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Inclusive jet cross-sections and correlations in Au+Au and p+p collisions at sqrt ( s NN ) = 200 GeV. Mateusz Ploskon For the STAR Collaboration. Outline. Motivation and strategy Datasets, jet algorithms, correction schemes Observables Inclusive jet cross-section + Jet R AA - PowerPoint PPT Presentation
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Inclusive jet cross-sections and correlations in Au+Au and p+p collisions at sqrt(sNN) = 200 GeV
Mateusz PloskonFor the STAR Collaboration
Mateusz Ploskon (LBNL), STAR, QM'09 2
Outline
• Motivation and strategy• Datasets, jet algorithms, correction schemes• Observables– Inclusive jet cross-section + Jet RAA
– Jet “radius” systematics– (di-)Hadron-jet recoil spectrum and Jet IAA
• Discussion: implications for jet quenching
Mateusz Ploskon (LBNL), STAR, QM'09 3
Motivation and Strategy
1
Cross-section ratio AuAu/pp
JetAAR
€
pT
Physics of full jet reconstruction in heavy ion collisions
€
dσ JetdpT
€
pT
p+p
Au+Au
Energy shift?
Absorption?
R=0.4Measure energy flow into “cone” of radius R
o Total momentum is conserved even for strongly quenched jets o Unbiased jet reconstruction: recover the full jet energy within
cone radius R
o Compare Au+Au and p+p jet spectrao → Inclusive cross section: RAAjet~1o → p0+jet conditional yield: IAAjet~1
o Caveat: initial state nuclear effects
R
p0
Jet
Mateusz Ploskon (LBNL), STAR, QM'09 4
Data setsEssential requirement: minimize trigger bias of jet population
• Inclusive spectrum data:– Au+Au (2007):
• online MinBias Trigger• offline select 10% most central events (8 x 106events)
– p+p (2006): • online “Jet Patch” trigger (int lumi 6.5 pb^-1)• offline correct bias at low ET
• h+jet coincidence data:– Both p+p (2006) and Au+Au (2007):
• Online “BEMC High Tower” trigger• Offline: hadron trigger energy from 3x3 tower cluster (ET>7 GeV)
• Track and Tower cuts:– BEMC towers energy > 0.2 GeV– TPC track momentum pT > 0.2 GeV/c
Mateusz Ploskon (LBNL), STAR, QM'09 5
Jet algorithms
Algorithms: kt and anti-kt from FastJet*– Resolution parameter R = 0.4, 0.2– Jet acceptance: |hJET| < 1.-R– Recombination scheme: E-scheme with massless particles
*Cacciari, Salam and Soyez, JHEP 0804 (2008) 005 [arXiv:0802.1188]
anti-kT jetKT jet
Anti-kt expected to be less susceptible to background effects in heavy ion collisions
R
Hard scattering
Fragmentation
Sequentialrecombinationalgorithms
Cone basedalgorithms
Mateusz Ploskon (LBNL), STAR, QM'09 6
Systematic correctionsTrigger corrections
– p+p trigger bias correction
Particle level corrections:– Detector effects: efficiency and pT resolution– “Double* counting” of particle energies
• * electrons: - double; hadrons: - showering corrections• All towers matched to primary tracks are removed from the analysis
Jet level corrections:• Spectrum shift:
– Unobserved energy– TPC tracking efficiency
• BEMC calibration (dominant uncertainty in p+p)• Jet patch trigger efficiency (only in p+p)• Jet pT resolution• Underlying event (dominant uncertainty in Au+Au)
Full assessment of jet energy scale uncertainties
Data driven correction scheme• Weak model dependence: only for single-particle response, p+p trigger response• No dependence on quenching models
Mateusz Ploskon (LBNL), STAR, QM'09 8
STAR Preliminary
Au+Au Central
Underlying event
Single di-jet event from a central Au+Au:- Two jet peaks on top of the HI background
Event background is characterized with median pT per unit area (r).<pT
BG> in R = 0.4 is ~45 GeV/c. S/B~0.5 at 20 GeV/c.
