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First-day observables in p-p and Pb-Pb with ALICE

First-day observables in p-p and Pb-Pb with ALICE. Francesco Prino INFN – Sezione di Torino. INFN, Commissione III, Genova, September 22 nd 2009. Results published in the first year after RHIC startup: Multiplicity of unidentified particles at midrapidity

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First-day observables in p-p and Pb-Pb with ALICE

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  1. First-day observables in p-p and Pb-Pb with ALICE Francesco Prino INFN – Sezione di Torino INFN, Commissione III, Genova, September 22nd 2009

  2. Results published in the first year after RHIC startup: Multiplicity of unidentified particles at midrapidity  PHOBOS, sent to PRL on July 19th 2000  PHENIX, sent to PRL on Dec 21th 2000 Elliptic flow of unidentified particles  STAR, sent to PRL on Sept 13th 2000 Particle to anti-particle ratios  STAR, sent to PRL on Apr 13th 2001  PHOBOS, sent to PRL on Apr 17th 2001  BRAHMS, sent to PRL on Apr 28th 2001 Transverse energy distributions  PHENIX, sent to PRL on April 18th 2001 Pseudorapidity distributions of charged particles  PHOBOS, sent to PRL on June 6th 2001  BRAHMS, sent to Phys Lett B on Aug 6th 2001 Elliptic flow of identified particles  STAR, sent to PRL July 5th 2001 … then came the high pT particle suppression from PHENIX (sent to PRL on Sept 9th 2008) 9 years ago: first data at RHIC First 10k-20k events, fast analysis statistics<≈100k events, longer analysis time due to the need of PID, detector calibration, combination of different detectors

  3. Outline • Three examples of “first day” observables • Multiplicities of unidentified particles • First-day analysis from the first 10-20 k events both in p-p and Pb-Pb • Abundances and pT spectra of identified hadrons (p, K, p) • Small statistics needed both in p-p and Pb-Pb, longer analysis time • Elliptic flow • First-day analysis from the first 20 k Pb-Pb events • For each observable • Physics motivation (in p-p and Pb-Pb) • What do we need?  The tools • Interaction vertex reconstruction, centrality determination, tracking, PID ... • Analysis algorithms, corrections and systematics • Where we are?  Analysis readiness

  4. First tool: ALICE at the LHC

  5. Second tool: the Grid • Productions • Several production dedicated to p-p first physics in 2009 • 4 M events generated, reconstructed and analyzed specifically for first physics • Plus 108 min. bias p-p events • 142 k Pb-Pb events • Analysis • Organized as analysis tasks (wagons of a common analysis train) running on the grid on ESD/AOD

  6. Multiplicity of unidentified particles

  7. Physics motivation • p-p @ √s=900 GeV • First measurement at the LHC • Comparison with existing measurements • p-p @ √s=7-14 TeV • Test (soft) particle production models in a new energy regime • In hadronic and nuclear collisions particle production is dominated by (non-perturbative) processes with small momentum transfer. Many models, but understanding of multiplicities based on first principles is missing. Nominal LHC energy • Multiplicity in Pb-Pb contains information about: • Energy density of the system (via Bjorken formula) • Geometry (centrality) of the collision

  8. increasing s – decreasing x RHIC results and modeling • Factorized dependence of dNch/dhmax on centrality and s reproduced by models based on gluon density saturation at small values of Bjorken x • Pocket formula: • l and d from ep and eA data • N0 only free parameter • Armesto Salgado Wiedemann, PRL 94 (2005) 022002 • Kharzeev, Nardi, PLB 507 (2001) 121.

  9. Towards the LHC (I) • Extrapolation of dNch/dhmax vs s • Fit to dN/dh  ln s • Saturation model (dN/dh  sl with l=0.288) • Clearly distinguishable with the first 10k events at the LHC Saturation model Armesto Salgado Wiedemann, PRL 94 (2005) 022002 Central collisions Models prior to RHIC Extrapolation of dN/dhln s 5500

  10. Towards the LHC (II) • Extrapolation of limiting fragmentation behavior • Persistence of extended longitudinal scaling implies that dN/dh grows at most logarithmically with s  difficult to reconcile with saturation models Saturation model dN/dh≈ 1600 Log extrapolation dN/dh≈ 1100 • Borghini Wiedemann, J. Phys G35 (2008) 023001

  11. ALICE: figure of merit • Wide angular coverage • about 9 units in pseudorapidity • Different detection techniques • Tracks in central barrel (ITS+TPC) • Tracklets in SPD • Occupancy in FMD

