russell betts (uic) for the phobos collaboration
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Russell Betts (UIC)for the
PHOBOS Collaboration
Multiplicity Measurementswith
The PHOBOS Detector
18th Winter Workshop on Nuclear Dynamics
Nassau, Jan 20th-27th,2002
ARGONNE NATIONAL LABORATORY
BROOKHAVEN NATIONAL LABORATORY
INSTITUTE OF NUCLEAR PHYSICS, KRAKOW
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
NATIONAL CENTRAL UNIVERSITY, TAIWAN
UNIVERSITY OF ROCHESTER
UNIVERSITY OF ILLINOIS AT CHICAGO
UNIVERSITY OF MARYLAND
Birger Back, Nigel George, Alan Wuosmaa
Mark Baker, Donald Barton, Alan Carroll, Joel Corbo, Stephen Gushue, George Heintzelman, Dale Hicks, Burt Holzman,Robert Pak, Marc Rafelski, Louis Remsberg, Peter Steinberg, Andrei Sukhanov
Andrzej Budzanowski, Roman Holynski, Jerzy Michalowski, Andrzej Olszewski, Pawel Sawicki , Marek Stodulski, Adam Trzupek, Barbara Wosiek, Krzysztof Wozniak
Wit Busza (Spokesperson), Patrick Decowski, Kristjan Gulbrandsen, Conor Henderson, Jay Kane , Judith Katzy, Piotr Kulinich, Johannes Muelmenstaedt, Heinz Pernegger, Michel Rbeiz, Corey Reed, Christof Roland, Gunther Roland, Leslie Rosenberg, Pradeep Sarin, Stephen Steadman, George Stephans, Gerrit van Nieuwenhuizen, Carla Vale, Robin Verdier, Bernard Wadsworth, Bolek Wyslouch Chia Ming Kuo, Willis Lin, Jaw-Luen Tang
Joshua Hamblen , Erik Johnson, Nazim Khan, Steven Manly,Inkyu Park, Wojtek Skulski, Ray Teng, Frank Wolfs
Russell Betts, Edmundo Garcia, Clive Halliwell, David Hofman, Richard Hollis, Aneta Iordanova, Wojtek Kucewicz, Don McLeod, Rachid Nouicer, Michael Reuter, Joe Sagerer
Richard Bindel, Alice Mignerey
The PHOBOS Collaboration
Completed Spring 2001 •4 Multiplicity Array
- Octagon, Vertex & Ring Counters• Two Mid-rapidity Spectrometers• TOF wall for High-Momentum PID• Triggering
-Scintillator Paddles- Zero Degree Calorimeter
137000 Silicon Pad channels
Outline of Talk• Centrality Determination Nparticipant and Ncollision
• Techniques for Multiplicity Measurements
1. Tracklets
2. Hit Counting
3. Energy Deposition
• Results
1. Energy Dependence for 1
2. Centrality Dependence
3. dN/d Shapes
• Summary and Taster of Future Delights
• Coincidence between Paddle counters at t = 0 defines a valid collision.
• Paddle + ZDC timing reject background.
• Sensitive to 97±3 % of inelastic cross section for Au+Au.
t (ns)
Eve
nts
Triggering on CollisionsNegativ
e Paddles
Positive Paddles
ZDC N
ZDC PAu Au
x
z
PPPNPaddle Counter
ValidCollision
ZDC Counter
Trigger Selection - ZDC vs Paddles
Peripheral
b
Central
b
10344 partN
Determining Centrality
Npart
• HIJING + GEANT• Glauber Calculation• Model of Paddle Response
Paddle signal (a.u.)
Co
unt
sC
ou
nts
• Estimating 97% when really 94% overestimates Npart
Uncertainty on Npart
• Measurement sensitive to trigger bias – “Minimum-bias” still has bias
– Affects most peripheral events
Paddle signal (a.u.)
Co
unt
s
Octagon
Rings
Hits in One Layer of Silicon
Vertex
Energy Spectrum (E) in Si pads
1 hit
2 hits
DataMC
Multiplicity Distributions
Au+Au Collision Event Display
Event Vertex Finding
+z
Vertex Resolution:x ~ 450 my ~ z ~ 200 m
Vertex Tracklet Reconstruction
= 1 – 2
= 1 – 2
Tracklets are two point tracks
that are constrained by
the event vertex.
|| < 0.04 || < 0.3
Combinatorial Background
Outer Hit Bin 10 (Data)
All Pairs of Hits
“Background Flip”
Backgrounds
Weak Decays Electrons
Vertex Tracklet Systematic Error
• Reconstruction: Vertex selection, Tracklet algorithm etc. 1.8%
• Weak Decays: Mostly Ks and 2%
• Background: Combinatorial, -electrons - 1.5%
• MC Generators: Different particle production, background etc. - 5%
• Total: 7.5%
Analog and Digital Hit-Counting
0 +3-3 +5.5-5.5
Octagon, Ring and Vertex Detectors (unrolled)
Count Hits or Deposited Energy
Discriminating Background with dE E
(“M
IP”)
20 64-2-6 -4
04
81
2
20 64-2-6 -4
E (
“MIP
”)0
48
12
Data Monte Carlo
Si E vs. in the OctagonFrom vertex
Not from vertex
1 Count hits binned in , centrality (b)
2 Calculate acceptance A(ZVTX) for that event
3 Find the occupancy per hit pad O(,b)
4 Fold in a background correction factor fB(,b)
E depositionin multiplicitydetectors for 1 event.