Central assumption:Signal and background can be factorized
with resolution:
True jet distribution smeared:sDATA ~ 6.8 GeV
Systematic studies indicate variation of sigma +/-1 is a conservative bracketing of systematic uncertainties.
Error bands indicate these limits.
Mateusz Ploskon (LBNL), STAR, QM'09 9
Fake jet contamination
“Fake” jet rate estimation: • Central Au+Au dataset (real data)• Randomize azimuth of each
charged particle and calorimeter tower
• Run jet finder• Remove leading particle from each
found jet• Re-run jet finder
“Fake” jets: signal in excess of background model from random association of uncorrelated soft particles (i.e. not due to hard scattering)
STAR Preliminary
Mateusz Ploskon (LBNL), STAR, QM'09 10
Fake jet contamination
“Fake” jet rate estimation: • Central Au+Au dataset (real data)• Randomize azimuth of each
charged particle and calorimeter tower
• Run jet finder• Remove leading particle from each
found jet• Re-run jet finder STAR Preliminary
“Fake” jets: signal in excess of background model from random association of uncorrelated soft particles (i.e. not due to hard scattering)
Mateusz Ploskon (LBNL), STAR, QM'09 11
Spectrum unfolding: methodBackground non-uniformity (fluctuations) and energy resolution introduce pT-smearing
Correct via “unfolding”: inversion of full bin-migration matrix
Check numerical stability of procedure using jet spectrum shape from PYTHIA
Procedure is numerically stableCorrection depends critically on background model
→ main systematic uncertainty for Au+Au
unfolding
Pythia
Pythia smeared
Pythia unfolded
Mateusz Ploskon (LBNL), STAR, QM'09 12
Spectrum unfolding
• Corrections for smearing of jet pT due to HI backround non-uniformities
• 1) raw spectrum
STAR Preliminary
Mateusz Ploskon (LBNL), STAR, QM'09 13
Spectrum unfolding
• Corrections for smearing of jet pT due to HI backround non-uniformities
• 1) raw spectrum• 2) removal of “fake”-
correlationsSTAR Preliminary
Mateusz Ploskon (LBNL), STAR, QM'09 14
Spectrum unfolding
• Corrections for smearing of jet pT due to HI backround non-uniformities
• 1) raw spectrum• 2) removal of “fake”-
correlations• 3) unfolding STAR Preliminary
Mateusz Ploskon (LBNL), STAR, QM'09 15
Spectrum unfolding
• Corrections for smearing of jet pT due to HI backround non-uniformities
• 1) raw spectrum• 2) removal of “fake”-
correlations• 3) unfolding• 4) correction for pT
resolution
STAR Preliminary
Mateusz Ploskon (LBNL), STAR, QM'09 17
Inclusive jet cross-section in p+p at sqrt(sNN) = 200 GeV
o Fully corrected jet cross-section reconstructed with kt algorithm
o Very good agreement between the algorithms
STAR PreliminaryUncertainty due to BEMC calibration
Mateusz Ploskon (LBNL), STAR, QM'09 18
Inclusive jet cross-section in p+p at sqrt(sNN) = 200 GeV
• Comparison to published STAR data– run 2003/2004
• Note: – published data
reconstructed with different jet algorithm:• Mid-point cone (R=0.4)
STAR Preliminary
Phys. Rev. Lett. 97 (2006) 252001
Mateusz Ploskon (LBNL), STAR, QM'09 19
Inclusive jet yields in 10% most central Au+Au at sqrt(sNN) = 200 GeV
Mateusz Ploskon (LBNL), STAR, QM'09 20
Inclusive jet yields in 10% most central Au+Au at sqrt(sNN) = 200 GeV
o Fully corrected jet spectrum
o Exactly the same algorithms and jet definitions used as compared to p+p
o Bands on data points represent estimation of systematic uncertainties due to background subtraction
