1. 1 Guénolé BOURDAUD -jet physics with the EMCal calorimeter of the ALICE experiment at LHC La physique des -jets avec le calorimètre EMCal de lexpérience ALICE au LHC

2. 2 outline 1. Context 2. Previous experimental observations 3. ALICE @ LHC : new possibilities 4. -jet reconstruction algorithms 5. identification 6. jet reconstruction 7. Hump-backed plateau determination 8. Summary & outlooks

3. 3 Context Quark and gluon plasma Heavy ion collisions Hard processes, jets, -jets

4. 4 Quark Gluon Plasma Dense medium of deconfined partons LHC Nuclear mater time Initial state final state PLASMA Hadronisation Hard processes QCD predictions : Energy density > 1 GeV/fm 3 Temperature > 200 MeV Baryonic density > 5-10 x normal nuclear matter density

5. 5 Hard probes in QGP study, historical view ~98%~ 50%~ 2% hard / tot Lessons from RHIC : Need dedicated detectors for high p T and Hard probes Alice was designed before RHIC results. EMCal QGP Initial state (partonic) observations. Explosion of hard probes JET-QUENCHING New matter state. Final state (hadronic) observations. Emergence of hard probes. Measurement 200920001994 Global Observables ~1994~1990~1980 Start of construction LHCRHICSPS Hard processes : Creation or diffusion of high p T particles

6. 6 Hard processes & jets Lead to jets of particles, from hadronisation of a high p T parton high p T parton jet Parton suffers energy loss travelling through the new medium Jet multiplicity modification Jet energy redistribution Jet-quenching phenomenon Transverse plan (azimuthal) Gluon radiation Jet modification

7. 7 -jet correlation g+q +q (Compton) q+q +g (Annihilation) Gluon radiation Jet attenuation : not perturbed by medium -jet estimates the initial jet energy -jet limits the azimuthal acceptance to search the jet Pertinent to probe QGP : A calorimeter (EMCal@ALICE) for A tracking system (Central trackers @ ALICE) for jet

8. 8 Use -jets to study medium induced jet modification (via fragmentation function modification) Use EMCal and tracking system from ALICE @ LHC to reconstruct -jets Goal

9. 9 Previous experimental observations STAR@RHIC Azimuthal correlation of hadrons First -jet study

10. 10 RHIC Relativistic Heavy Ion Collider, BNL (USA) s NN = 200 GeV (Au-Au) s NN = 500 GeV (p-p) = 5 GeV/fm 3

11. 11 Jet-quenching at RHIC Suppression of jet azimuthal correlation Adam et. al. Phys. Rev. Lett. 91, 072304 (2003) -hadron correlation Difficulties : direct- identification First step for -jet study di-hadron correlation STAR : T. Hallman QM2008

12. 12 ALICE @ LHC : new possibilities ALICE@LHC Dedicated experiment Access to new observables

13. 13 LHC Large Hadron Collider, CERN (Geneva) s NN = 5500 GeV (Pb-Pb) X 28 s NN = 14000 GeV (p-p) = 15-60 GeV/fm 3 X 3-12

14. 14 Central tracking + EMCal : dedicated to -jets Tracking-PID : ITS+TPC+(TOF, TRD) –Charged particles | | < 0.9 –Excellent momentum resolution up to 100 GeV/c ( p/p < 6%) –Tracking down to 100 MeV/c EMCal –Energy from neutral particles –Pb-scintillator, 13k towers – = 110, | | < 0.7 –Energy resolution ~10%/E PHOS –High resolution electromagnetic spectrometer –| | < 0.12 –220 < < 320 –Energy resolution: E /E = 3%/ E

15. 15 -jet with ALICE Central tracking & EMCal Full jet reconstruction with tracking. Jet energy with the gamma in EMCal ~ 10 000 -jets/year in ALICE ( in EMCal) for E> 30 GeV Lower statistics than di-jets (4 orders of magnitude) Need the high geometrical acceptance of EMCal

