Transcript Charged particle pseudorapidity distributions in nucleus-nucleus collisions from SPS to LHC Francesco Prino

Charged particle pseudorapidity
distributions in nucleus-nucleus
collisions from SPS to LHC
Francesco Prino
INFN – Sezione di Torino
XLIV International Winter Meeting on Nuclear Physics
Bormio, January 31st, 2006
OUTLINE:
Physics motivation
Experimental requirements and techniques
Experimental results from SPS and RHIC
Perspectives for ALICE at the LHC
Introduction:
Physics motivation
Particle production in nuclear collisions
Particle multiplicity in nucleus-nucleus collisions (= number of particles
produced in the collision) = global observable carrying important information
about:
How initial energy available is redistributed for producing particles in the final
state
 Entropy of the system created in the collision
 Initial energy density, parton density in the initial state
Centrality of the collision
 Nucleus-nucleus collisions described in multicollision models as a superposition of
elementary (nucleon-nucleon) collisions
Underlying dynamics of the particle production mechanism
Hard processes
Soft processes
Large momentum transfer
Small momentum transfer
Small distance
Large distance
Interactions at partonic level
 Governed by perturbative QCD
 Scale like the number of
elementary collisions (Ncoll)

Described by phenomenological
non-perturbative models
 Scale like the number of
participant nucleons (Npart)

Evaluation of Npart and Ncoll
Glauber model calculations:
Physical inputs:
Woods-Saxon
density for colliding nuclei
Nucleon-nucleon
inelastic cross-section inel
Numerical calculation of:
Interaction
probability, Npart , Nspect, Ncoll ...
vs. impact parameter b

0 (Pb)= 0.16 fm-3
0
1  e ( r  r0 ) / C
C (Pb)= 0.549 fm
r0 (Pb)= 6.624 fm
Accel.
SPS
RHIC
LHC
√s (GeV) 3-5
17
200
5500
21
33
42
60
inel
AGS
Key measurements
Scaling of particle multiplicity vs. energy
Change the energy available for particle
production
Change the number of collision per participant

Handle for changing the balance of particle
production between soft and hard processes
Scaling of particle multiplicity vs.
centrality of the collision
Change the volume of particle production
region ( Npart)
Handle for changing the system size
Change the number of collision per participant


Second handle for changing the balance
between soft and hard processes
Scaling of particle multiplicity for
different colliding nuclei
Second handle to change the system size
Particle momentum distributions
Particle momenta decomposed
Longitudinal momentum (pL)
Rapidity variable
1  E  pL 

y   ln
2  E  p L 
Lorentz invariant
Pseudorapidity variable
   
1  p  p L 
h   ln 


ln
tan  


2  p  pL 
  2 
h≈y for large momenta
h more easily accessed
experimentally
Transverse momentum (pT)
dN/dh – basics
Midrapidity peak / plateau
pT = pL
q = 45 (135) degrees
h = ±0.88
Sensitive to hadroproduction
details
Related to energy density

pL>>pT
pT>pL
pL>>pT
Bjorken formula (requires a
“central-plateau structure” in the y
distribution of produced particles)
 BJ 
mT  dN 


