inspire Record 1080735 DOI 10.17182/hepdata.58863

We present measurements of Underlying Event observables in pp collisions at $\sqrt{s}$ = 0.9 and 7 TeV. The analysis is performed as a function of the highest charged-particle transverse momentum $p_{\rm T, LT}$ in the event. Different regions are defined with respect to the azimuthal direction of the leading (highest transverse momentum) track: Toward, Transverse and Away. The Toward and Away regions collect the fragmentation products of the hardest partonic interaction. The Transverse region is expected to be most sensitive to the Underlying Event activity. The study is performed with charged particles above three different $p_{\rm T}$ thresholds: 0.15, 0.5 and 1.0 GeV/$c$. In the Transverse region we observe an increase in the multiplicity of a factor 2-3 between the lower and higher collision energies, depending on the track $p){\rm T}$ threshold considered. Data are compared to Pythia 6.4, Pythia 8.1 and Phojet. On average, all models considered underestimate the multiplicity and summed $p_{\rm T}$ in the Transverse region by about 10-30%.

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Jet and underlying event properties as a function of particle multiplicity in proton-proton collisions at sqrt(s) = 7 TeV

The CMS collaboration Chatrchyan, Serguei ; Khachatryan, Vardan ; Sirunyan, Albert M ; et al.
Eur.Phys.J.C 73 (2013) 2674, 2013.
Inspire Record 1261026 DOI 10.17182/hepdata.68128

Characteristics of multi-particle production in proton-proton collisions at $\sqrt{s}$=7 TeV are studied as a function of the charged-particle multiplicity, $N_{ch}$. The produced particles are separated into two classes: those belonging to jets and those belonging to the underlying event. Charged particles are measured with pseudorapidity |η|<2.4 and transverse momentum $p_T$ > 0.25 GeV/c. Jets are reconstructed from charged-particles only and required to have $p_T$ > 5 GeV/c. The distributions of jet $p_T$, average $p_T$ of charged particles belonging to the underlying event or to jets, jet rates, and jet shapes are presented as functions of $N_{ch}$ and compared to the predictions of the PYTHIA and HERWIG event generators. Predictions without multi-parton interactions fail completely to describe the $N_{ch}$-dependence observed in the data. For increasing $N_{ch}$, PYTHIA systematically predicts higher jet rates and harder $p_T$ spectra than seen in the data, whereas HERWIG shows the opposite trends. At the highest multiplicity, the data–model agreement is worse for most observables, indicating the need for further tuning and/or new model ingredients.

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