STAR Preliminary
Uncertainty due to BEMC calibration
Mateusz Ploskon (LBNL), STAR, QM'09 21
Inclusive jet spectrum: p+p and central Au+Au (R=0.4 and R=0.2)
p+p Au+Au central
STAR Preliminary
STAR Preliminary
Mateusz Ploskon (LBNL), STAR, QM'09 22
Cross-section ratios in p+p and Au+ Au with R=0.2/R=0.4
p+p: “Narrowing” of the jet structure with increasing jet energy
Au+Au: Strong broadening of the jet energy profile
STAR Preliminary
p+p
Au+Au
Many systematics effects cancel in the ratio
Mateusz Ploskon (LBNL), STAR, QM'09 24
R = 0.4
5% uncertainty on BEMC calibration
o Significant energy recovered as compared to RAA~0.2 for hadrons
o Visible trends: o different sensitivity of
the algorithmso Central values drop as a
function of jet pT
STAR Preliminary
RAA Jets
Mateusz Ploskon (LBNL), STAR, QM'09 25
RAA Jets and Energy flow in smaller “cone” radii
Significant drop of RAA as a function of jet pT for R=0.2 as compared to R=0.4Jet energy not fully recovered in small “cones” – shift towards lower pT
STAR Preliminary
R=0.4
R=0.2
Mateusz Ploskon (LBNL), STAR, QM'09 27
Di-hadron – jet correlations
Yiel
d pe
r trig
ger
STAR, PRL 97, 162301 (2006)
Df
STAR high pT dihadrons: bias towards non-interacting jet population
A
B
Recoil
Mateusz Ploskon (LBNL), STAR, QM'09 28
Hadron+jet coincidence
1
Cond. yield ratio AuAu/pp
JetAAI
€
pT
€
pT
p+p
Au+Au
Energy shift?
Absorption?
R=0.4
o Trigger on hard, leading p0 (pT>6 GeV/c)o 3x3 tower cluster in BEMC
o Construct spectrum of recoil jetso normalized per di-hadron trigger
This event selection will maximize the recoil path length distribution in matter
Cond
ition
al y
ield
R
Jet
p0
Mateusz Ploskon (LBNL), STAR, QM'09 29
H – recoil jet coincidences
A
B pT > 0.5 GeV/c
Recoil jet
A
B pT > 6 GeV/c
Recoil jet
Use jet fragmentation bias to vary jet path length distribution?
Mateusz Ploskon (LBNL), STAR, QM'09 30
H – recoil jet coincidences
A
B
STAR Preliminary
(Au+Au: 10% central)Anti-kt R=0.4
Mateusz Ploskon (LBNL), STAR, QM'09 31
H – recoil jet coincidences
STAR Preliminary
(Au+Au: 10% central)Anti-kt R=0.4
A
B
Mateusz Ploskon (LBNL), STAR, QM'09 32
H – recoil jet coincidences
STAR Preliminary
(Au+Au: 10% central)Anti-kt R=0.4
A
B
Mateusz Ploskon (LBNL), STAR, QM'09 33
H – recoil jet coincidences
STAR Preliminary
(Au+Au: 10% central)Anti-kt R=0.4
A
B
Significant suppression of the bias free recoil jet spectrum
Mateusz Ploskon (LBNL), STAR, QM'09 34
STAR Preliminary
Summaryo Qualitatively new measurement of jet
quenching in terms of energy flow (rather than hadronic observables) has been established
o What we have shown:o Minimum bias dataset: RAA~0.5 or largero Significant broadening of jet energy profile
R=0.2 -> R=0.4o Strong suppression of recoil jet rate at maximum
path-length
o Consistent interpretation: o quenching induces jet broadening o R=0.4 (with the presented jet definitions) is
insufficient for unbiased reconstruction
STAR Preliminary
STAR Preliminary
STAR Preliminary
Au+Au10% central
RAu+Au
10% central
Mateusz Ploskon (LBNL), STAR, QM'09 35
Outlook
• Rich new set of observables to confront calculations
• New MC jet quenching models (qPythia, JEWEL, T. Renk)
• New jet algorithms for HI collisions?– Post-processing – integration of significant energy
flow outside the “initial” jet areas (however probably hard to calculate/resolve theoretically