Ac f  dy  y 0
Boost-invariant central plateau?
Width of the distribution
Information on longitudinal
expansion and stopping power
(stopping vs. transparency)
Fragmentation regions
Investigate effects connected
with target and projectile
fragmentation
Experimental requirements
and techniques
Experimental issues
Acceptance:
Large h coverage to measure particles at mid-rapidity and in fragmentation
regions
Low pT cut-off if a magnetic field is present
Analysis techniques
Count fired channels (hits) on detectors
NA50, PHOBOS
 In general 1 hit NOT EQUAL to 1 particle because of:
–
–
PHYSICAL PROCESSES in the detector volume (multiple occupancy, charge sharing…)
INSTRUMENTAL PROBLEMS (electronic noise, cross-talk …)
 What
is done is to count CLUSTERS (i.e. groups of contiguous strips firing
together) and apply a correction to go from clusters to crossing particles
Measure energy deposition in detector channels NA57, BRAHMS, PHOBOS
 Correction for Landau distribution of energy deposition required
Match hits between 2 detectors (TRACKLETS) PHOBOS
 More precise alignment and knowledge of primary vertex required
 Correction for tracking efficiency to be applied
Full tracking
NA49, STAR
Example: NA50 analysis
Silicon microstrip detector measuring
the number and the angular distribution
of charged particles produced in the
collision
2 Planes (MD1, MD2)
each plane made of 2 layers (up/down)
36 azimuthal sectors (=10o)
192 radial strips (h=0.02)
6912 strips in each plane
Only 128 innermost strips used
NA50 analysis method
Extract number of particles from number of
clusters in bins of h (h=0.15) and centrality
Cluster size distribution not reproduced by a
VENUS+GEANT simulation (only physical clusters)
Dedicated MC, aimed at reproducing cluster size
distribution observed in data
Calculate primary dNch/dh .
Subtract the delta electron contribution (GEANT)
 Max. 5% of the occupancy in the most peripheral bin
Divide by secondary/primary ratio (extracted from
VENUS+GEANT simulation)

VENUS+GEANT data reconstructed with
the same method as experimental data.

1.2 –1.8 correction factor.


Does not depend on centrality.
Depends on target thickness, target position,
particular MD plane.
Large corrections due to thick (3 mm) target
High multiplicity bin
Cross checks (I)
Compare results from different
detector planes
Average between detector planes
Wide h coverage
Compare results from runs with two
different target thicknesses and
positions
Average between different thicknesses
Wider h coverage
Cross checks (II)
Compare results from 2 independent centrality estimators
dN/dh values obtained with ET and EZDC centrality selections agree within 1.5%
Both centrality estimators independent of MD
ET centrality selection
EZDC centrality selection
 Abreu et al. (NA50 collaboration) Phys. Lett. B530 (2002) 43
Experimental results:
width of the distribution
Width of dN/dh distribution (I)
Information on longitudinal expansion and degree of stopping
How would an isotropic source emitting at rest look like?
FWHM = 1.8
dN
 const
d
dN
 sin 
d
dN
1

dh cosh 2 h
Width vs. centrality at SPS and RHIC
NA50 at 158 GeV/c (√s=17.2 GeV)
√s= 200 GeV
√s= 130 GeV
Gaussian width (FWHM) decreases with increasing centrality
Observed also by NA35, WA80, Helios/Emulsion, E802
Stopping power effect
Decreasing contribution of protons from target and projectile fragmentation
Width vs. energy
NA50 most central Pb-Pb
E877
central
Au-Au
 h  0.58  0.32  ln s
Available phase space in rapidity increases with √s
Fit with the simple scaling law h = a + b · ln s
At SPS energies dN /dh (dN/dy) are twice as large as the one expected
from a thermal fireball (Senger and Strobele, nucl-ex/9810007)
Experimental results:
particle density at midrapidity
Midrapidity peak / plateau
The maximum of pseuorapidity distribution (dNch/dh | max ) at hcm=0:
Most frequently used variable to characterize the multiplicity of the interaction
of phase space acceptance  allows comparison between different experiments
Increases with collision energy (√s) and centrality
Independent
central
central
peripheral
peripheral
Scaling with centrality at the SPS (I)
Agreement within 10% among
experiments at 158 GeV/c
Fit with the power law
dN
dh
 N apart
max
Values of exponent a between 1.00
(NA50) and 1.08 (WA98)
 Depends
on the model to calculate
Npart (NA50 finds a=1.00 with a
Glauber estimation of Npart and 1.08
with a VENUS estimation)
Two-component fit:
dN
dh
 A  N part  B  N coll
max
Values of B compatible with 0
Scaling with centrality at the SPS (II)
NA50
Npart describes the centrality
dependence of particle
production at midrapidity at SPS
energies
Soft processes dominate particle
production at such energies
No important contribution from
hard processes (as expected)
Introduce yield per participant
pair:
dN ch
dh max
0.5 N part
A flat behaviour reflects the
linear dependence of dN/dhmax on
Npart
Scaling with centrality at RHIC
PHOBOS PRC 2004, nucl-ex/0405027
Yield per participant pair increases by ≈ 25% from peripheral to
central Au-Au collisions
Contribution of the hard component of particle production ?
BUT:
 The ratio 200 / 19.6 is independent of centrality

