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Correlations and Fluctuations WorkshopFirenze, July 9 th 2006 Event-by-Event physics in ALICE Chiara Zampolli ALICE-TOF Centro E. Fermi (Roma), INFN (Bologna)

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Presentation on theme: "Correlations and Fluctuations WorkshopFirenze, July 9 th 2006 Event-by-Event physics in ALICE Chiara Zampolli ALICE-TOF Centro E. Fermi (Roma), INFN (Bologna)"— Presentation transcript:

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

2 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli Outline Introduction PID performance Identified Particle Spectra Particle Ratios Mean p T Summary and Conclusions

3 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli 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 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli Event by Event Fluctuations FLUCTUATIONS Statistical Finite number of particles produced Experimental acceptance and resolution Statistical Finite number of particles produced Experimental acceptance and resolution Dynamical Dynamics of the collision Evolution of the system 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 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli Some Experimental Results K/ ratio STAR STAR, = 200 GeV Mean p T NA49, = 17.2 GeV What will ALICE sensitivity be?

6 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli 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 p T Particle Ratios Multiplicity Conserved Quantities (Charge) HBT radii Balance Function Flow DCC... http://aliceinfo.cern.ch/http://aliceinfo.cern.ch/, ALICE PPR II Particle IDentification plays a crucial role!

7 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli ALICE PID separation @ 3 separation @ 2 (dE/dx)

8 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli Monte Carlo Event Sample p t > 0.15 GeV/c, -0.9 < < 0.9 Kp average # generated 6750720380 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 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli Primary Track Selection 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 K p efficiency K p

10 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli PID Performance - Definitions The PID performance is evaluated in terms of: efficiency = contamination = overall efficiency = = number of correctly/uncorrectly identified particles = number of generated primaries N = number of reconstructed particles to which the PID procedure is applied

11 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli Combined PID – ITS || TPC || TOF K p 0.15 < p T < 4 GeV/c Kp ID5150360280 wrongly ID1557413 Efficiencycontamination KP Kp 98%78%92%3%20%4% overall efficiency Kp 40%70% K p

12 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli Generated vs Identified Spectra Generated Identified (w) Identified (t + w) K p

13 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli p from weak decays p Generated p Reconstructed p from Generated p Generated Reco p from 3851308 Per event:

14 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli Fitting of the Spectra Event by event fitting procedure for p T spectra: exponential function,T = slope parameter, connected to the Correction of the identified spectra taking into account: Limited acceptance and reconstruction efficiency of the detectors: ε acc Transverse momentum reconstruction efficiency: ε p PID efficiency: ε PID PID contamination: C PID kinetical freeze-out temperature

15 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli Results – Single Event, p T spectra Temperature (MeV) Kp 186 ± 2208 ± 8319 ± 13 Fit range: 0.25 < p T < 2 GeV/c K Generated Reconstructed i.e. corrected! p

16 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli Results – T Distributions = 182 MeV T = 3 MeV = 226 MeV T = 13 MeV = 303 MeV T = 21 MeV T /T ~ 0.5% T /T ~ 6% T /T ~ 7% K p

17 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli 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 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli Particle Ratios K/ R = 0.106 σ R = 0.009 R = 0.106 σ R = 0.009 p/ R = 0.055 σ R = 0.006 R = 0.055 σ R = 0.006 σ R /R ~ few %s

19 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli Mean p T, all particles = 476 MeV p T = 7 MeV p T /p T ~ 1.5% The mean value depending on the relative particle concentrations!!

20 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli Mean p T K p = 451 MeV p T = 6 MeV = 578 MeV p T = 24 MeV = 744 MeV p T = 50 MeV p T /p T ~ 1% p T /p T ~ 4% p T /p T ~ 7%

21 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli 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 (, K, p) and the particle ratios (K/, p/ ) on an Event-by-Event basis.

