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Guénolé BOURDAUD

-jet physics with the EMCal calorimeter of the ALICE

experiment at LHC

La physique des-jets avec le calorimètre EMCal de l’expérience ALICE au LHC

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outline

1. Context2. Previous experimental observations3. ALICE @ LHC : new possibilities4. -jet reconstruction algorithms5. identification6. jet reconstruction7. Hump-backed plateau determination8. Summary & outlooks

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Context • Quark and gluon plasma

• Heavy ion collisions

• Hard processes, jets, -jets

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Quark Gluon Plasma

Dense medium of deconfined partons

LHCNuclear mater

time

Initial state final statePLASMA HadronisationHard

processes

QCD predictions :

• Energy density > 1 GeV/fm3

• Temperature > 200 MeV

• Baryonic density > 5-10 x normal nuclear matter density

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Hard probes in QGP study, historical view

~98%~ 50%~ 2%hard/tot

Lessons from RHIC :Need dedicated

detectors for high pT and Hard probes

Alice was designed before RHIC results.

EMCal

QGPInitial state

(partonic) observations.

Explosion of hard probes

JET-QUENCHING

New matter state.Final state (hadronic)

observations.Emergence of hard probes.

Measurement

200920001994Global Observables

~1994~1990~1980Start of construction

LHCRHICSPS

Hard processes : Creation or diffusion of high pT particles

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Hard processes & jets Lead to jets of particles, from hadronisation of a high pT parton

high pT parton

jet

Parton suffers energy loss travelling through the new medium

Jet multiplicity modification

Jet energy redistribution

Jet-quenching phenomenon

Transverse plan

(azimuthal)

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tanln

Gluon radiation

Jet modification

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-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

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• Use -jets to study medium induced jet modification (via fragmentation function modification)

• Use EMCal and tracking system from ALICE @ LHC to reconstruct -jets

Goal

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Previous experimental observations

STAR@RHIC

• Azimuthal correlation of hadrons

• First -jet study

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RHIC Relativistic Heavy Ion Collider, BNL (USA)

• √sNN = 200 GeV (Au-Au)

• √sNN = 500 GeV (p-p)

• = 5 GeV/fm3

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Jet-quenching at RHICSuppression 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

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ALICE @ LHC : new possibilitiesALICE@LHC

• Dedicated experiment

• Access to new observables

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LHCLarge Hadron Collider, CERN (Geneva)

• √sNN = 5500 GeV (Pb-Pb) X 28

• √sNN = 14000 GeV (p-p)

= 15-60 GeV/fm3 X 3-12

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Central tracking + EMCal : dedicated to -jets

Tracking-PID : ITS+TPC+(TOF, TRD)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

EMCalEMCal– Energy from neutral particles– Pb-scintillator, 13k towers– = 110, || < 0.7– Energy resolution ~10%/√E

PHOSPHOS– High resolution electromagnetic

spectrometer– || < 0.12– 220 < < 320– Energy resolution: E/E = 3%/E

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-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

16x

p-p

Pb-Pb

Highlight the jet energy redistribution

• Hump-backed plateau : distribution of the energy in the jet

= ln[pT(jet)/pT(part)]

)(

)(

JetT

particleT

ppx

Tracking

Calorimeter

Borghini-Wiedemann, hep-ph/0506218

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Feasibility with ALICE

Simulation used to :

Test capacity of the detectors to identify and reconstruct -jets

Determine parameters of the method

Test efficiencyEvent

generator

Particle propagatio

n

Detector response

-jet reconstruct

ion 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

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-jet reconstruction algorithm• Schematical view

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-jet reconstruction algorithm

Azimutal plan

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-jet reconstruction algorithm

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CR

180°

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identification• Shower shape

• Bayesian method

• Efficiency

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Particle IDentification

Shower shape 0 :Cluster in EMCalH

igher energy

°

°

°

Gustavo Conesa : Nucl. Phys. A 2006.10.039

1 tower

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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

/d

x Bayesian method

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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

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Particle IDentification

hadrons

°

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0 Parametrisation for 0

Gaussian + Landau :

6 parametersMean value of Gaussian distribution

Multiplicative constant of Landau distribution

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dn

/d

02

27 GeV

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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

• Measured0 of the unknown particle

(Method implemented in AliRoot framework)

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0 Identification

Identified : W(i) > 0,3

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Photon identification

Identified : W(i) > 0,3

Can identify photon for a -jet study !

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-jet reconstruction• candidate selection

• Azimuthal correlation

• Energy correlation

• Background fluctuations

• Jet axis determination

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From photon to -jet

candidate

1. Energy > 30 GeV (maximization direct / inclusive photons) hep-ph/0311131

2. PIDW,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)

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-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°

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-jet : energy correlation

• Ejet / Eis the fraction of reconstructed energy of the jet

RC=0.7

•100 GeV-jets

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Pb-Pb : background

Need jet energy higher than background fluctuations

Jet energy

Mean bkg

energy

bkg fluctuations

E

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Pb-Pb : background

Compromise :

• Low Rc for bkg limitation

• High Rc to maximize Ejet in cone

With Ejet = 30 GeV :

– Rc = 0,25

– Ejet / (bkg) = 2

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Jet axis reconstructionp-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.

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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

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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

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HBP Modification without background (100 GeV -jet)

Without bkg : modification of hump-backed plateau easy to measure

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Pb-Pb : background (100 GeV -jet)

How to subtract the background ?

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Pb-Pb : subtract background (100 GeV -jet)

• Background of low pT particles pollutes HBP for >3.8

• Background subtraction extends HBP measurement up to = 4.2

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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)

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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 pT particles Enhancement of low pT particles

Highlight the jet energy redistribution

Realistic spectrum : 1 year g-jets @ LHC simulated from 30 to 100 GeV

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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 pT 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)).

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• 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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backup

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from photon to gamma-jetSimulation of -jets (p-p : PYTHIA ; Pb-Pb : HIJING)

PYQUEN : quenching simulation

p-p : no background, Pb-Pb with background

IV - -jet reconstruction in ALICE

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Mach cone effect 3 novembre 2008

Phys.Rev. C 77, 011901 (2008)

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jet quenching at RHIC • Suppression of high pT hadrons in pp collision compared to Au-Au

• High pT photon suppression due to non medium effect.

QM2008

RAA = d2N/dpTd (Au+Au)

NColld2N/dpTd (p+p)

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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

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EMCal

tower

Module (4 towers)

strip-module (12

modules)

super-module (24 strip-modules)

EMCal (10 S-modules & 2 half S-

modules)

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-jets reconstruction algorithm

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CR

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Neutral pion desintegration

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Background anisotropy

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Jet energy reconstruction

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Rc determination

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Gamma energy resolution

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Hadron energy reconstruction

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Fragmentation function

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