A two-compoment fit with dN/dh  [ (1-x) Npart /2 + x Ncoll ] gives compatible
values of x (≈ 0.13) at the two energies.
Warning
Npart is not a direct experimental observable and affects the
scale of both axes of plots of yield per participant vs. Npart
Different methods of evaluating Npart give significantly
different results!
NA50 at 158 A GeV/c
s = 130 GeV
Density at midrapidity vs. energy
WARNING when comparing dN/dhmax between collider and fixed
target experiments: pseudo-rapidity h is not boost invariant
Conversion from dN/dh|lab to dN/dy (Lorentz invariant) and then to
dN/dh|cm
dN ch
dN ch
m2
 1 2
dN/dhmax in central heavy
dpT dh
mT cosh 2 y dpT dy
ion collisions increases as
ln(s) from AGS to top
RHIC energies
Different √s
dependence in pp and
heavy ion collisions
Experimental results:
total charged multiplicity
Multiplicity vs. density at midrapidity
central
peripheral
The shape of pseudorapidity distributions
is not independent of centrality (Npart)
Height increases more than linearly with Npart
Width decreases with increasing centrality
BUT Height  Width ≈ constant
√s= 200 GeV
Total multiplicity vs. Npart
Total multiplicity obtained
integrating dN/dh
distributions
Small extrapolation thanks to
the wide h coverage of
PHOBOS
Total charged-particle
multiplicity proportional to
Npart
Total yield per participant is
the same as in e+e- collisions
at the same energy
Gold vs. copper
62.4 GeV
200 GeV
Cu+Cu
PHOBOS
PHOBOS
Preliminary
3-6%, Npart = 100
Cu+Cu
Preliminary
3-6%, Npart = 96
Au+Au
35-40%, Npart = 99
Au+Au
Preliminary
35-40%,Npart = 98
Unscaled dN/dh very similar for Au-Au and Cu-Cu collisions with
the same Npart
Compare central Cu-Cu with semi-peripheral Au-Au
For the same system size (Npart) Au-Au and Cu-Cu are very similar
Integrated yield vs. energy
Multiplicity in pp
collisions lower
than in e+e-
1
Understood
as due
to leading particle
effect
Multiplicity in AA collisions
Below pp and e+e- at AGS energies
Cross through pp at SPS energies
Joins e+e- data above top SPS energy
No leading particle effect AA collisions
at RHIC energies
Due to multiple collisions per participant ?
The outgoing
proton takes away
a substantial
amount of energy
Experimental results:
fragmentation regions
Limiting fragmentation
Study particle production in the rest frame of one of the two
nuclei
Introduce the variable y’ = y - ybeam (or h’ = h – ybeam )
Limiting fragmentation

Benecke et al., Phys. Rev. 188 (1969) 2159.
At high enough collision energy both d2N/dpTdy
and the particle mix reach a limiting value in
a region around y’ = 0
Also dN/dh’ reach a limiting value and become
energy independent around h’=0
Observed for p-p and p-A collisions
In nucleus-nucleus collisions
Particle production in the fragmentation region
independent of energy, but NOT necessarily
independent of centrality
Limiting fragmentation (I)
PHOBOS Phys. Rev. Lett. 91, 052303 (2003)
Particle production
independent of
energy in
fragmentation
regions
Extended limiting
fragmentation (4
units of h at 200
GeV)
No evidence for
boost invariant
central plateau
Spectator emission ?
Limiting fragmentation (II)
Different limiting curves for
central and peripheral data
Particle production in the
fragmentation region changes
significantly with centrality
The hypothesis of limiting
fragmentation does not imply that
the limiting curve is independent of
centrality
BUT both (central and
peripheral) energy independent
What have we learned so far ?
Charged particle multiplicities follow simple scaling behaviours
Total yield at RHIC energies ≈ Npart  multiplicity in e+e- at the same energy
Extended (up to 4 h units) fragmentation regions where particle production is
independent of energy (BUT not of centrality)