22 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli Summary and Conclusions – contd Temperature fluctuations: statistical fluctuations of the order of few percent for K and p. Particle ratios: statistical fluctuations of the order of few percent for both K/ and p/ Mean p T : statistical fluctuations of the order of few percent for, 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 dN ch /dy. HIJING simulation: dN ch /dy ~ 4500; RHIC results suggest a reduction by a factor ~ 2÷3 in the data. E-by-E studies still feasible

23 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli Work in Progress E-by-E fluctuation analysis on p-p collisions Multiplicity fluctuations Effect of Jets and Minijets

24 Correlations and Fluctuations WorkshopFirenze, July 9 th 2006 Back-Ups

25 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli Color superconductor B Hadronic matter Critical end point ? Nuclei Chiral symmetry broken Chiral symmetry restored Neutron stars T 1 st order line ? Quark-Gluon Plasma Continuous transition for small chemical potential at: T c ~ 170 MeV c ~ 0.7 GeV/fm 3 Lattice calculations: crossover at μ b ~ 0 Many parameters involved The T-μ QCD Phase Diagram 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

26 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli Experiments at the LHC ATLAS CMS Designed for high p T physics in p-p collisions ALICE Dedicated LHC HI experiment ~ 9 km CERN LHC

27 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli -Multiplicities & Et distributions, -HBT Correlations, elliptic and transverse flow, -hadron ratios and spectra, -Evt-by-Evt fluctuations -… The ALICE Physics Program -Charmonium and Bottomonium states, -strangeness enhancement, resonance modification, -jet quenching and high pt spectra, -open Charm and Beauty -thermal radiation,… Probes of deconfinement & chiral symmetry restoration Global characteristics of the fireball (Evt by Evt) Heavy ion observables in ALICE p-p and p-A physics in ALICE Physics of ultra-peripheral heavy ion collisions Contribution of ALICE to cosmic-ray physics

28 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli A Large Hadron Collider Experiment - ALICE ITS Low p T tracking Vertexing TPC Tracking, dE/dx TRD Electron ID TOF PID HMPID PID (RICH) @ high p T PHOS γ, π 0 PMD γ multiplicity MUON μ-pairs MUON μ-pairs = 5.5 TeV/NN Designed for dN ch /dy| max = 8000 (optimized for 4000) L max = 1 10 27 cm -2 s -1

29 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli ALICE Tracking Track Reconstruction has to be performed in a high flux environment Reconstruction at low p T 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 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli ALICE Tracking Strategy dN/dy =8000 (slice: 2 o in HMPID TOF TRD TPC ITS Final refit inwards Primary Vertex Finding in ITS Extrapolation and connection with outer PID detectors After cluster finding, start iterative process through the central tracking detectors, ITS+TPC+TRD: Propagation to the vertex, tracking in ITS Back-propagation in TPC and in the TRD Track seeding in outer TPC

31 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli ALICE Tracking Performance Tracking Efficiency / Fraction of Fake Tracks for dN/dy = 2000, 4000, 6000, 8000 For dN/dy = 2000 ÷ 4000, efficiency > 90%, fake track probability < 5%!!! For dN/dy = 2000 ÷ 4000, efficiency > 90%, fake track probability < 5%!!! Full chain, ITS + TPC + TRD

32 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli P T Resolution

33 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli ALICE Inner Tracking System – ITS Six Layers of silicon detectors for precision tracking in | |< 0.9 3-D reconstruction (< 100 m) of the Primary Vertex Tracking+Standalone reconstruction of very low momentum tracks Particle identification via dE/dx for momenta < 1 GeV SPD - Silicon Pixel SDD - Silicon Drift SSD - Silicon Strip Secondary vertex Finding (Hyperons, D and B mesons) Three tecnhnologies:

34 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli ALICE Time Projection Chamber – TPC Efficient (>90%) tracking in < 0.9 (p)/p < 2.5% up to 10 GeV/c Conventional TPC optimized for extreme track densities 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 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli ALICE Time Of Flight – TOF Large array at R ~ 3.7 m, covering | | < 0.9 and full Extensive R&D, from TB data: Intrinsic Resolution ~ 40 ps Efficiency > 99% Readout pads 3.5x2.5 cm 2 122 cm TOF basic element: double-stack Multigap RPC strip Occupancy < 15% (O(10 5 ) readout channels) 2x5 gas gaps of 250mm

