Centrality dependence of the charged-particle multiplicity density at mid-rapidity in Pb-Pb collision at

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1 Tatiana Drozhzhova for ALICE Collaboration Centrality dependence of the charged-particle multiplicity density at mid-rapidity in Pb-Pb collision at GSI, Goethe Universität Frankfurt am Main ETTORE MAJORANA FOUNDATION AND CENTRE FOR SCIENTIFIC CULTURE INTERNATIONAL SCHOOL OF SUBNUCLEAR PHYSICS 54th Course: "THE NEW PHYSICS FRONTIERS IN THE LHC-2 ERA"

2 Motivation. What we knew before Run 2? Particle production multiplicity density at different energies: Pseudorapidity - emission angle of the particle relative to the beam axis Tatiana Drozhzhova (GSI / Goethe University) - Erice

3 Motivation. What we knew before Run 2? Particle production multiplicity density at different energies:? Curve confirmed? Pseudorapidity New data recorded in November 2015! - emission angle of the particle relative to the beam axis We present the measurement of the charge-particle pseudorapidity density in the interval First measurement which we can even do without magnetic field! Tatiana Drozhzhova (GSI / Goethe University) - Erice

4 Question Step 1: How to make the selection of the central (0-5 %) collisons? Tatiana Drozhzhova (GSI / Goethe University) - Erice

5 Geometric model Npart nucleons participating in the B b - impact parameter A collisions, which have undergone at least one binary collision Ncoll number of binary nn collisions Nuclear density in Glauber Model: Woods-Saxon distribution - nucleon-spectator Nucleus radius: Skin thickness: Hard-sphere exclusion distance: - wounded nucleon: nucleon Npart Inelastic nn cross-section for 5.02 TeV: Tatiana Drozhzhova (GSI / Goethe University) - Erice

6 Number of participants from impact parameter centrality classes Impact parameter distribution Tatiana Drozhzhova (GSI / Goethe University) - Erice

7 Number of participants from impact parameter centrality classes Number of participants distribution Tatiana Drozhzhova (GSI / Goethe University) - Erice

8 Question Step 2: How to connect model and experimental data? Tatiana Drozhzhova (GSI / Goethe University) - Erice

9 ALICE detector Content Tatiana Drozhzhova (GSI / Goethe University) - Erice

10 ALICE detector Content Tatiana Drozhzhova (GSI / Goethe University) - Erice

11 Inner ALICE detector VZERO: - arrays of scintillators - provides the signal ~ Ncharge particle striking V0 V0A V0C ArXiv: v2 Tatiana Drozhzhova (GSI / Goethe University) - Erice

12 Centrality classes and number of participants The % classification by V0A & V0C amplitude fitted with MC Glauber coupled with two-component model Effective number of particle production sources: & Negative Binomial Distribution (NBD) Npart, Ncoll is estimated from Glauber Model ϝ~0.8 - quantifies relevant contribution Centrality range: 0-80% Tatiana Drozhzhova (GSI / Goethe University) - Erice

13 Events selection and triggers The interaction triggers: V0A & V0C Events selected: Have a well defined primary vertex Reconstructed vertex: Pseudorapidity range: (extracted by correlating hits in the two SPD (Silicon Pixel Detector) layers) (to minimize edge effect) (constant acceptance) 0-80% hadronic cross section Tatiana Drozhzhova (GSI / Goethe University) - Erice

14 Question Step 3: How to measure multiplicity at mid-rapidity range? Tatiana Drozhzhova (GSI / Goethe University) - Erice

15 Multiplicity measurement The measurement relies on the ALICE Inner Tracking System SPD (Silicon Pixel Detector) consisting of two arrays of pixels & : D SP We can measure: Number of tracklets (a short track segment) Tatiana Drozhzhova (GSI / Goethe University) - Erice

16 Step 4: RESULTS Tatiana Drozhzhova (GSI / Goethe University) - Erice

17 Charged particle multiplicity density at mid-rapidity In order to compare bulk particle production at different energies and in different collision systems For PHOBOS and ATLAS: 0-6% centrality For all others 0-5% centrality events!!! W NE ~ A-A: pp, p-a: The results at 5.02 TeV confirms the trend established by lower energy data The strong rise in AA is not solely related to the multiplicity collisions undergone by the participants CERN-PH-EP Tatiana Drozhzhova (GSI / Goethe University) - Erice

18 Centrality dependence of charged particles pseudorapidity density CERN-PH-EP c fa peripheral.8 1 r: o t central strong dependence from Npart: factor: 1.8 Error bars: (Systematics) centrality dependent uncertainties Shaded band: correlated contributions Statistical uncertanties are negligiable 1.13) Smooth trend toward the value measured in MB p-pb Tatiana Drozhzhova (GSI / Goethe University) - Erice