No evidence for a boost invariant central plateau also at top RHIC energy
From STAR White paper:
“Most bulk properties measured appear to fall on quite SMOOTH CURVES
with similar results from lower energy collisions…Similarly the centrality
dependences observed at RHIC are generally smooth… These experimental
results contrast with theoretical speculations and predictions… which often
suggested strong energy dependences accompanying the hadron-to-QGP
phase transition”
Energy density from Bjorken formula and measured dN/dy (dN/dh) at top
RHIC energy gives values of ~ 5 GeV/fm3 “well above the critical density (1
GeV/fm3) predicted by Lattice QCD for a transition to the QGP
 BJ
mT  dN 
0.6 GeV / c 2
3


3

 


700


1
.
1

5
GeV
/
fm


Ac f  dy  y 0 145 fm 2  c 1fm / c 
2

Perspectives for ALICE at the
LHC
Energy dependence and the LHC
Detectors planned for
dN/dh > 5000
Saturation model
Armesto, Salgado, Wiedemann hep-ph/0407018
Models prior to RHIC
dN/dη ~ 1800
dN/dη ~ 1100
Log extrapolation
Limiting fragmentation and the LHC
dN/dη ~
1800
Limiting fragmentation
dN/dη ~ 1100
W. Busza, Zakopane ’04
ALICE at the LHC
Forward Multiplicity Detector (FMD)
Inner Tracking System (ITS)
Time Projection Chamber (TPC)
ALICE pseudorapidity coverage
p-p collisions at LHC:
s = 14 TeV
ybeam = 9.6
Different measurement techniques
CLUSTERS on innermost ITS layers (Silicon Pixels)
TRACKLETS with 2 innemost layers of ITS (Silicon Pixels)
FULL TRACKING (ITS+TPC)
ENERGY DEPOSITION in the pads of Forward Multiplicity Detector (FMD)
dN/dh measurement with ITS
Multiplicity from:
2 innermost layers of Silicon Pixel Detectors:


Wider h coverage
No energy loss information
Analysis techniques:
Count “clusters” on the 2 layers
Count “Tracklets” (associations between 2 layers)
 ALICE collab. - Pysics Performance Report - Vol II
Silicon Pixel Detectors (2D)
Silicon Drift Detectors (2D)
Silicon Strip Detectors (1D)
L= 97.6 cm
R= 43.6 cm
dN/dh at mid-rapidity with ITS
dN/dh in |h|<0.5 for:
100 HIJING events
Standard noise level
No magnetic field
zVERTEX = 0
Hits = number of primary
particles crossing a layer
Number of clusters
Lower than generated
multiplicity in layer 1
 due cluster merging at high
multiplicity
Enhanced in layer 2
 due to secondary particles
produced in the inner layer
Tracklets
Association efficiency
decreases with increasing
multiplicity
Systematic effects
Magnetic field effect
Clusters in layer 1
insensitive to the field
low pT tracks do not
reach layer 2
Field = 0 best condition
to measure multiplicities
Noise level effect
Tracklet method more
stable against noise level
(looser cut)
(tighter cut)
Generated mult.
Standard noise level
Noise effect almost
completely removed at
the price of a decrease
of efficiency (larger
MonteCarlo correction
needed)
dN/dh reconstruction in ITS (I)
dN/dh distribution for:
1 central HIJING event
(dN/dh = 6000)
Standard noise level
No magnetic field
zVERTEX = 0
With zVERTEX smearing an
acceptance correction has to
be included
dN/dh reconstruction in ITS (II)
dN/dh distribution for:
300 semi-central HIJING events (dNch/dh ≈ 3000)
Standard noise level
No magnetic field
zVERTEX spread = ± 5 cm
+ acceptance correction
zVERTEX spread allows to increase
the h coverage
Thanks to…
Tiziano Virgili (NA57), Gunther Roland (PHOBOS) for giving me
plots and material
…and to…
Marek Idzik, Marco Monteno, Marzia Nardi, Luciano Ramello for
discussions and clarifications
…and to…
NA50 and ALICE collaborations
Backup slides
Multiplicity and collision centrality
The impact parameter (b) determines the “centrality” of the event
SMALL IMPACT PARAMETER (Central events)
Many participant nucleons (large Npart ) and few spectators
 Many nucleon-nucleon collisions ( large Ncoll )
 Big system
 Many produced particles (~ 5000 at top RHIC energy )

