1. Matching between charged tracks and electromagnetic calorimeter (EMCAL) clusters in ALICE Alberto Pulvirenti University & INFN Catania ACAT 2007 Conference Amsterdam, 24 April 2007

2. 2 Outlook  The context › the ALICE experiment › the EMCAL detector › the computing framework  The algorithm ingredients › ALICE tracking › EMCAL clusters  Description of the algorithm  Tests and results  Conclusions and perspectives

3. 3 http://www.cern.ch ~9 km LHC SPS CERN The CERN Large Hadron Collider & ALICE

4. 4 …and “worst” expectation forLHC “worst” actual case: RHIC Some numbers about LHC  Pb-Pb collisions at 5.5 A TeV  Expected charged multiplicity › from RHIC data: (dN ch / dy) y=0 = 3000 › design baseline: (dN ch / dy) y=0 = 8000  Luminosity for Pb-Pb: › L max = 1  10 27 cm -2 s -1  Event rate : › 8000 minimum bias coll. / s › ~10 9 events/year › 1% collected

5. 5 The ALICE detector ITS low p t tracking Vertexing ITS low p t tracking Vertexing TPC Tracking, dE/dx TPC Tracking, dE/dx TRD Electron ID TRD Electron ID TOF PID TOF PID HMPID PID at high p t HMPID PID at high p t PHOS ,  0 PHOS ,  0 MUON-Arm  -pairs MUON-Arm  -pairs PMD  multiplicity PMD  multiplicity EMCAL Photons, jets EMCAL Photons, jets

6. 6 AliROOT: the ALICE computing framework STEER Base classes, overal control AliReconstruction  ESD reconstruction Event Summary Data Particle generators DPMJET HIJING HBTP PYTHIAPDF ISAJET Particle transport GEANT3GEANT4FLUKA Analysis HBTJETPWG0-4 Detectors ZDCPHOS EMCALHMPID TOF TRD TPC ITS T0V0PMDMUON Response GeometryCalibration Alignment

7. 7 The ElectroMagnetic CALorimeter (EMCAL) Acceptance  = 1.4  = 100 o

8. 8 The ElectroMagnetic CALorimeter (EMCAL)  12 supermodules › 24 strips in η › 12 (or 6) modules in φ › projective wr. to TPC/TRD sectors  12672 elementary sensors (towers) › 77 alternating layers of 1.44 mm Pb (1% Sb) 1.76 mm polystirene scintillator › radiation length: ~20 X 0  Acceptance: › φ : 80  190 degrees › η : -0.7  0.7

9. 9 EMCAL primary objective: jet study  High energy partons fragmentation  jets  Jets traveling through a dense color medium loose energy through gluon radiation  “jet quenching” EMCAL PROVIDES:  Jet trigger  Improved jet reconstruction up to 200 GeV jets › background reduction › improved energy resolution (including neutrals) Charged only Charged + Neutral RMS [GeV]2115 E cone /E T 0.500.77 Eff.67%80%

10. 10 PID with EMCAL (high momentum particles)    discrimination (  measure of direct photons ) › invariant mass › shower shape analysis  e   discrimination › E (from EMCAL) / p (from tracking) ratio

11. 11 Tracking in ALICE TIME PROJECTION CHAMBER (TPC) up to 180 pt / track [main contribution - seed] INNER TRACKING SYSTEM (ITS) up to 6 pt / track [resolution improvement] TRANSITION RADIATION DETECTOR (TRD) up to 6 pt / track Tracking procedure based on Kalman Filter: 1)Predict track intersection point at a layer of tracking device 2)Choose the cluster which determines the smalles  ² increase 3)Add a cluster  adjust track parameters according to Kalman matrix equations

12. 12 ITSTPCTRD ALICE tracking work flow Seeding & inward track propagation through the TPC Inward track propagation through the ITS Outward track propagation through the ITS Outward track propagation through the TPC Outward track propagation through the TRD Final inward re-fit through all tracking devices, up to the beam pipe time