19 Data comparison with models Color-glass-condensate models - QCD inspired models - high gluon density which becomes saturated at high energy -> number of soft gluons available for scattering and particle production is reduced by nonlinear interactions and parton recombination CERN-PH-EP Centrality range: 0-80% EPOS - model based on the Gribov-Regge theory of parton level - incorporates collective effect treated via flow parametrisation HIJING - combines perturbative QCD process with soft interactions - Includes a strong impact parameter dependence of parton shadowing Tatiana Drozhzhova (GSI / Goethe University) - Erice

20 Summary We have measured charge-particle pseudorapidity density in Pb-Pb at the highest available center-of-mass energy and observed: 20% increase for the most central collisions with respect to simular measurements at confirm the previously established power-law dependence of this quantity. centrality dependence of is very simular to that previously measured in lower energy AA collisions, increase from peripheral to central collisions. Most of the models which where able to reproduce the data at are able to describe the data at Our results provide further constraints for models describing high-energy heavy ion collisions. Tatiana Drozhzhova (GSI / Goethe University) - Erice

21 Back up slides Tatiana Drozhzhova (GSI / Goethe University) - Erice

22 Comparison of (dnch /dη)/npart /2 with model calculations for Pb Pb at Phys. Rev. Lett. 106, Tatiana Drozhzhova (GSI / Goethe University) - Erice

23 Centrality dependence of charge particle pseudorapidity density CERN-PH-EP CERN-PH-EP central peripheral peripheral central The ratio between the data measured at the two collision energies is independent of Npart withing the uncertanties which are largely uncorrelated Tatiana Drozhzhova (GSI / Goethe University) - Erice

24 Two component model and data CERN-PH-EP Tatiana Drozhzhova (GSI / Goethe University) - Erice

25 Centrality classes and number of participants The % classification by V0A & V0C amplithude fitted with MC Glauber coupled with two component model Effective number of particle production sources: & Negative Binomial Distribution Parametrised by: - <Multiplicity> per source - controls the width Npart, Ncoll is estimated from Glauber Model ϝ~0.8 - quantifies relevant contribution Centrality range: 0-80% Tatiana Drozhzhova (GSI / Goethe University) - Erice

26 Tracklets reconstruction in SPD Tatiana Drozhzhova (GSI / Goethe University) - Erice

27 HIJING combines perturbative-qcd (pqcd) processes with soft interactions includes a strong impact parameter dependence of parton shadowing. The data at s = 2.76TeV were previously compared to HIJING using gluon shadowing parameter: sg = 0.20 and sg = 0.23 [*] sg = 0.23 better estimate of the overall normalization, sg = a better agreement with the shape. At s = 5.02TeV, a larger sg = > limit the multiplicity per participant, -> that leading to a centrality dependence which does not reproduce the data. [*] - Phys. Rev. Lett. 106, (2011) Link: W.-T. Deng, X.-N. Wang, and R. Xu, Hadron production in p þ p, p þ Pb, and Pb þ Pb collisions with the HIJING 2.0 model at energies available at the CERN Large Hadron Collider, Phys. Rev. C 83, (2011).

28 EPOS model based on the Gribov-Regge theory at the parton level which incorporates collective effects treated via a flow parametrization in the EPOS LHC version. It provides a good description of the data Link: T. Pierog, I. Karpenko, J. M. Katzy, E. Yatsenko, and K. Werner, EPOS LHC: Test of collective hadronization with data measured at the CERN Large Hadron Collider, Phys. Rev. C 92, (2015).

29 Saturation-inspired models 1) rcbk-mc, with the MV initial conditions [1,2], 2) Kharzeev, Levin, and Nardi [3] 3) Armesto, Salgado, and Wiedemann [4]: rely on pqcd Initial-state gluon saturation => Limiting the number of produced partons This results in a factorization of the energy and centrality dependences of the multiplicity in the models, as observed in the experimental data. The rcbk-mc and Armesto, Salgado, and Wiedemann models provide a better description of the data, in particular of the shape, than the Kharzeev, Levin, and Nardi model. [1] J. L. Albacete, A. Dumitru, and Y. Nara, CGC initial conditions at RHIC and LHC, J. Phys. Conf. Ser. 316, (2011). [2] arxiv: [3] D. Kharzeev et all Color glass condensate at the LHC: Hadron multiplicities in pp, pa, and AA collisions, Nucl. Phys. A747, 609 (2005). [4] ] N. Armesto et all Relating High-Energy Lepton-Hadron, Proton-Nucleus and NucleusNucleus Collisions through Geometric Scaling, Phys. Rev. Lett. 94, (2005).