36 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli PID with the ITS dE/dx (MIP units) PID in the 1/ 2 region 2 measurements out of 4 Layers (SSD, SDD) used in the truncated mean (dE/dx) ~ 10%, K,p signals ~ gaussians p = 0.4 GeV dE/dx (MIP units) p (GeV/c) Mis-associated Clusters central PbPb events

37 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli PID with the TPC kaons pions protons p (GeV/c) dE/dx (MIP units) Use maximum signal in cluster, shared clusters not included Truncated mean with 60% lowest signals dE/dx (a.u.) Well described by gaussians (@ fixed p T ) dE/dx resolution ~ 6.8% at dN/dy=8000 (5.5% for isolated tracks, or pp collisions) Pions, 0.4 { "@context": "http://schema.org", "@type": "ImageObject", "contentUrl": "http://images.slideplayer.com/2/584195/slides/slide_37.jpg", "name": "Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli PID with the TPC kaons pions protons p (GeV/c) dE/dx (MIP units) Use maximum signal in cluster, shared clusters not included Truncated mean with 60% lowest signals dE/dx (a.u.) Well described by gaussians (@ fixed p T ) dE/dx resolution ~ 6.8% at dN/dy=8000 (5.5% for isolated tracks, or pp collisions) Pions, 0.4

38 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli PID with the TOF TOF response gaussian in (t TOF – t exp ), t exp = time calculated from tracking for a given mass hypothesis t TOF = measured time of flight Pions Mass (GeV/c 2 ) P (GeV/c) Mass= p·(t 2 TOF /L 2 -1) 1/2 k p Total System resolution (including track reconstruction) ~ 90 ps Mis-associated tracks

39 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli efficiency contamination p dependence of: ALICE PID Performance (&) Central Pb + Pb HIJING events – kaon case ITS stand-alone TPC stand-alone TOF stand-alone 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!!! ITS & TPC & TOF combined!!!

40 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli ALICE PID Approach Weaker momentum dependence of the efficiency (contamination) Efficiency (contamination) higher (lower) or at least equal than with stand- alone detectors Weaker momentum dependence of the efficiency (contamination) Efficiency (contamination) higher (lower) or at least equal than with stand- alone detectors A common BAYESIAN approach is adopted by every ALICE detector performing PID; The probability w(i|s) to be a particle of type i (i = e,,,...) 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 C i a priori probability to find a particle of type i in the detector Combined PID combining (multiplying) the r(s|i) from different dets

41 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli Results – T Distributions K p = 182 MeV T = 4 MeV = 225 MeV T = 17 MeV = 304 MeV T = 22 MeV T /T ~ 2% T /T ~ 7% K p

42 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli Efficiency Correction Variation Kp = 182 ± 1 MeV/c (was 182) = 225 ± 1 MeV/c (was 225) = 306 ± 2 MeV/c (was 304) No significant change! K p = 3.8 MeV/c = 15.7 MeV/c = 22.6 MeV/c

43 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli Contamination Correction Variation K p = 181 ± 1 MeV/c (was 182) = 227 ± 1 MeV/c (was 225) = 304 ± 2 MeV/c (was 304) No significant change! K p = 3.8 MeV/c = 16.0 MeV/c = 22.3 MeV/c

44 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli ITS PID K p Kp ID5200330270 wrongly ID31512530 Efficiencycontamination KP Kp 97%63%85%6%38%13% K p overall efficiency Kp 31%65%

45 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli TPC PID K p KP ID5380220225 wrongly ID310356 Efficiencycontamination KP Kp >99%50%76%6%15%3% K p overall efficiency Kp 25%58%

46 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli TPC || ITS PID K p Kp ID5200310260 wrongly ID2307515 Efficiencycontamination KP Kp 98%32%85%4%25%6% K p overall efficiency Kp 33%65%

47 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli TOF PID K p Kp ID5200360260 wrongly ID1008010 Efficiencycontamination KP Kp 98%76%86%2%22%5% K p overall efficiency Kp 39%66%

48 Firenze, July 9 th 2006Correlations and Fluctuations Workshop Chiara Zampolli E-by-E Fluctuations: Observables Mean Transverse Momentum Mean Energy Charge Fluctuations Particle Ratios Identified Particle Spectra Particle IDentification plays a crucial role!


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