13. 13 Barrel to EMCAL track matching Implementation in AliROOT framework › “tracker” class  algorithm execution › “track class”  input data  final information EMCAL clusters are not used to update the track state vector Target: › associating to each track the EMCAL cluster generated by its particle (if any) › cleaning the sample of cluster for photon analysis (jets) › adding PID information from EMCAL to high momentum charged tracks

14. 14 Work-flow of the algorithm Search for EMC clusters close to the intersection Create a list of “match candidates” Geometrical CUTS Quality parameter: Track-Cluster distance Each cluster/track is used only in the “best” candidate Save the “surviving” candidates as final information. Propagate track to the EMCAL surface

15. 15 Performance tests Test on single-track events Data: 1 track / event (fixed type) fixed momentum 1, 5, 10, 25, 50, 75, 100 GeV fixed direction Objective: evaluate  /  shift between track hit and reconstructed cluster evaluate typical cluster size (# towers) Test on “box” events Data: (fixed) track / event photons, pions, electrons Random momentum in a fixed range (1-10 GeV) Random direction in a fixed window (EMCAL acceptance) Objective: evaluate efficiency and contamination in a simple multi-track scenario Test on “physical” simulations Proton-Proton collision: PYTHIAPb-Pb collisions: HIJING parameterized Objective: evaluate efficiency and contamination in a “physical” sample with a realistic momentum distribution and signals from neutral particles (as a perturbation factor)

16. 16 Phi and Eta shift between hits and clusters ELECTRONSPHOTONSPIONS

17. 17 Average #digits per particle amp > 1% of total amp > 2% of total amp > 5% of total amp > 10% of total

18. Cluster/Particle energy comparison electrons & photons: ~100% of total pions: ~20% of total

19. 19 Track matching evaluation EfficiencyContamination Geometrical cuts tuned on pion events and used for all tests without changes

20. 20 Efficiency evaluation: “box” of electrons 10 primaries / event50 primaries / event 100 primaries / event 150 primaries / event

21. 21 Efficiency evaluation: “box” of pions 10 primaries / event50 primaries / event 100 primaries / event 150 primaries / event

22. 22 Efficiency evaluation: PYTHIA simulation of minimum bias p-p collisions at 14 TeV

23. 23 Efficiency evaluation: HIJING parameterized (preliminary) dN/dη = 4000

24. 24 Conclusions & perspectives  Track matching code preliminary version implemented within ALICE reconstruction framework › based on Kalman Filter-style track propagation  Efficiency results: › box: good not negligible contamination for high multiplicity (150) › PYTHIA: good › HIJING: good only for very high momenta investigate performances at this track density  Future perspectives: › improve results for high mutiplicity events cluster pattern study

25. 25

26. 26 Work-flow of the algorithm: STEP 1  propagation  Seed: outer “snapshot” of the reconstructed track  Propagate tracks to the EMCAL surface XY plane (transverse to beam) Cluster positions Track intersections with EMCAL

27. 27 Track propagation plane (in track local coords.) not all clusters lie in the same plane (Δy,Δz) LOCAL cuts  (Δφ,Δη) GLOBAL cuts X Track local reference system: rotation of detector plane around Z axis, in order to put it in a plane orthogonal to X axis X = distance of detector plane from origin Z Y

28. 28 Insertion of track matching into global barrel reconstruction work-flow ITS (in – I) TPC (in - I) ITS (out) TPC (out) TRD (out) TOF (matching) ITS (refit) TPC (refit) TRD (refit) Entry point EMCAL (matching)

29. 29 Energy distribution in clusters Portion (%) of total cluster energy per hit tower. L O G s c a l e ! ! ! e (25 GeV)  (25 GeV)

30. 30 ALICE objectives  Heavy ion collisions in a new energy range  Properties of nuclear matter at high temperature and energy density  Formation and study of Quark-Gluon Plasma (QGP) 10 –6 s 10 –4 s 3 m ~10 10 yrs Big Bang QGP QGP Nucleons Nuclei Atoms Today