LARGE IMPACT PARAMETER (Peripheral events)
Few participant nucleons (small Npart ) and many spectators
 Few nucleon-nucleon collisions (small Ncoll )
 Small system
 Few produced particles

“Glauber” calculations
Optical approximation
 Czyz and Maximon, Annals Phys. 52 (1969) 59.
Nucleus thickness
functions
Nucleus-nucleus
thickness function
Nucleon-nucleon
collision probability
PHOBOS Apparatus
Centrality determination in NA50
Two detectors independent from MD to measure event-by-event
centrality related observables
Electromagnetic calorimeter  transverse energy of neutral particles (ET)
Zero Degree Calorimeter  energy of spectator nucleons (EZDC)
Centrality intervals for dN/dh analysis defined in terms of
fraction of total inelastic cross section
NA50 analysis method (I)
Data selection
Beam cleaning cuts, pile-up rejection, interaction in-target identification
Calculation of raw number of particles in each h bin (h=0.15)
and centrality class
Cluster (group of contiguous strips firing together) correction
 Cluster size distribution not reproduced by a VENUS+GEANT simulation
 Dedicated MC, aimed at reproducing cluster size distribution observed in data
High multiplicity bin
Low multiplicity bin
NA50 analysis method (II)
Calculation of primary dNch/dh .
Subtraction of the delta electron contribution (from GEANT).
Max. 5% of the occupancy in the most peripheral bin.
Correction with secondary/primary ratio from VENUS+GEANT simulation

VENUS+GEANT data reconstructed with
the same method as experimental data.
 1.2 –1.8 correction factor.



Do not depend on centrality.
Depend on target thickness, target position,
particular MD plane.
Large corrections due to thick target
Systematic error estimation
8% systematic error on primary charged multiplicity
 Abreu et al. (NA50 collaboration) Phys. Lett. B530 (2002) 33
Changing the beam energy
Pb-Pb at 40 GeV/c (√s=8.77 GeV)
ET centrality selection
Peak position changes (midrapidity = ybeam/2 )
Pb-Pb at 158 GeV/c (√s=17.2 GeV)
ET centrality selection
Particle density at the peak
increases with available energy
Width of dN/dh distribution (II)
E917 at AGS
Incomplete stopping
already at AGS energies
PHOBOS at RHIC
At RHIC energies only 22% of the particles
emitted with pT>pL ( |h| < 0.88 )
Width vs. centrality at RHIC
√s= 200 GeV
√s= 130 GeV
√s= 19.6 GeV
Gaussian width decreases with increasing centrality
Same feature observed at SPS energies
Scaling with centrality at the SPS (II)
Factor 1.7 between NA50 and
NA57 measurements
Quite different experimental
conditions and analysis techniques
for the different experiments
 EZDC
not available for NA50 at this
energy, so not all the cleaning cuts
were applied to this data sample
 NA57
uses the multiplicity to define
centrality classes (autocorrelations?)
Fit with the power law
dN
dh
 N apart
max
Values of exponent a between 1.02
(NA50) and 1.09 (NA57)
Npart GLAUBER vs. VENUS
Boost invariant central plateau?
Pseudorapidity distorts the distributions for production angles
near 0° and 90°
Rapidity distributions from BRAHMS at RHIC very similar to
data at lower energies and well represented by gaussian fits
No evidence of a plateau at midrapidity
dNch/dh in p-p
LHC
C. Jorgensen
Predictions
Predictions before RHIC startup
Predictions before LHC startup
2000
4000
6000
dNch / dy
8000
10000