  12. ZP ZN Φ 5 η -10 -5 0 10 Φ -10 -5 0 5 10 η Φ 5 η -10 -5 0 10 Tools: trigger and tagging of diffractive events in p-p • Minimum Bias trigger: • SPDFastOr or V0A or V0C • Also ZDCs and ZEM can provide a p-p MB trigger (ZPA or ZNA or ZPC or ZNC or ZEM) • Trigger efficiency (from Pythia @ 3.5+3.5 TeV) =91% • Trigger efficiency independent of multiplicity in central barrel • Tagging of diffractive events: • based on signal only on one side • Signal in ZNC or ZPC • No signal in ZNA and ZPA and ZEM Non-diffractive inelastic (ND) s≈65 mb From 50k PYTHIA p-p @ 7 TeV (LHC09b12) SD trigger efficiency: 52% SD trigger purity: 50% ND events in MB sample: 68% ND events tagged as SD: 5.2% Single Diffraction (SD) s≈10mb M Double Diffraction (DD) s≈7 mb

  13. Tools: centrality determination in Pb-Pb • Centrality measurement from EZDC (deposited energy in ZDC) vs. EZEM (=deposited energy in ZEM) correlation • Centrality classes defined by selecting events from the correlation corresponding to certain fractions of the inelastic cross section EZDC vs. EZEM b  Nparticipants Glauber model Nparticipants

  14. SPD RecPoints Good (crossing the beam pipe, small DCA) tracklets Fake (rejected by the vertexing algo) tracklets Primary vertex Tools: Vertex reconstruction (I) • Reconstruction from SPD tracklets • Tracklets = pairs of associated reconstructed points in the two innermost ITS layers

  15. Tools: Vertex reconstruction (II) • Reconstruction from SPD tracklets • Available before tracking, used to seed the Kalman filter • OK for multiplicity analyses (high efficiency, sufficient resolution) • For 80% of triggered events reconstruction in 3D available, for 15% (low multiplicity) of triggered events only Z coordinate

  16. Multiplicity from tracklets • Features: • Large h and pT acceptance • Less stringent calibration needs • Suitable for the very first data • First measurement that ALICE will be able to perform in p-p and Pb-Pb • Several corrections needed • Background from secondaries • Algorithm efficiency • Detector efficiency+acceptance • Vertexing efficiency • Trigger efficiency p-p @ 7 TeV (Pythia) - LHC09b12

  17. Multiplicity and pT spectra of identified particles

  18. y x Physics motivation: spectra • p-p @ 900 GeV • Comparison with existing measurements • p-p @ 7/10/14 TeV • Test for particle production models that combine perturbative QCD for the description of hard partonic interaction and phenomenological approaches for the soft component of the spectrum • Reference for pT spectra in Pb-Pb • Pb-Pb: slope of pT spectra in the soft-pT region (< 1 GeV/c) sensitive to temperature at thermal freeze-out and radial flow • Flow = collective motion superposed on top of the thermal motion • Due to large pressures arising from compressing and heating the nuclear matter • Test of hydrodynamics models

  19. Physics motivation: abundances • Hadron abundances: • Small s (< 5 GeV): • fireball dominated by stopped particles • High baryonic content • Importance of isospin and quarks “stopped” from colliding nuclei • Large s (> 20 GeV): • Fireball dominated by produces particles • Low baryonic content • Mass hierarchy ( Np > NK > Np )

  20. Statistical hadronization models • Fit measured particle abundances (or ratios) with hadron densites from grand canonical partition function • Temperature T and chemical potential mB are free parameters

  21. Towards the LHC • Extrapolations to LHC of T and mB trend vs. √s • TLHC = 161±4 MeV • mBLHC=0.8 MeV • A. Andronic et al. in arXiv:0711.0974 [hep-ph]

  22. Tools: tracking - ITS+TPC+TRD • Track reconstruction: • Start from TPC signals in the outer pads + SPD vertex -> move inward • Match TPC tracks to points in outer ITS layer -> follow the track until the innermost ITS layer • Back propagate to outer TPC radius and attach TRD points • Extrapolate to outer detectors (TOF, PHOS, HMPID, EMCAL) • Refit the track inward (TRD, TPC, ITS) and propagate to SPD vertex MC simulations: p-p

  23. Tools: tracking - ITS standalone • Group clusters in l,f windows on the 6 layers • Starting point (seed): SPD vertex + a cluster in one of the inner ITS layers (1, 2 or 3) • Extrapolation to next layer taking into account trajectory curvature • N iterations increasing at each step the l,f window size • Track fitted with Kalman filter • Goals: • Recover tracks missed by the TPC • Extend low-pT reach w.r.t. TPC+ITS tracks

  24. Tools: PID • Hadron identification in ALICE barrel based on: • Momentum from track parameters • Velocity related information (dE/dx, time of flight, Čerenkov light...) specific for each detector • Different systems are efficient in different momentum ranges and for different particles EMCAL +

