correlations and fluctuations workshopfirenze, july 9 th 2006 event-by-event physics in alice chiara...
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Correlations and Fluctuations WorkshopFirenze, July 9th 2006
Event-by-Event physics in ALICE
Chiara ZampolliALICE-TOF
Centro E. Fermi (Roma), INFN (Bologna)
Correlations and Fluctuations in Relativistic Nuclear Collisions, Firenze, 7th-9th July 2006
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Outline
Introduction PID performance Identified Particle Spectra Particle Ratios Mean pT
Summary and Conclusions
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
QGP Signatures
The nature and the time evolution of the hot and dense system created in a heavy-ion collision are expected to show the characteristic behaviour of a QGP phase transition, which could dramatically change from one event to the other.
Apart from the very well known probes (inclusive probes, probes related to deconfinement...), an analysis on an Event by Event basis offers the opportunity to study the QCD phase transition and to get insights into the QGP. For example:
Thermodynamic quantities (T,S)Energy density fluctuations
Jets and minijetsDCC, Balance function...
Properties of the systemOrder of phase transitionPhysics of the QGPChiral phase transition, hadronization time...
relying on the very high particle multiplicities produced per event (SPS, RHIC, LHC)
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Event by Event Fluctuations
FLUCTUATIONS
Statistical Finite number of
particles produced Experimental
acceptance and resolution
Statistical Finite number of
particles produced Experimental
acceptance and resolution
DynamicalDynamics of the
collision Evolution of the
system
DynamicalDynamics of the
collision Evolution of the
system
Sources of event-by-event fluctuations:• geometrical• energy, momentum, charge conservation• anisotropic flow• Bose-Einstein correlations• resonance decays• jets and mini-jets• temperature fluctuations
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Some Experimental Results
K/ratio
STAR
STAR, = 200 GeVNNs
Mean pT
NA49, = 17.2 GeV NNs
What will ALICE sensitivity be?
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
ALICE E-by-E Program
Thanks to the very high charged particle multiplicity expected per event, E-by-E studies will be feasible with the ALICE detector for many observables:
Temperature
Mean pT
Particle RatiosMultiplicityConserved Quantities (Charge)HBT radiiBalance FunctionFlowDCC...
http://aliceinfo.cern.ch/, ALICE PPR II
Particle IDentification plays
a crucial role!
Particle IDentification plays
a crucial role!
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
ALICE PID
separation @ 3 separation @ 2
(dE/dx)
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Monte Carlo Event Sample
pt> 0.15 GeV/c,
-0.9 < < 0.9 K p
average # generated
6750 720 380
300 Hijing Pb-Pb events (fully simulated and reconstructed)
Centrality 0 – 10% of minbias cross section (0 < b < 5 fm)
Magnetic Field B = 0.5 T
~ 4500/dydNch
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Primary Track Selection
The selection on primary tracks has been performed relying on the quality of the extrapolation of the tracks to the reconstructed primary vertex, taking into account the covariance parameters of the track as well.
The inefficiency of the cut can be due to reconstruction defectssecondaries included
Kpef
ficie
ncy
N(Prim)Prim)|N(χ
)N()|N(Prim
K p
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
PID Performance - Definitions
The PID performance is evaluated in terms of:
efficiency = NNt
id
wtid
wid
NN
contamination =
prim
tid
NN
overall efficiency =
wt,idN = number of correctly/uncorrectly identified particles
primN = number of generated primaries
N = number of reconstructed particles to which the PID procedure is applied
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Combined PID – ITS || TPC || TOF
K
p 0.15 < pT < 4 GeV/c
K p
ID 5150 360 280
wrongly ID
155 74 13
Efficiency contamination
K P K p
98%
78%
92%
3%20%
4%
overall efficiency
K p
40% 70%
K
p
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Generated vs Identified Spectra
Generated
Identified (w)
Identified (t + w)
K
p
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
p from weak decays
p
Generated p
Reconstructed p from
Generated p Generated Reco p from
385 130 8
Per event:
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Fitting of the Spectra
Tp
expdydpNd
πpT
T
2
T2
1
Tp
expdydpNd
πpT
T
2
T2
1
Event by event fitting procedure for pT spectra: exponential function
,T = slope parameter, connected to the
Correction of the identified spectra taking into account:
Limited acceptance and reconstruction efficiency of the detectors: εacc
Transverse momentum reconstruction efficiency: εp
PID efficiency: εPID
PID contamination: CPID
(id)dydpNd
C1ε1
ε1
ε1
(reco)dydpNd
T
2
PIDPIDPaccT
2
T
kinetical freeze-out temperature
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Results – Single Event, pT spectra
Temperature (MeV)
K p
186 ± 2 208 ± 8 319 ± 13
Fit range: 0.25 < pT < 2 GeV/c
K
GeneratedReconstructed
i.e. corrected!
