University of Illinois at Chicago

1
The Latest Results from PHOBOS _at_ RHIC
Pseudorapidity Distribution of Charged
Particlesin d Au Collisions at 200
GeV
University of Illinois at Chicago
and Brookhaven National Laboratory
for the Collaboration

Seminar at BNL

November 14, 2003
Rachid NOUICER

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PHOBOS Collaboration (October 2003)
Birger Back, Mark Baker, Maarten Ballintijn,
Donald Barton, Russell Betts, Abigail Bickley,
Richard Bindel, Wit Busza (Spokesperson), Alan
Carroll, Zhengwei Chai, Patrick Decowski,
Edmundo García, Tomasz Gburek, Nigel George,
Kristjan Gulbrandsen, Stephen Gushue, Clive
Halliwell, Joshua Hamblen, Adam Harrington, Conor
Henderson, David Hofman, Richard Hollis, Roman
Holynski, Burt Holzman, Aneta Iordanova, Erik
Johnson, Jay Kane, Nazim Khan, Piotr Kulinich,
Chia Ming Kuo, Willis Lin, Steven Manly, Alice
Mignerey, Gerrit van Nieuwenhuizen, Rachid
Nouicer, Andrzej Olszewski, Robert Pak, Inkyu
Park, Heinz Pernegger, Corey Reed, Michael Ricci,
Christof Roland, Gunther Roland, Joe Sagerer,
Iouri Sedykh, Wojtek Skulski, Chadd Smith, Peter
Steinberg, George Stephans, Andrei Sukhanov,
Marguerite Belt Tonjes, Adam Trzupek, Carla
Vale, Siarhei Vaurynovich, Robin Verdier, Gábor
Veres, Edward Wenger, Frank Wolfs, Barbara
Wosiek, Krzysztof Wozniak, Alan Wuosmaa, Bolek
Wyslouch, Jinlong Zhang ARGONNE NATIONAL
LABORATORY BROOKHAVEN NATIONAL LABORATORY INSTITU
TE OF NUCLEAR PHYSICS, KRAKOW MASSACHUSETTS
INSTITUTE OF TECHNOLOGY NATIONAL CENTRAL
UNIVERSITY, TAIWAN UNIVERSITY OF ILLINOIS AT
CHICAGO UNIVERSITY OF MARYLAND UNIVERSITY OF
ROCHESTER
68 Participants 8 Institutions 3 Countries
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Outline

• PHOBOS multiplicity detector
• Centrality determination and cross checks
• Minimum-bias pseudorapidity distribution
• Systematic errors
• Comparison of d Au to Au Au and p p
  systems
• Comparison to the predictions of parton
  saturation model and microscopic models
  (HIJING, RQMD, AMPT)
• Summary

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PHOBOS Multiplicity Detector

• 4p Multiplicity Array
• - Central Octagon Barrel
• - 6 Rings at higher Pseudorapidity
• Triggering Scintillator counter arrays

ZDC
1m
Triggering Scintillatorcounter arrays
Ring Counters
Octagon
ZDC
Sample Silicon pad sizes Octagon Detector 2.7 x
8.8 mm2 Ring Counter 20 105 mm2
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PHOBOS Capability in Charged Particle
Multiplicity Analysis
Event display of One collision event
f
Octagon region
Rings
Rings

• Two analysis methods
• 1- Hit-Counting Analysis based on ratio
  of hit pads to empty pads using
  Poisson statistics
• 2- Analog Analysis based on particle
  energy deposited in each pad

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Extensive systematic Au Au data
Phys. Rev. Lett., 91, 052303 (2003)
200 GeV
19.6 GeV
130 GeV
PHOBOS
PHOBOS
PHOBOS
dN/dh
Typical systematic band
(90C.L.)
h
h
h

• Phys. Rev. Lett. 85, 3100 (2000)
• Phys. Rev. Lett. 87, 102303 (2001)
• Phys. Rev. C 65 , 31901R (2002)
• Phys. Rev. Lett. 88 , 22302 (2002)
• Phys. Rev. C 65 , 061901R (2002)
• Phys. Rev. Lett. 91, 052303 (2003)
• nucl-ex/0301017, subm. to PRL
• nucl-ex/0311009, subm. to PRL

PHOBOS Multiplicity papers
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Parton Saturation Describes Au Au
Kharzeev Levin, Phys. Lett. B523 (2001) 79
Au Au at 130 GeV

• We need a simpler system such as d Au in order
  to understand a complex system Au Au
• The results of dAu are crucial for testing the
  saturation approach

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PHOBOS Capability in Charged Particle
Multiplicity Analysis