  25. Particle identification with TOF • Features: • Large acceptance (surface = 140 m2) • High efficiency (>95%) • Excellent time resolution (<100 ps) • Nominal resolution including all possible contributions = 80 ps • High granularity (105 channels) 5 modules in z 18 modules in 

  26. Hadron spectra with PID in TOF • Efficiency x acceptance for p, K , p including: • Tracking (ITS+TPC+TRD) efficiency • Track-TOF matching efficiency • ≈80% for p with 1.75<pT<2 GeV/c (including dead regions of TOF) • Identification efficiency • Spectra from few 106 p-p MB events (first day of data taking) • Good accuracy up to pT 2.5 GeV/c • For pT > 2.5 GeV/c correction for contamination in PID needed

  27. Elliptic flow

  28. y z x Anisotropic transverse flow • In heavy ion collisions with b≠0 the impact parameter selects a preferred direction in the transverse plane • The fireball shows an initial geometrical anisotropy with respect to the reaction plane • Re-scatterings among produced particles convert this initial geometrical anisotropy into an observable momentum anisotropy • Anisotropic transverse flow is a collective motion giving rise to a correlation between the azimuth [=tan-1 (py/px)] of the produced particles and the impact parameter (reaction plane) • The initial particle momentum distribution is isotropic • Pressure gradients in the transverse plane are anisotropic (=  dependent) • Larger pressure gradient in the x,z plane (along impact parameter) that along y Reaction plane

  29. Elliptic flow • Elliptic flow = 2nd harmonic in Fourier expansion of particle  distributions • At time = 0: • Geometrical anisotropy • Isotropic distribution of momenta • Interaction among constituents • Transform initial spatial anisotropy into a momentum anisotropy • Hydrodynamics to describe the system evolution from equilibration time until thermal freeze-out • The mechanism is self quenching • The driving force dominate at early times

  30. Towards the LHC (I) • Ideal hydro reproduces central collisions at RHIC • Fluid created in Au-Au at RHIC has exceptionally low viscosity • But also hints for incomplete equilibration / non zero viscosity • E.g. no hint for saturation in v2 vs. dN/dy 0.3 40 45 50

  31. Towards the LHC (II) • Extended longitudinal scaling of v2vsh • Naturally accounted in a low-density limit scenario (with v2dN/dh) • Extrapolations of ideal hydrodynamics from RHIC to LHC predict values not exceeding v2=0.06 at h=0 • The first 20,000 Pb-Pb events at LHC will bring new pieces of evidence to understand the picture

  32. Tools: estimate the reaction plane • Reaction plane estimated from the (second harmonic) anisotropy of reconstructed tracks in ITS+TPC+TRD • Event plane = estimator of the unknown reaction plane • Event plane resolution depends on • v2 of produced particles • Event multiplicity • Correct v2 for event plane resolution:

  33. Centroid resolution vs Neutron Multiplicity V1=20% GEANT-based simulation Tools: reaction plane from ZDC • Reaction plane estimated by measuring the bounce-off of the spectator neutrons in ZDC • Independent estimate, reduced non-flow correlations • Allow to study v1 and the sign of v2 • Resolution on ZDC event plane depends on: • v1 of spectator neutrons • Neutron multiplicity (on a lesser extent) <cos(φZN-φRP)> vs centrality

  34. Elliptic flow: analysis methods • Comparison between three different analysis methods implemented in ALICE analysis framework and applied to 28000 Pb-Pb like events (GeVSim) • Methods based on multiparticle correlation (LYZ, v2{4}) less biased by non-flow correlations (jets, particle decays) • If non flow correlations are not included in simulations all methods correctly estimate flow • In presence of two-particle non-flow, method based on two-particle correlations (v2{2}) give biased results

  35. Conclusions • Successful commissioning of detectors involved in “first day” observables • ITS, TPC and TOF took cosmics since August 17th till September 13th. Data being analyzed for calibration and alignment. • More cosmics in the next weeks. • Analysis tools ready for analysis of “first day” observables • Analysis code ready and tuned on the Monte Carlo samples produced on the Grid • Acceptance/efficiency corrections extracted from the Monte Carlo samples produced on the Grid • Study of systematics on-going and in good shape • Everything ready for first p-p collisions at LHC

  36. Thanks to … • Nora De Marco, GraziaLuparello, ChiaraOppedisano, Francesco Noferini, MariellaNicassio, LucianoRamello • For providing me a significant fraction of the material shown in this presentation • Paolo Giubellino, Massimo Masera and LucianoRamello • For suggetions/discussions/criticism on the topics and the analyses to be presented

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