Centrality Dependence of Pseudorapidity Distributions in d Au collisions at vs 200GeV - PowerPoint PPT Presentation

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Centrality Dependence of Pseudorapidity Distributions in d Au collisions at vs 200GeV

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Used a shape matching algorithm between Data and Simulations ... Used ERing. Least auto-correlation bias (from Data and MC studies) Octagon. Rings. Rings ... – PowerPoint PPT presentation

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Title: Centrality Dependence of Pseudorapidity Distributions in d Au collisions at vs 200GeV


1
Centrality Dependence of Pseudorapidity
Distributions in dAu collisions at vs 200GeV
  • Richard S Hollis
  • University of Illinois at Chicago
  • For the collaboration

2
Collaboration (October 2004)
Burak Alver, Birger Back, Mark Baker, Maarten
Ballintijn, Donald Barton, Russell Betts, Abigail
Bickley, Richard Bindel, Wit Busza
(Spokesperson), Alan Carroll, Zhengwei Chai,
Vasundhara Chetluru, Patrick Decowski, Edmundo
García, Tomasz Gburek, Nigel George, Kristjan
Gulbrandsen, Clive Halliwell, Joshua Hamblen,
Ian Harnarine, Conor Henderson, David Hofman,
Richard Hollis, Roman Holynski, Burt Holzman,
Aneta Iordanova, Jay Kane, Nazim Khan, Piotr
Kulinich, Chia Ming Kuo, Wei Li, Willis Lin,
Steven Manly, Alice Mignerey, Gerrit van
Nieuwenhuizen, Rachid Nouicer, Andrzej
Olszewski, Robert Pak, Heinz Pernegger, Corey
Reed, 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, Sergei Vaurynovich, Robin Verdier,
Gábor Veres, Peter Walters, Edward Wenger, Frank
Wolfs, Barbara Wosiek, Krzysztof Wozniak, Alan
Wuosmaa, Bolek Wyslouch ARGONNE NATIONAL
LABORATORY BROOKHAVEN NATIONAL LABORATORY INSTITU
TE OF NUCLEAR PHYSICS PAN, KRAKOW MASSACHUSETTS
INSTITUTE OF TECHNOLOGY NATIONAL CENTRAL
UNIVERSITY, TAIWAN UNIVERSITY OF ILLINOIS AT
CHICAGO UNIVERSITY OF MARYLAND UNIVERSITY OF
ROCHESTER
3
Outline
  • dAu Centrality
  • New Results
  • Shapes
  • Limiting Fragmentation
  • Integrated Yield
  • Limiting Fragmentation Revisited
  • Conclusion

4
Detector
Au
Trigger Apparatus Paddles ? One Hit on Each
Array is the Minimum-Bias Trigger
d
  • Analysis Apparatus
  • 4p Multiplicity Array
  • Central Octagon Barrel
  • 6 Rings at higher (Pseudo) Rapidity

5
dAu Event Selection
Shapes agree reasonably in High multiplicity
region
  • Event Selection
  • Clean-up by requiring a valid silicon vertex
  • Efficiency
  • Used a shape matching algorithm between Data and
    Simulations (HIJING or AMPT)
  • Efficiency includes Trigger and Vertex finding
    efficiency
  • Estimated to be 83

Hijing GEANT Data
Data inefficient for peripheral events
EOct is the summed charge deposited in the
Octagon detector
6
dAu Centrality
  • Centrality binning
  • Used ERing
  • Least auto-correlation bias (from Data and MC
    studies)
  • Centrality
  • Correct for efficiency
  • Divide data into 20 bins

Primary Trigger (Scintillator) Paddles
Octagon
Rings
Rings
?
Schematic Plot not to scale
7
Data arXivnucl-ex/0409021
Deuteron-going hemisphere
Gold-going hemisphere
  • Five Centrality Classes
  • Each of 20 cross-section
  • Brief Observations
  • Increase centrality
  • Total number of particles grows
  • Asymmetry grows
  • Mean ? shifts to Gold-going hemisphere

8
Limiting FragmentationMeasuring the Total Yield
  • Limiting Fragmentation
  • Yield of particles is the same close to the beam
    rapidity of the target nucleus
  • Independent of energy
  • Can shift our distributions by the beam rapidity
    of the gold.
  • Lends guidance to extrapolate the total
    charged-particle yield

50-70 Central
pEmulsion ? 38.7GeV ? 23.7GeV ? 19.4GeV ?
11.2GeV 6.7GeV
9
Integrated YieldsNch scaled by Npart/2
  • dAu Data
  • consistent with pp (UA5)
  • Lower than the PHOBOS AuAu data
  • 20-25 lower
  • Compared to the 50 most central AuAu

10
Integrated YieldsNch(dAu) scaled by Nch(pp)
  • Scale by pp for comparison with lower energy
    data
  • All data fall on a common line
  • RA 0.5ltNpartgt

11
Limiting FragmentationRevisited
  • Close to the deuteron beam rapidity
  • Same Limiting fragmentation observations
  • Departure point from the limiting curve
  • Determined by kinematics
  • Collision Energy
  • Can compare the limiting slopes in both rest
    frames
  • invert the ?ytarget figure

Rest position of the deuteron nucleus
12
Limiting FragmentationLimiting Curves
  • Limiting curve 50-70 centrality class
  • Similar (yield/?) slope
  • both target and projectile
  • Limiting curves offset from each other in ? space
    1 unit
  • SIMILAR limiting slopes only for peripheral
    centrality classes!

13
Limiting FragmentationDeparture Points in
dNch/d?-space
By eye, departure point from limiting curve
different 38.7GeV ? large uncertainty in the
departure point.
14
Limiting FragmentationDeparture Points in
dNch/d?-space
Scale
Scale (a) distribution such that the deuteron
peak is the same as the gold peak (equalize the
dashed lines) 20 increase
15
Limiting FragmentationDeparture Points in
dNch/d?-space
Scale
By eye, departure point from the limiting curve
relatively the same
16
Conclusions
  • Detailed centrality dependence of dAu collisions
  • Total yield scaled by 0.5ltNpartgt
  • consistent with pp data
  • Lower than AuAu data (top 50)
  • Observe consistency with lower energy data
  • Total yield / pp
  • Limiting fragmentation regions
  • Relative departure points from the limiting curve
    are the same in the gold and deuteron rest frames.
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