• The goal is to measure minimum-bias dNch/dh
• Challenge is to correct for trigger and event
  selection bias
• Measure the dNch/dh in narrow bins of centrality
  and integrate over centrality to produce a
  minimum-bias result
• Cross check influence of auto-correlations

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Centrality Determination
ETot signal distributions Data and MC unbiased
Efficiency distribution for ETot signal
Overall trigger and vertex-finding
efficiency is 83
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Centrality Determination
Comparison of the signal distributions from Data
and MC (HIJING)
DATA measured cross section
Normalize
MC distribution with trigger and vertex bias
Scale

• Data and MC (biased) distributions match well
• - Data cut MC cut X scale factor

Scaling factor 1.046
Details of centrality determination were
presented in DNP talks A. Iordanova and R.
Hollis at UIC
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Centrality Determination
- Unbiased ETot signal distribution represents
the full geometrical cross section - Slice this
distribution into percentile bins - For each
slice we extract dN/dh
HIJING

• Number of participants for minimum-bias is
  

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Five Distinct Silicon Centrality Methods for
Cross Checks
2) EOct method h lt 3
3) EAuDir method h lt -3
1) ETot method h lt 5.4
EOct
ETot
EAuDir
Centrality methods
4) EdDir method h gt 3
5) ERing method 3 lth lt 5.4
EdDir
ERing
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Minimum-Bias dN/dh Obtained from the Five
Distinct Silicon Centrality Methods
The distributions agree to within 5
PHOBOS DATA
PHOBOS DATA
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Final Minimum-Bias distribution obtained from
Silicon Centrality Methods
PHOBOS DATA

• In the following, we will discuss the
  systematic errors

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Systematic Errors
These systematic errors are h-dependent and the
major contributions are

• Analysis methods Digital and Analog methods
  1-5
• Silicon centrality methods 1-5
• HIJING/ feed-down corrections 5-18
• Efficiency from a different Monte-Carlo
  simulation 5

At h0 the total systematic error is 7
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Final Minimum-Bias Pseudorapidity Distribution
in d Au at 200 GeV
nucl-ex/0311009 and Submitted to PRL

• Charged particle pseudorapidity density near
  midrapidity is

PHOBOS DATA

• Integrated primary charged particle
  multiplicity in the measured region is

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Estimates of the Total Charged Particle Production
Using AMPT Model
Using Triple Gaussian fit

• Upper limit including systematic errors

• Estimated total charged particle multiplicity is
  

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Comparison of d Au to Au Au and p p
Systems at the Same Energy
nucl-ex/0311009 and Submitted to PRL

• Normalized to the number of participants / 2
• Compared to p p collisions
• increase in particle production in the gold
  direction
• reduction of particle production in the deuteron
  direction
• The total integrated charged particle
  multiplicity normalized to the number of
  participant in d Au and p p is approximately
  the same

PHOBOS DATA d Au and Au Au
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Comparison to Parton Saturation and RQMD Models
nucl-ex/0311009 and Submitted to PRL

• Parton saturation (KLN) and RQMD models are
  inconsistent with the data
• KLN model overestimates the height of the gold
  side peak, underestimates its width, and predicts
  the peak at h -3 rather than h -1.9 as in
  data.

Parton saturation model predictions for d Au
D. Kharzeev et al., arXivhep-ph/0212316
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Comparison to AMPT and HIJING Models
nucl-ex/0311009 and submitted to PRL

• The HIJING calculation
• reproduces the deuteron side and the peak of the
  gold-side
• fails to reproduce the tail in the gold direction
  (h lt -2.5).
• AMPT predictions
• With without final-state interactions fall
  close to the data.
• FSI appear to broaden the gold-side peak, leading
  to moderate increase of the particle multiplicity
  in the region h lt -3.5.

AMPT predictions for d Au Zi-Wei Lin et al.,
arXivnucl-ph/0301025
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Ratio of the Model predictions to data

• Quantitative evaluation of the model predictions,
  expressed as the ratio of the model prediction to
  the data

nucl-ex/0311009 and submitted to PRL
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Summary

• The dN/dh in d Au collisions at 200 GeV has
  been measured
• The distribution is broader than pp and peaked
  in the gold direction
• The average pseudorapidity density is
• The measured integrated charged particle
  multiplicity is
• The total integrated charged particle
  multiplicity normalized to the number of
  participant in d Au and p p is approximately
  the same
• Comparison to the predictions of microscopic
  models is made
• The data disfavors the predictions of parton
  saturation model

• The latest news from PHOBOS More to come !