30 EKRT Model is based on pqcd initial state with mini-jets with gluon saturation to suppress soft parton production Further evolution is performed by event-by-event viscous hydrodynamics. The normalization is fixed by exploiting the 0 5% most central multiplicity measurement. The EKRT model can broadly describe both the shape and the overall magnitude of the dependence of multiplicity on centrality. Link:H. Niemi, K. J. Eskola, and R. Paatelainen, Event-byevent fluctuations in a perturbative QCD + saturation + hydrodynamics model: Determining QCD matter shear viscosity in ultrarelativistic heavy-ion collisions, Phys. Rev. C 93, (2016).

31 Laboratory of Ultra-high Energy Physics, Saint-Petersburg State University Determination of classes of events in multiplicity and its relevance to centrality in high energy Pb-Pb and p-pb collisions in different MC models Drozhzhova Tatiana XI International Conference on Quark Confinement and the Hadron Spectrum, 2014, St.Petersburg

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33 Opposite bunches particle scattering Fix nucleus-target collision A b B - Number of wounded nucleons - Number of nucleons-spectators - Total Energy of collision fixed by calorimeters - Energy of a nucleon 2 methods of fixing centrality: Multiplicity Nucleon-spectators

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35 Example: Centrality classes in ALICE experiment If y(x) is a function of events distribution versus of impact parameter of AA collision. Then F(x) square under the plot Peak value F(x) = F(0) normalization F(x) : For Impact Parameter G(0) = 0% G(xmax)=100% % G(x) - function compares value of centrality of the collisions (expressed in percentage) to value of the impact parameter. For Multiplicity G(0) = 100% G(xmax)=0% Borders of intervals of the centrality are equal to values of function G (x) in the points limiting the given interval.

36 Centrality in Pb-Pb collisions at 2.76 TeV based on Glauber Model

37 Multiplicity Percentile MC Glauber, PbPb 2.76TeV Some multiplicity centrality classes Npart distribution in the different centrality classes

38 RMS of Npart See details in T.Drozhzhova poster report ISSP 2014 With decrease of width of centrality bin the RMS decreases Plato (~5-10) is reached at centrality width For central events near 3% For peripheral 10% is enough MC Glauber, PbPb 2.76TeV

39 Centrality in p-pb collisions at 5.02 TeV HIJING 1.38

40 HIJING [1] It was based on a two-component geometrical model of minijet production and soft interaction. It has incorporated nuclear effects such as nuclear modification of the parton distribution functions (gluon shadowing) Gluon shadowing [2] Without shadowing nucleons interaction will be independent There are differences between nuclear and proton PDF(parton distribution function) (observed in experiments). This leads to decrease of nucleon-nucleon cross section at low x. Similar effect is also present in Models with energy conservation in elementary nucleon-nucleon collisions (see refs [3-5]) [1] HIJING: A Monte Carlo model for multiple jet production in p p, p A and A A collisions, Xin-Nian Wang and Miklos Gyulassy, Phys.Rev.D 44, 3501 (1991) [2] J. Jalilian-Marian arxiv:hep-ph/ [3] G. Feofilov, A. Ivanov, Number of nucleon-nucleon collisions vs energy in modified Glauber calculations // Journal of Physics G CS, 5, (2005) [4] Irais Bautista, Carlos Pajares, Jose Guilherme Milhano, Jorge Dias de Deus. Phys. Rev. C 86 (2012) [5] V. Kovalenko, Phys. Atom. Nucl. 76, 1189 (2013), arxiv: [hep-ph]; arxiv: [hep-ph], 2013; V. Kovalenko, V. Vechernin. PoS(BaldinISHEPP XXI) 077, 2012, arxiv: [nucl-th]

41 Dependence on a shadowing parameter PRL 110, Experimental data is better described by HIJING with shadowing sg <Npart> <Mult>

42 Centrality from Multiplicity in p-pb

43 Centrality from Multiplicity in p-pb

44 Normalization of Multiplicity yields PRL 110, <Npart>=7.9±0.6 From Glauber model Sg <Npart> <Mult> Number of participants is depended on models HIJING 1.38 No straight forward treatment of experimental data on multiplicity, based on normalization to Npart See details in T. Drozhzhova, G. Feofilov, V. Kovalenko, A. Seryakov. PoS (QFTHEP 2013) 053, 2013

45 Summary and Conclusions: The method of centrality evaluation initially developed for ion-ion collisions was applied for p+pb Large fluctuations of number of participants in multiplicity classes make dividing of the events in classes according to Npart problematically Model dependence of Npart makes questionable normalization of multiplicity yields to Npart

46 Back-up slides

47 Centrality from impact parameter p-pb

48 Centrality from impact parameter p-pb

49 Pb-Pb AB-collision s NN = 2.76TeV Nuclear density Woods-Saxon distribution: r RA ( r) 0 1 exp a 1 R R A A R fm a fm

50 Poisson disctribution: Particle multiplicity is proportional to number of produced strings, which is proportional to participants number N ( AB ) and collisions number N x [0,1] C ( )