dNch
d =hits
O(,b) ×fB(,b)
A(ZVTX)
“Measuring” the Occupancy
!)(
N
eNP
N
N=number of tracks/pad=mean number of tracks/pad
The numbers of empty, and occupied, padsdetermine the occupancy as a function of ,b
Method: Assume Poisson statistics
Ntr
acks
/hit
pad
0-3%
50-55%
Octagon
Rings(central)
(peripheral)
MC, Occupancy Corrected
MC “truth”
Compare PHOBOS Monte Carlo “data” analyzed usingoccupancy corrections to “truth” - the difference gives corrections for remaining background.
f B(
,b)
fB=MCTruth/MCOcc
dNch
/d
Estimating remaining
backgrounds
-6 -4 -2 0 2 4 6
-6 -4 -2 0 2 4 6
0.2
0.4
0.6
0.8
1.0
200
400
600
Energy Loss Multiplicity
300 m Si
PRIM
TOTAL
i
NNiM
Measured S/N = 10 - 20 << Landau Width
Use Non-Hit pads - forCommon-Mode Noise Suppression
M = 240 ± 15 ± 5 ± CMN for one sensor (120 channels) at = 0
NoiseCommonNoiseRandomMLandauM 2i
2i
0.30 - 0.40
Energy deposited in ith pad (truncated)corrected for angle of incidence
Mean energy loss for oneparticle traversing pad RATIO OF TOTAL TRACKS
TO PRIMARY TRACKS
Uncertainty in Theoretical Predictions
Constraining the Models
Ratio 200/130 GeV
Phobos Measurement
Ratio 200/130averaged for four PHOBOS methods
R200/130 = 1.14 +/- 0.05 Moderate Increase in Energy Density?Systematic Uncertainty
Hard and Soft Processes
• Soft processes (pT < 1 GeV)
– Color exchange excites baryons
– Baryons decay to soft particles
– Varies with number of struck nucleons
• “Wounded Nucleon Model”
• Hard processes (pT > 1 GeV)
– Gluon exchange in a binary collision creates jets
– Jets fragment into hadrons, dominantly at mid-rapidity
(mini)jet
(mini)jet
Multiple Collisions with Nuclei• Nuclei are extended
– RAu ~ 6.4 fm (10-15 m)
– cf. Rp ~ .8 fm
• Geometrical model
– Binary collisions (Ncoll)
– Participants (Npart)
• Nucleons that interact inelastically
– Spectators (2A – Npart)
• p+A: Npart = Ncoll + 1
(Npart ~ 6 for Au)
• A+A: Ncoll Npart4/3
Participants
Spectators
Spectators
b(fm)
b
Ncoll
Npart
pp collisions
pA collisions
0 189
1200
400
Hard & Soft
collpppart
pp NxnN
nxd
dN
2)1(
What about non-central events?
We already expect that charged particleproduction can have two components:
We can tune the relative contribution byvarying the collision centrality
proton-proton multiplicity
Fraction from hard processes
Is this Description unique ?
• Gluons recombine at a critical density characterized by “saturation” scale Qs
2
• Below this scale, the nucleus looks “black” to a probe
Parton Saturation• Gluons below x~1/(2mR)
overlap in transverse plane with size 1/Q
3/1222 , AQxNQQ sgsss
Scale depends on volume(controlled by centrality!)
t
“Colored Glass Condensate”McLerran, Venugopalan,
Kharzeev, Dumitru, Schaffner-Bielich…
Data and Models for 130 GeV
Yellow band: Systematic
Error
Data and Models for 200 GeV
Yellow band: Systematic
Error
Shapes of dN/d Distributions at 130 GeV - Hit Counting
• Shapes only weakly dependent on centrality
• Differ in details
(0-6%)
(35-45%) (p-p)
HIJING
AMPT
Most of “new” behavior is at mid-rapidity – detailed comparison with pp and pA required.
130 GeV
Energy Dependence and Comparison to pp•Width increases with Ecm
•Increase = ybeam
•Scaling in fragmentation region
HI part. Production is increased at mid-rapidity
7-10% syst error
7-10% syst error
Scaling in the Fragmentation Region
FragmentationFragmentation
UA5: Alner et al., Z. Phys. C33,1 (1986) PHOBOS 2000/2001
7-10% syst error
Summary
Energy and Centrality Dependence of Mid-Rapidity Multiplicity has Constrained Models and given Insight into Interplay of Different Processes
Shapes of Multiplicity Distributions show Scaling in Fragmentation Region illustrating Common Mechanism for Particle Production which Evolves to Features Unique to HI Situation at Mid-Rapidity
To Come:
Shapes versus Centrality at 200 GeV
Multiplicity at 20 GeV
pp Data with PHOBOS at 200 GeV
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