p
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Results – T Distributions
= 182 MeV
T = 3 MeVπT = 226 MeV
T = 13 MeVKT = 303
MeV
T = 21 MeV
pT
T/T ~ 0.5% T/T ~ 6% T/T ~ 7%
K p
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Systematic Uncertainties on the Corrections
Possible sources of systematic errors: Knowledge of the acceptance and reconstruction efficiencies,
secondaries’ flow...
A detailed study on is to be made of systematic uncertainties.
Nevertheless, since a level of 10% seems reasonable, 100 virtual experiments randomly changing the efficiency (contamination) correction factors by 10%.
A small relative increase of few %s in the width of the temperature distributions has been observed in both cases (efficiency/ contamination).
The mean values of the temperatures can vary by few %s.
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Particle Ratios
K/R = 0.106σR = 0.009R = 0.106σR = 0.009
p/ R = 0.055σR = 0.006R = 0.055σR = 0.006
σR/R ~ few %s
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Mean pT, all particles
= 476 MeV
pT = 7 MeV
Tp
pT/pT ~ 1.5%
The mean value depending on the relative particle concentrations!!
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Mean pT
Kp
= 451 MeV
pT = 6 MeV
πT,p = 578 MeV
pT = 24
MeV
KT,p = 744 MeV
pT = 50
MeV
pT,p
pT/pT ~ 1% p
T/pT ~ 4% p
T/pT ~ 7%
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Summary & Conclusions
Event by event fluctuations studies are an important tool to explore the QCD phase diagram, searching for the QGP, and the QCD critical point.
Several recent experimental studies (at the SPS -NA49- and RHIC -STAR, PHENIX...- have focused on the studies of fluctuations in relativistic heavy ion collisions (high temperature and energy densities).
Thanks to its very high particle yield per event, and to the excellent PID capabilities, ALICE will be able to study fluctuations measuring the identified particle spectra (, K, p) and the particle ratios (K/, p/) on an Event-by-Event basis.
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Summary and Conclusions – cont’d
Temperature fluctuations: statistical fluctuations of the order of few percent for K and p.
Particle ratios: statistical fluctuations of the order of few percent for both K/ and p/
Mean pT: statistical fluctuations of the order of few percent for , K and p and for inclusive spectra.
Any other contribution from dynamical fluctuations due to new physics will result in
an increase of the observed values
The results presented herein strongly depend on the assumed dNch/dy.
HIJING simulation: dNch/dy ~ 4500;
RHIC results suggest a reduction by a factor ~ 2÷3 in the data.E-by-E studies still feasible
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Work in Progress
E-by-E fluctuation analysis on p-p collisions Multiplicity fluctuations Effect of Jets and Minijets
Correlations and Fluctuations WorkshopFirenze, July 9th 2006
Back-Ups
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Color superconductor
B
Hadronicmatter
Critical end point
?
Nuclei
Chiral symmetrybroken
Chiral symmetryrestored
Neutron stars
T
1st order line ?
Quark-Gluon Plasma
Continuous transition for small chemical potential at:
Tc~ 170 MeVc ~ 0.7 GeV/fm3
Lattice calculations: crossover at μb~ 0
Many parameters involved
The T-μ QCD Phase Diagram
No sharp boundary between hadronic matter and QGP!!!
QCD prediction: @ very high temperatures and energy densities, a Phase Transition from Hadronic Matter to the QGP occurs. What kind of phase transition? But really a phase transition or a crossover?
