Event-by-Event physics in ALICE

1. Event-by-Event physics in ALICE Chiara Zampolli ALICE-TOF Centro E. Fermi (Roma), INFN (Bologna) Correlations and Fluctuations in Relativistic Nuclear Collisions, Firenze, 7th-9th July 2006

2. Outline • Introduction • PID performance • Identified Particle Spectra • Particle Ratios • Mean pT • Summary and Conclusions

3. QGP Signatures • The nature and the time evolution of the hot and dense system created in a heavy-ion collision are expected to show the characteristic behaviour of a QGP phase transition, which could dramatically change from one event to the other. • Apart from the very well known probes (inclusive probes, probes related to deconfinement...), an analysis on an Event by Event basis offers the opportunity to study the QCD phase transition and to get insights into the QGP. For example: Thermodynamic quantities (T,S) Energy density fluctuations Jets and minijets DCC, Balance function... Properties of the system Order of phase transition Physics of the QGP Chiral phase transition, hadronization time... relying on the very high particle multiplicities produced per event (SPS, RHIC, LHC)

4. Event by Event Fluctuations FLUCTUATIONS • Statistical • Finite number of particles produced • Experimental acceptance and resolution • Dynamical • Dynamics of the collision • Evolution of the system • Sources of event-by-event fluctuations: • geometrical • energy, momentum, charge conservation • anisotropic flow • Bose-Einstein correlations • resonance decays • jets and mini-jets • temperature fluctuations

5. Some Experimental Results STAR, = 200 GeV NA49, = 17.2 GeV Mean pT K/p ratio What will ALICE sensitivity be? STAR

6. ALICE E-by-E Program Thanks to the very high charged particle multiplicity expected per event, E-by-E studies will be feasible with the ALICE detector for many observables: • Temperature • Mean pT • Particle Ratios • Multiplicity • Conserved Quantities (Charge) • HBT radii • Balance Function • Flow • DCC • ... Particle IDentification plays a crucial role! http://aliceinfo.cern.ch/, ALICE PPR II

7. ALICE PID separation @ 3s separation @ 2s (dE/dx)

8. Monte Carlo Event Sample • 300 Hijing Pb-Pb events (fully simulated and reconstructed) • Centrality 0 – 10% of minbias cross section (0 < b < 5 fm) • Magnetic Field B = 0.5 T • ~ 4500

9. Primary Track Selection p p K p p K • The selection on primary tracks has been performed relying on the quality of the extrapolation of the tracks to the reconstructed primary vertex, taking into account the covariance parameters of the track as well. • The inefficiency of the cut can be due to • reconstruction defects • secondaries included efficiency

10. PID Performance - Definitions efficiency= contamination = overall efficiency = = number of correctly/uncorrectly identified particles = number of generated primaries • The PID performance is evaluated in terms of: N = number of reconstructed particles to which the PID procedure is applied

11. Combined PID – ITS || TPC || TOF p K p K p p 0.15 < pT < 4 GeV/c

12. Generated vs Identified Spectra p K p Generated Identified (t + w) Identified (w)

13. p from L weak decays p Generated p Reconstructed p from L Per event:

14. Fitting of the Spectra • Correction of the identified spectra taking into account: • Limited acceptanceand reconstruction efficiency of the detectors: εacc • Transverse momentum reconstruction efficiency: εp • PID efficiency: εPID • PID contamination: CPID • Event by event fitting procedure for pT spectra: exponential function ,T = slope parameter, connected to the kinetical freeze-out temperature

15. Results – Single Event, pT spectra p K p Generated Reconstructed i.e. corrected! Fit range: 0.25 < pT < 2 GeV/c

16. Results – T Distributions p p K = 226 MeV sT = 13 MeV = 182 MeV sT=3 MeV = 303 MeV sT = 21 MeV sT/T ~ 0.5% sT/T ~ 7% sT/T ~ 6%

17. Systematic Uncertainties on the Corrections • Possible sources of systematic errors: • Knowledge of the acceptance and reconstruction efficiencies, secondaries’ flow... • A detailed study on is to be made of systematic uncertainties. • Nevertheless, since a level of 10%seems reasonable, 100 virtual experiments randomly changing the efficiency (contamination) correction factors by 10%. • A small relative increase of few %s in the width of the temperature distributions has been observed in both cases (efficiency/ contamination). • The mean values of the temperatures can vary by few %s.

18. Particle Ratios K/p: R = 0.106 σR = 0.009 p/p: R = 0.055 σR = 0.006 σR/R~ few %s

19. Mean pT, all particles = 476 MeV spT=7 MeV spT/pT~ 1.5% The mean value depending on the relative particle concentrations!!