16. 16 x p-p Pb-Pb Highlight the jet energy redistribution Hump-backed plateau : distribution of the energy in the jet = ln[p T (jet)/p T (part)] Tracking Calorimeter Borghini-Wiedemann, hep-ph/0506218

17. 17 Feasibility with ALICE Simulation used to : Test capacity of the detectors to identify and reconstruct -jets Determine parameters of the method Test efficiency Event generator Particle propagation Detector response -jet reconstruction algorithm PYTHIA for p-p collisions HIJING for Pb-Pb simulation PYQUEN for quenching effect Possibility to force -jet events Tuneable : energy, direction… GEANT & detectors geometry Analysis framework AliRoot

18. 18 -jet reconstruction algorithm Schematical view

19. 19 -jet reconstruction algorithm Azimutal plan

20. 20 -jet reconstruction algorithm 180°

21. 21 identification Shower shape Bayesian method Efficiency

22. 22 Particle IDentification Shower shape 0 : Cluster in EMCal Higher energy ° ° ° Gustavo Conesa : Nucl. Phys. A 2006.10.039 1 tower

23. 23 Particle IDentification Bayesian method + Shower shape analysis = particle identification Shower shape Bayesian method : conditional probability : Distinguish different kind of objects, knowing the distribution of a parameter for each kind of objects. If distributions are different enough, an identification is possible. x dN/dx Bayesian method

24. 24 0 distribution Simulation to obtain the distributions :, 0 and other hadrons are simulated with energies 5<E<60 GeV 3000 events of a single particle in EMCal acceptance 3 kinds of particles 13 energies 0 obtains from reconstructed data (ESD) Parameterization : 0 distributions are parameterized as a function of the energy Reconstruction of the PID weights for an unknown particle : From 0 distributions, unknown particle energy & 0

25. 25 Particle IDentification hadrons °

26. 26 0 Parametrisation for 0 Gaussian + Landau : 6 parameters Mean value of Gaussian distribution Multiplicative constant of Landau distribution 0 2 dn/d 0 2 27 GeV

27. 27 PID efficiency Simulation Each event contents 3 particles of each kind (, °, hadrons), with energies from 5 to 60 GeV in EMCal acceptance 3000 events mixed with p-p collisions @14 TeV (PYTHIA) 3000 events mixed with Pb-Pb collisions @ 5.5 TeV (HIJING) Calculating unknown particle PID weights from : 0 distributions Measured energy of the unknown particle Measured 0 of the unknown particle (Method implemented in AliRoot framework)

28. 28 0 Identification Identified : W(i) > 0,3

29. 29 Photon identification Identified : W(i) > 0,3 Can identify photon for a -jet study !

30. 30 -jet reconstruction candidate selection Azimuthal correlation Energy correlation Background fluctuations Jet axis determination

31. 31 From photon to -jet candidate 1.Energy > 30 GeV (maximization direct / inclusive photons) hep-ph/0311131 2.PID W,3 (only photons) 3.Isolation criteria (no decay photons) Isolation : photon without energetic particles in the photon area p-p : no particles E > 1 GeV in cone Rc = 0,4 Pb-Pb : no particles E > 3 GeV in cone Rc = 0,3 Gustavo Conesa : CERN Thesis-2006-050 (2005)

32. 32 -jet : correlation The jet is emitted back-to-back with the photon in azimuthal angle 90 % of the -jets with (+/- 0.3 rad) Determined with 100 GeV -jets in p-p collisions (no background) 180°

33. 33 -jet : energy correlation E jet / E is the fraction of reconstructed energy of the jet R C =0.7 100 GeV -jets

34. 34 Pb-Pb : background Need jet energy higher than background fluctuations Jet energy Mean bkg energy bkg fluctuations E

35. 35 Pb-Pb : background Compromise : Low R c for bkg limitation High R c to maximize E jet in cone With E jet = 30 GeV : – R c = 0,25 – E jet / (bkg) = 2

36. 36 Jet axis reconstruction p-p Pb-Pb -jets @ 100 GeV Simulation : 1 minute for a p-p collision (PYTHIA) several hundreds of particles 10 hours for a Pb-Pb collision (HIJING) several tens of thousands particles Reconstruction of -jet : Developped in AliRoot, 1GB of a daily evoluting code, no (ever) retro-compatibility.

