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1 Guénolé BOURDAUD Gamma-jet physics with the Electromagnetic Calorimeter (EMCal) in ALICE experiment at LHC 20 th July.

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Presentation on theme: "1 Guénolé BOURDAUD Gamma-jet physics with the Electromagnetic Calorimeter (EMCal) in ALICE experiment at LHC 20 th July."— Presentation transcript:

1 1 Guénolé BOURDAUD Guenole.bourdaud@subatech.in2p3.fr Gamma-jet physics with the Electromagnetic Calorimeter (EMCal) in ALICE experiment at LHC 20 th July 2007 HEP 2007

2 2 Hard Probes in QGP Study, historical view ~98%~ 50%~ 2%  hard /  tot Alice was designed before RHIC results. Lessons from RHIC : Need dedicated detectors for high p T and Hard probes > EMCal QGP Initial state (partonic) observations. Explosion of hard probes New matter state. Final state (hadronic) observations. Emergence of hard probes. Measurement 200820001994 Global Observables ~1994~1990~1980 Start of construction LHCRHICSPS

3 3 Hard probes : interest of LHC Heavy ion dedicated experiment : ALICE More jets, higher p T and access to gamma-jet correlations with enough statistics. 2008 : first pp collisions at 14 TeV… 2009 : collisions Pb-Pb low luminositiy 2010 : collisions Pb-Pb high luminositiy

4 4 Jet quenching @ RHIC Hard scatterings in nucleon collisions produce jets of particles. In the presence of a color-deconfined medium, the partons strongly interact loosing a significant part of their energy. Energy loss : “Jet Quenching” Redistribution of jet energy : - less particles at high pT : interaction with medium : seen @ RHIC + more particles at low pT : radiations of gluons : visible @ ALICE ?

5 5 ALICE Central tracking + EMCal : Well designed detectors to study jet quenching effect Alice central tracking :  = +/- 0.9  = 360° Charged particles High particle identification capabilities Low p T possibilities For neutral electromagnetic particles : PHOS : high granularity spectrometer (  ⅹ  = 0.24ⅹ100°) EMCAL : large acceptance calorimeter (  ⅹ  = 1.4ⅹ110°)

6 6 ALICE Central tracking + EMCal : Well designed detectors to study jet quenching effect EMCal & TPC : Possibility to reconstruct jet event by event. Full jet reconstruction (neutral and charged) Gamma detection (for gamma-jet). EMCal : U.S.-Italy-France project  = +/- 0.7  = 110° 11 modules Ready for run 2009 (1 module)

7 7 Direct prompt  g+q   +q (Compton) q+q   +g (Annihilation) – Parton in-medium modification perturb final hadronic state (jet-quenching) – Prompt photons are not perturbed by the medium – Prompt photons gives jet energy. Initial Photon (  prompt). Initial parton Leading Particle Jet Want to study jet modification due to in medium interaction (p-p vs Pb-Pb) Need to obtain the jet energy : gamma-jet is a good solution. Gamma-jet _

8 8 gamma-jet in ALICE Gamma-jet in EMCal is one order of magnitude higher than in PHOS. ~ 10k events for energy higher than 30 GeV / year Need the high geometrical acceptance of EMCal Not seen at RHIC (not enough statistic) PHOS has a lower geometrical acceptance, can not see (enough) Gamma-jets Hard to observe : background from jet-jet and heavy-ion collision.

9 9 x Dashed red : quenched black : unquenched Schematic example Fragmentation function & Hump-backed Plateau Depletion of High energy particles to increase the number of low energy particles

10 10 180° EMCal p T leading > 10% p T  prompt p T Jet ~ p T  prompt Beam axis TPC Algorithm for gamma-jet reconstruction

11 11 Gamma selection Particle identification : PID (based on Shower Shape Analysis : SSA) Method developed for EMCal, can distinguish ,  0 and other hadrons. Efficiency ~55 % and Purity ~70 % for  Gamma energy higher than 30 GeV to avoid background photons (thermal, decay, …) Isolation cut :  energy higher than 10% of the energy in a cone centred around it. If exact,  is isolated and so considered as a prompt . SSA

12 12 Jet reconstruction Cuts & parameters Azimuthal correlation, angular selection :  (  - jet) < 0,1 rad Leading particle E lead /E  < 0,1 Reduced cone algorithm R=0.3 =  (  ²+  ²) (background study in progress)