20. Mean pT p K p = 451 MeV spT=6 MeV = 578 MeV spT=24 MeV = 744 MeV spT=50 MeV spT/pT~ 1% spT/pT~ 7% spT/pT~ 4%

21. Summary & Conclusions • Event by event fluctuations studies are an important tool to explore the QCD phase diagram, searching for the QGP, and the QCD critical point. • Several recent experimental studies (at the SPS -NA49- and RHIC -STAR, PHENIX...- have focused on the studies of fluctuations in relativistic heavy ion collisions (high temperature and energy densities). • Thanks to its very high particle yield per event, and to the excellent PID capabilities,ALICE will be able to study fluctuations measuring the identified particle spectra (p, K, p) and the particle ratios (K/p, p/p) on an Event-by-Event basis.

22. Summary and Conclusions – cont’d • Temperature fluctuations: statistical fluctuations of the order of few percent for p, K and p. • Particle ratios: statistical fluctuations of the order of few percent for both K/p andp/p. • Mean pT: statistical fluctuations of the order of few percent for p, K and p and for inclusive spectra. Any other contribution from dynamical fluctuations due to new physics will result in an increase of the observed values • The results presented herein strongly depend on the assumed dNch/dy. • HIJING simulation: dNch/dy ~ 4500; • RHIC results suggest a reduction by a factor ~ 2÷3 in the data. E-by-E studies still feasible

23. Work in Progress • E-by-E fluctuation analysis on p-p collisions • Multiplicity fluctuations • Effect of Jets and Minijets

24. Back-Ups

25. The T-μ QCD Phase Diagram Critical end point ? T Quark-Gluon Plasma Chiral symmetry restored Hadronic matter 1st order line ? Color superconductor Chiral symmetry broken B Nuclei Neutron stars No sharp boundary between hadronic matter and QGP!!! QCD prediction: @ very high temperatures and energy densities, a Phase Transition from Hadronic Matter to the QGP occurs. What kind of phase transition? But really a phase transition or a crossover? LHC • Continuous transition for small chemical potential at: • Tc~ 170 MeV • ec~ 0.7 GeV/fm3 • Lattice calculations: crossover at μb~ 0 • Many parameters involved

26. Experiments at the LHC CMS LHC Designed for high pT physics in p-p collisions ALICE Dedicated LHC HI experiment ~ 9 km ATLAS CERN

27. The ALICE Physics Program • Probes of deconfinement & chiral symmetry restoration • Global characteristics of the fireball (Evt by Evt) • Heavy ion observables in ALICE -Multiplicities & Et distributions, -HBT Correlations, elliptic and transverse flow, -hadron ratios and spectra, -Evt-by-Evt fluctuations -… -Charmonium and Bottomonium states, -strangeness enhancement, resonance modification, -jet quenching and high pt spectra, -open Charm and Beauty -thermal gradiation,… • p-p and p-A physics in ALICE • Physics of ultra-peripheral heavy ion collisions • Contribution of ALICE to cosmic-ray physics

28. A Large Hadron Collider Experiment - ALICE MUON μ-pairs HMPID PID (RICH) @ high pT • = 5.5 TeV/NN • Designed for dNch/dy|max = 8000 (optimized for 4000) • Lmax = 11027 cm-2s-1 TOF PID TRD Electron ID PMD γ multiplicity ITS Low pT tracking Vertexing TPC Tracking, dE/dx PHOS γ, π0

29. ALICE Tracking • Track Reconstruction has to be performed in a high flux environment • Reconstruction at low pT very delicate (multiple scattering and energy loss) Tracking based on a KALMAN FILTER technique • Simultaneous reconstruction and fitting • Rejection of incorrect space points “on the fly” • Simpler handling of multiple scattering and energy loss effects • Easy extrapolation from one detector to the other

30. ALICE Tracking Strategy After cluster finding, start iterative process through the central tracking detectors, ITS+TPC+TRD: dN/dy =8000 (slice: 2o in q) • Primary Vertex Finding in ITS • Track seeding in outer TPC HMPID • Propagation to the vertex, • tracking in ITS TOF • Back-propagation in TPC • and in the TRD TRD • Extrapolation and connection • with outer PID detectors TPC • Final refit inwards ITS

31. ALICE Tracking Performance Tracking Efficiency / Fraction of Fake Tracks for dN/dy = 2000, 4000, 6000, 8000 Full chain, ITS + TPC + TRD • FordN/dy = 2000÷ 4000, • efficiency > 90%, • fake track probability < 5%!!!