LHC
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Experiments at the LHC
ATLAS
CMS
Designed for high pT physics in p-p
collisions
ALICE Dedicated LHC HI experiment~ 9 km
CERN
LHC
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
-Multiplicities & Et distributions, -HBT Correlations, elliptic and transverse flow, -hadron ratios and spectra, -Evt-by-Evt fluctuations-…
The ALICE Physics Program
-Charmonium and Bottomonium states, -strangeness enhancement, resonance modification,-jet quenching and high pt spectra, -open Charm and Beauty-thermal radiation,…
Probes of deconfinement & chiral symmetry restoration
Global characteristics of the fireball (Evt by Evt)
Heavy ion observables in ALICE
p-p and p-A physics in ALICE Physics of ultra-peripheral heavy ion collisions Contribution of ALICE to cosmic-ray physics
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
A Large Hadron Collider Experiment - ALICE
ITSLow pT trackingVertexing
TPCTracking, dE/dx
TRDElectron ID
TOFPID
HMPIDPID (RICH) @ high pT
PHOSγ, π0
PMDγ multiplicity
MUON μ-pairs MUON μ-pairs
= 5.5 TeV/NNDesigned for
dNch/dy|max = 8000 (optimized for 4000)Lmax = 11027 cm-
2s-1
s
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
ALICE Tracking
Track Reconstruction has to be performed in a high flux environment Reconstruction at low pT very delicate (multiple scattering and energy loss)
Tracking based on a KALMAN FILTER techniqueTracking based on a KALMAN FILTER technique
Simultaneous reconstruction and fitting
Rejection of incorrect space points “on the fly”
Simpler handling of multiple scattering and energy loss effects
Easy extrapolation from one detector to the other
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
ALICE Tracking Strategy
dN/dy =8000 (slice: 2o in
HMPID
TOF
TRD
TPC
ITS
• Final refit inwards
• Primary Vertex Finding in ITS
• Extrapolation and connection with outer PID detectors
After cluster finding, start iterative process through the central tracking detectors, ITS+TPC+TRD:
• Propagation to the vertex, tracking in ITS
• Back-propagation in TPC and in the TRD
• Track seeding in outer TPC
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
ALICE Tracking Performance
Tracking Efficiency / Fraction of Fake Tracks for dN/dy = 2000, 4000, 6000, 8000
For dN/dy = 2000 ÷ 4000,
efficiency > 90%,
fake track probability < 5%!!!
For dN/dy = 2000 ÷ 4000,
efficiency > 90%,
fake track probability < 5%!!!
Full chain, ITS + TPC + TRD
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
PT Resolution
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
ALICE Inner Tracking System – ITS
Six Layers of silicon detectors for precision tracking in ||< 0.9
• 3-D reconstruction (< 100m) of the Primary Vertex
• Tracking+Standalone reconstruction of very low momentum tracks
• Particle identification via dE/dx for momenta < 1 GeV
SPD - Silicon Pixel
SDD - Silicon Drift
SSD - Silicon Strip
• Secondary vertex Finding (Hyperons, D and B mesons)
Three tecnhnologies:
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
ALICE Time Projection Chamber – TPC
• Efficient (>90%) tracking in < 0.9
• (p)/p < 2.5% up to 10 GeV/c
Conventional TPC optimized for extreme track densities
• Two-track resolution < 10 MeV/c
• PID with dE/dx resolution < 10%
Space-Point resolution 0.8 (1.2) mm in xy,(z), occupancy from 40% to 15%
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
ALICE Time Of Flight – TOF
Large array at R ~ 3.7 m, covering | | < 0.9 and full
Extensive R&D, from TB data:
Intrinsic Resolution ~ 40 ps Efficiency > 99%
Readout pads 3.5x2.5 cm2
122
cm
TOF basic element: double-stack Multigap RPC
stripOccupancy < 15% (O(105)
readout channels)
2x5 gas gaps of 250mm
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
PID with the ITSd
E/d
x (
MIP
un
its) PID in the 1/2 region
2 measurements out of 4 Layers (SSD, SDD) used in the truncated mean
(dE/dx) ~ 10%
,K,p signals ~ gaussians
p = 0.4 GeV
dE/dx (MIP units)
p (GeV/c)
Mis-associated Clusters
central PbPb events
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
PID with the TPC
kaons
pions
protons
p (GeV/c)
dE
/dx (
MIP
un
its)
Use maximum signal in cluster, shared clusters not included
Truncated mean with 60% lowest signals
dE/dx (a.u.)