37. 37 Hump-Backed Plateau (HBP) determination -jet without background (p-p) : PYTHIA simulation -jet with background (Pb-Pb) : PYTHIA (signal) merged with HIJING (bkg) simulation -jet quenched : PYQUEN, processed on PYTHIA events 100 GeV -jets HBP reconstruction in p-p collisions HBP modification without background effect HBP modification with background effect HBP modification with realistic -jets

38. 38 Hump-backed plateau in p-p collisions (100 GeV -jets) – Rc dependence – Low variations for high Rc (> 0,7) – Rc = 0,7 to determine HBP distribution

39. 39 HBP Modification without background (100 GeV -jet) Without bkg : modification of hump-backed plateau easy to measure

40. 40 Pb-Pb : background (100 GeV -jet) How to subtract the background ?

41. 41 Pb-Pb : subtract background (100 GeV -jet) Background of low p T particles pollutes HBP for >3.8 Background subtraction extends HBP measurement up to = 4.2

42. 42 Background effect (100 GeV -jet) Subtraction efficient for 1< <4,2 with 100 GeV - jets Need to test with realistic -jet energy (about 30 GeV)

43. 43 Modification of HBP with realistic -jets Select -jets with 30<E<40 GeV Error <10% for 0.5< < 3.2 Main error contribution : background Reconstructed hump-backed plateau show the two domains : Decrease of high p T particles Enhancement of low p T particles Highlight the jet energy redistribution Realistic spectrum : 1 year g-jets @ LHC simulated from 30 to 100 GeV

44. 44 Summary Particles identification : For 7<E<50 GeV : It is possible to differentiate photons, neutral pions other hadrons (efficiency ~ 50 % et purity ~ 60 %) This Method has been integrated in AliRoot framework. High p T photons are identifiable in EMCal -jets : It is possible to reconstruct and study -jets with energy higher than 30 GeV. The range for hump-backed plateau study is 0,5< <3,2 (error <10% (Pb-Pb)).

45. 45 Particle IDentification – Add a track matching with TPC & EMCal to improve particle identification – Add an automatic procedure of 0 parametrisation -jets – Improve the background estimation – Test other algorithms for jet reconstruction – Test with a Rc dependant of the energy for jet reconstruction Outlooks

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48. 48

49. 49 backup

50. 50 from photon to gamma-jet Simulation of -jets (p-p : PYTHIA ; Pb-Pb : HIJING) PYQUEN : quenching simulation p-p : no background, Pb-Pb with background IV - -jet reconstruction in ALICE

51. 51 Mach cone effect 3 novembre 2008 Phys.Rev. C 77, 011901 (2008)

52. 52 jet quenching at RHIC Suppression of high p T hadrons in pp collision compared to Au-Au High p T photon suppression due to non medium effect. QM2008 R AA = d 2 N/dp T d (Au+Au) N Coll d 2 N/dp T d (p+p)

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54. 54 EMCal tower Module (4 towers) strip-module (12 modules) super-module (24 strip-modules) EMCal (10 S-modules & 2 half S-modules) II - LHC, ALICE, EMCal

55. 55 EMCal tower Module (4 towers) strip-module (12 modules) super-module (24 strip-modules) EMCal (10 S-modules & 2 half S-modules)

56. 56 -jets reconstruction algorithm

57. 57 Neutral pion desintegration

58. 58 Background anisotropy

59. 59 Jet energy reconstruction

60. 60 Rc determination

61. 61 Gamma energy resolution

62. 62 Hadron energy reconstruction

63. 63 Fragmentation function

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