32. PTResolution

33. ALICE Inner Tracking System – ITS Six Layers of silicon detectors for precision tracking in ||< 0.9 Three tecnhnologies: SPD - Silicon Pixel SDD - Silicon Drift SSD - Silicon Strip • 3-D reconstruction (< 100mm) of the Primary Vertex • Secondary vertex Finding (Hyperons, D and B mesons) • Particle identification via dE/dx for momenta < 1 GeV • Tracking+Standalone reconstruction of very low momentum tracks

34. ALICE Time Projection Chamber – TPC Conventional TPC optimized for extreme track densities • Efficient (>90%) tracking in < 0.9 • s(p)/p < 2.5% up to 10 GeV/c • Two-track resolution < 10 MeV/c • PID with dE/dx resolution < 10% Space-Point resolution 0.8 (1.2) mm in xy,(z), occupancy from 40% to 15%

35. ALICE Time Of Flight – TOF Large array at R ~ 3.7 m, covering | | < 0.9 and fullf 122 cm • TOF basic element: • double-stackMultigap RPC strip • Occupancy < 15% (O(105) readout channels) 2x5 gas gaps of 250mm Readout pads 3.5x2.5 cm2 • Extensive R&D, from TB data: • Intrinsic Resolution ~ 40 ps • Efficiency > 99%

36. PID with the ITS p = 0.4 GeV p,K,p signals ~ gaussians Mis-associated Clusters dE/dx (MIP units) PID in the 1/b2 region central PbPb events • 2 measurements out of 4 Layers (SSD, SDD) used in the truncated mean • s(dE/dx) ~ 10% dE/dx (MIP units) p (GeV/c)

37. PID with the TPC central PbPb events • Use maximum signal in cluster, shared clusters not included • Truncated mean with 60% lowest signals protons dE/dx (MIP units) Also some separation in the relativistic rise kaons Pions, 0.4<p<0.5 GeV/c pions p (GeV/c) • Well described by gaussians (@ fixed pT) • dE/dx resolution ~ 6.8% at dN/dy=8000 (5.5% for isolated tracks, or pp collisions) dE/dx (a.u.)

38. PID with the TOF Mis-associated tracks Total System resolution (including track reconstruction) ~90 ps Mass=p·(t2TOF/L2-1)1/2 P(GeV/c) • •k •p Mass (GeV/c2) Pions TOF response gaussianin (tTOF – texp ), • tTOF = measured time of flight • texp = time calculated from tracking • for a given mass hypothesis

39. ALICE PID Performance (&) ITS TPC stand-alone stand-alone TOF ITS & TPC & TOF combined!!! stand-alone Central Pb + Pb HIJING events – kaon case Combining the PID information from different detectors allows a weaker momentum dependence of the efficiency (contamination) which stays higher (lower) or at least equal than with stand-alone detectors!!! p dependence of: efficiency contamination

40. ALICE PID Approach • A common BAYESIAN approach is adopted by every ALICE detector performing PID; • The probabilityw(i|s) to be a particle of type i (i = e, m, p, ...) if a signal s (dE/dx, TOF,...) is detected, is: r(s|i) conditional pdf to get a PID signal s in a detector, if a particle of type i is detected Ci a priori probability to find a particle of type i in the detector Combined PID combining (multiplying) the r(s|i) from different dets • Weaker momentum dependence of the efficiency (contamination) • Efficiency (contamination) higher (lower) or at least equal than with stand-alone detectors

41. Results – T Distributions p K K p p p = 225 MeV sT = 17 MeV = 182 MeV sT=4 MeV = 304 MeV sT = 22 MeV sT/T ~ 2% sT/T ~ 7% sT/T ~ 7%

42. Efficiency Correction Variation K p p K p p = 182 ± 1 MeV/c (was 182) = 225 ± 1 MeV/c (was 225) = 306 ± 2 MeV/c (was 304) = 3.8 MeV/c = 15.7 MeV/c = 22.6 MeV/c No significant change!

43. Contamination Correction Variation p K p p K p = 181 ± 1 MeV/c (was 182) = 227 ± 1 MeV/c (was 225) = 304 ± 2 MeV/c (was 304) = 3.8 MeV/c = 16.0 MeV/c = 22.3 MeV/c No significant change!

44. ITS PID K p p p K p

45. TPC PID K p p p K p

46. TPC || ITS PID p p p K K p

47. TOF PID p K p K p p

48. E-by-E Fluctuations: Observables • Mean Transverse Momentum • Mean Energy • Charge Fluctuations • Particle Ratios • Identified Particle Spectra Particle IDentification plays a crucial role!