13 13 x  =ln(1/x) 1/N dN/d  Fragmentation function Ejet=30GeV. Humpbacked plateau 1/N dN/dx Reconstruction of Fragmentation Function & humpbacked plateau. quenched but no background unquenched Pythia simulation, full geant reconstruction Quenching with pyquen. I.P. Lokhtin, A.M. Snigirev, Eur. Phys. J. C 46 (2006)211-217 q ~ 30 GeV 2 /fm No background 71% of gammas found 72 % of jet found if gamma found. ^

14 14 Estimating the heavy-ion background The modification of the hump-backed plateau is dominated by background in Pb-Pb collisions. Measured S/B : S/B ~ 10 -2 for  > 2.5 (p T < 2.46 GeV) quenched signal only : no background Signal + background Measured (S+B)/S

15 15 With the heavy-ion background & errors The modification of the hump-backed plateau is dominated by background in Pb-Pb collisions. Need background corrections. Actually : Can see depletion of high energy particles (seen at RHIC) Need bkg. subtraction unquenched quenched with background quenched but no background ratio unquenched/quenched With background Need bkg substraction ratio unquenched/quenched Without background Only Signal  =ln(1/x) 1/N dN/d  1/N dN/dx x Hb. pLat. PB/p

16 16 Conclusion With the EMCAL, ALICE will greatly improve its direct photon and jet physics capabilities. These new, more accessible, probes, will help ALICE to study the Quark Gluon Plasma in greater detail. gamma-jets give access to redistribution of the jet energy. Show the depletion for high energy particles. The low pT particles increase has to be studied by background subtraction.

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18 18 More …

19 19 Jet-quenching at RHIC  s = 200A GeV 1/N trigger dN/d(  ) Near side Away side

20 20 Jet-quenching at RHIC  s = 200A GeV 1/N trigger dN/d(  ) Near side Away side

21 21 Jet-quenching at RHIC  s = 200A GeV 1/N trigger dN/d(  ) The back to back jet correlation is lost due to hard interaction in plasma. The rare process (Hard Scattering or “Jets”) is the probe of whether the soft production products form a medium.

22 22 Conclusion – gamma-JETS It is possible to show the decrease of high energy particles, not yet the increase of low energy particle (Background subtraction in progress) Need: Systematic study of cuts in algorithm Jet-jet pollution of signal (isolation cut study)

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25 25 PID, shower shape Shower shape 0 : Cluster in EMCal higher energy °°  °° °°      Gustavo Conesa, thesis : University of Nantes and University of Valencia, 2005 ALICE-INT-2005-053 A tower

26 26 Apport de EMCal dans ALICE : total energy measurement (neutral and charged) Beter definition of fragmentation function, at low z (energy loss dynamic) better jet trigger with central tracking :  medium modification (part soft)  composition of the quenched jets L’expérience idéale pour la physique des grands p T : Calorimeter like ATLAS and CMS  Resolution (detector, measurement of the jets)  higher Acceptance Tracking and Identification of Particles in ALICE La réalité : des expériences complémentaires interest ATLAS/CMS :  high yield  higher pT (> 350 GeV)  study of  -jet, Z-jet (low statistics) interest of ALICE : see previous

27 27 TPC acceptance = 90% ALICE dN/d  =6000 CMS dN/d  = 3200

28 28 Efficiency for  identification

29 29 Efficiency for  ° identification

30 30 Simulation conditions 10000 events with a single Gamma-jet,  in PHOS acceptance. AliGenPythia gener2->SetEnergyCMS(14000. or 5500.) SetProcess(kPyDirectGamma)  -jets process SetStrucFunc(kCTEQ4L) SetQuench(0 or 2) quenching with Pyquen Pyquen : parameters and initial conditions selected as an estimation for LHC heavy ion beam energies. Initial conditions for Pyquen :  0 = 0.1 fm/c T 0 =1 GeV/c Lokhtin, Hep-ph/0406038

31 31   Gamma Energy (GeV) 100 GeV simulated jets Jet reconstruction. Jet Energy (GeV)

32 32  decay from  0 : angle EMCAL tower size changed : 0.014 From Marco van Leeuwen

33 33 PID for EMCal   ° hadrons

34 34 Discriminant parameter PID, particle identification , e ±,  ° and other hadrons. Discriminating parameters. Distributions ([ , e ±,  °, hadrons], energy). Probability for particle nature (Bayesian method). ACB

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