Well described by gaussians (@ fixed pT)
dE/dx resolution ~ 6.8% at dN/dy=8000 (5.5% for isolated tracks, or pp collisions)
Pions, 0.4<p<0.5 GeV/c
central PbPb events
Also some separationin the relativistic rise
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
PID with the TOF
TOF response gaussian in (tTOF – texp ),
• texp = time calculated from tracking for a given mass hypothesis
• tTOF = measured time of flight
Pions
Mass (GeV/c2)
P (G
eV
/c)
Mass= p·(t2TOF/L2-1)1/2
• • k• p
Total System resolution(including track
reconstruction) ~90 ps
Mis-associated tracks
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
efficiency
contamination
p dependence of:
ALICE PID Performance (&)
Central Pb + Pb HIJING events – kaon case
ITSstand-alone
TPCstand-alone
TOFstand-alone
Combining the PID information from different detectors allows a weaker momentum dependence of the efficiency (contamination) which stays higher (lower) or at least
equal than with stand-alone detectors!!!
Combining the PID information from different detectors allows a weaker momentum dependence of the efficiency (contamination) which stays higher (lower) or at least
equal than with stand-alone detectors!!!
ITS & TPC & TOF
combined!!!
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
ALICE PID Approach
Weaker momentum dependence of the efficiency (contamination) Efficiency (contamination) higher (lower) or at least equal than with stand-
alone detectors
Weaker momentum dependence of the efficiency (contamination) Efficiency (contamination) higher (lower) or at least equal than with stand-
alone detectors
A common BAYESIAN approach is adopted by every ALICE detector performing PID;
The probability w(i|s) to be a particle of type i (i = e, , , ...) if a signal s (dE/dx, TOF,...) is detected, is:
π...μ,e,kk
i
Ck|srCi|sr
s|iw
r(s|i)conditional pdf to get a PID signal s in a detector, if a
particle of type i is detected
Ci
a priori probability to find a particle of type i in the
detector
Combined PID combining (multiplying) the r(s|i) from different dets
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Results – T Distributions
K p
= 182 MeV
T = 4 MeVπT = 225 MeV
T = 17 MeVKT = 304
MeV
T = 22 MeV
pT
T/T ~ 2% T/T ~ 7% T/T ~ 7%
K p
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Efficiency Correction Variation
K p
πT = 182 ± 1 MeV/c (was 182)
KT = 225 ± 1 MeV/c (was 225)
pT = 306 ± 2 MeV/c (was 304)
No significant change!
K p
πTσ = 3.8 MeV/c KTσ = 15.7 MeV/c pTσ = 22.6 MeV/c
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
Contamination Correction Variation
K p
πT = 181 ± 1 MeV/c (was 182)
KT = 227 ± 1 MeV/c (was 225)
pT = 304 ± 2 MeV/c (was 304)
No significant change!
K p
πTσ = 3.8 MeV/c KTσ = 16.0 MeV/c pTσ = 22.3 MeV/c
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
ITS PID
K
p
K p
ID 5200 330 270
wrongly ID
315 125 30
Efficiency contamination
K P K p
97%
63%
85%
6%38%
13%
K
p
overall efficiency
K p
31% 65%
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
TPC PID
K
p
K P
ID 5380 220 225
wrongly ID
310 35 6
Efficiency contamination
K P K p
>99%
50% 76% 6% 15% 3%
K
p
overall efficiency
K p
25% 58%
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
TPC || ITS PID
K
p
K p
ID 5200 310 260
wrongly ID
230 75 15
Efficiency contamination
K P K p
98%
32%
85%
4%25%
6%
K
p
overall efficiency
K p
33% 65%
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
TOF PID
K
p K p
ID 5200 360 260
wrongly ID
100 80 10
Efficiency contamination
K P K p
98%
76%
86%
2%22%
5%
K
poverall efficiency
K p
39% 66%
Firenze, July 9th 2006 Correlations and Fluctuations Workshop Chiara Zampolli
E-by-E Fluctuations: Observables
Mean Transverse Momentum
Mean Energy
Charge Fluctuations
Particle Ratios
Identified Particle Spectra
Particle IDentification plays a crucial role!Particle IDentification plays a crucial role!