Charged Particle Multiplicity Near Mid-Rapidity in Central Au Au Collisions at ?s=56 and 130 AGeV

1
Charged Particle Multiplicity Near Mid-Rapidity
in Central AuAu Collisions at ?s56 and 130
AGeV

• Wit Busza for the PHOBOS collaboration
• 19 July 2000
• Brookhaven National Laboratory

2
Relativistic Heavy Ion Collider

• 12 June 1st Collisions _at_ ?s 56 AGeV
• 24 June 1st Collisions _at_ ?s 130 AGeV

3
PHOBOS Collaboration

• ARGONNE NATIONAL LABORATORY
• Birger Back, Nigel George, Alan Wuosmaa
• BROOKHAVEN NATIONAL LABORATORY
• Mark Baker, Donald Barton, Mathew Ceglia, Alan
  Carroll, Stephen Gushue, George Heintzelman,
  Hobie Kraner ,Robert Pak,Louis Remsberg, Joseph
  Scaduto, Peter Steinberg, Andrei Sukhanov
• INSTITUTE OF NUCLEAR PHYSICS, KRAKOW
• Wojciech Bogucki, Andrzej Budzanowski, Tomir
  Coghen, Bojdan Dabrowski, Marian Despet,
  Kazimierz Galuszka, Jan Godlewski , Jerzy Halik,
  Roman Holynski, W. Kita, Jerzy Kotula, Marian
  Lemler, Jozef Ligocki, Jerzy Michalowski, Andrzej
  Olszewski?, Pawel Sawicki , Andrzej Straczek,
  Marek Stodulski, Mieczylsaw Strek, Z. Stopa, Adam
  Trzupek, Barbara Wosiek, Krzysztof Wozniak, Pawel
  Zychowski
• JAGELLONIAN UNIVERSITY, KRAKOW
• Andrzej Bialas, Wieslaw Czyz, Kacper Zalewski
• MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• Wit Busza, Patrick Decowski, Piotr Fita, J.
  Fitch, C. Gomes, Kristjan Gulbrandsen, P.
  Haridas, Conor Henderson, Jay Kane , Judith Katzy
  , Piotr Kulinich, Clyde Law, Johannes
  Muelmenstaedt, Marjory Neal, P. Patel, Heinz
  Pernegger, Miro Plesko, Corey Reed, Christof
  Roland, Gunther Roland, Dale Ross, Leslie
  Rosenberg, John Ryan, Pradeep Sarin, Stephen
  Steadman, George Stephans, Katarzyna Surowiecka,
  Gerrit van Nieuwenhuizen, Carla Vale, Robin
  Verdier, Bernard Wadsworth, Bolek Wyslouch
• NATIONAL CENTRAL UNIVERSITY, TAIWAN
• Yuan-Hann Chang, Augustine Chen, Willis Lin,
  JawLuen Tang
• UNIVERSITY OF ROCHESTER
• A. Hayes, Erik Johnson, Steven Manly, Robert Pak,
  Inkyu Park, Wojtech Skulski, Teng, Frank Wolfs
• UNIVERSITY OF ILLINOIS AT CHICAGO
• Russell Betts, Christopher Conner, Clive
  Halliwell, Rudi Ganz, Richard Hollis, Burt
  Holzman,, Wojtek Kucewicz, Don McLeod, Rachid
  Nouicer, Michael Reuter
• UNIVERSITY OF MARYLAND
• Richard Baum, Richard Bindel, Jing Shea, Edmundo
  Garcia-Solis, Alice Mignerey

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PHOBOS Apparatus
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Commissioning Run Setup

• Configuration used for first data
• SPEC 6 planes of a single spectrometer arm
• VTX Half of the Top Vertex Detector
• Paddles 2 sets of 16 scintillators paddles

Acceptance of SPEC and VTX
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PHOBOS Trigger
Positive Paddles
Negative Paddles
ZDC N
ZDC P
Au
Au
PN
PP

• Very loose coincidence of paddle counters (38ns)
• Includes collision background
• Allows clean separation of collisions and
  background offline

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First Collisions at PHOBOS

• Background was rejected by requiring at least 3
  hits in each set of paddles
• As soon as collisions appeared on the morning of
  June 13, we were ready
• Recorded 1000 collisions during the night at ?s
  56 AGeV

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Examples of events
Hits in SPEC
Tracks in SPEC
Hits in VTX
130 AGeV
130 AGeV
56 AGeV
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Event selection

• Paddle Timing
• Dt lt 8 ns selects events with vertex zlt120 cm
• Still contains background events
• ZDC Timing
• Dt lt 20 ns confirms selected events as collisions
• However, at ?s56 AGeV, rejects 10 of central
  collisions. lt 1 at ?s130 AGeV.
• Paddle Multiplicity
• Requiring PP,PN to have a large ADC sum recoups
  central events lost to ZDC cut.
• Offline event trigger is 1 AND (2 OR 3)

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Event Statistics

• 56 AGeV
• Collision Events 6352
• Central Events 382
• Central Events (25 lt z lt 15) 103
• 130 AGeV
• Collision Events 12074
• Central Events 724
• Central Events (25 lt z lt 15) 151

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Variables Observables

• Variables
• Beam Energy
• RHIC delivered ?s 56 AGeV and 130 AGeV
• Centrality of collision
• Multiplicity in the paddles is related to number
  of participants, Npart
• Observables
• dN/dh hlt1 ( where h - ln tan (q/2) )
• Charged particle density averaged over 1 lt h lt 1
• dN/dh hlt1 / ( ?Npart?/2 )
• Particles produced per participant pair
• (dN/dh hlt1 )130 / (dN/dh hlt1 )56
• Scaling of density with energy
• Results presented will be for most central
  collisions

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What do we learn from dN/dh hlt1

• Initial energy density in the collision
• e is related to dN/dy
• e.g. Bjorken estimate
• dN/dy is related to dN/dh
• lt 5 CERN LAB frame, 15 RHIC CM frame
• We can also compare to pp, pp data
• Energy scaling is sensitive to interplay between
  hard and soft processes

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Monte Carlo Simulations

• Event generator and detector simulation used for
  
• A proper description of all detector effects
• Estimate of number of participants
• We use several packages
• HIJING 1.35
• Event generator for AA collisions
• Hard Processes, Shadowing, Jet Quenching
• GEANT 3.21
• Detector simulations
• Production of secondaries in apparatus
• Measured detector response
• Derived from test-beam results
• Generates fake data for silicon and paddle
  detectors

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Centrality Selection

• Paddles cover 3lthlt4.5
• Sum of analog signals (gain-normalized) is
  proportional to the number of particles
• Secondaries deposit large amounts of energy. To
  reduce fluctuations, we use truncated mean

PP
PN
Hijing 130 AGeV b lt 3 fm
3lthlt4.5
h
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Understanding Paddle Counters
56 AGeV
130 AGeV
PP12
MC
PN12
DATA
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ZDC Sum vs. Paddle Sum
130 AGeV
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Estimating Npart
Events/bin
Npart

• 6 most central events based on paddles gives

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Signal Distributions in Si

• Critical test of detector understanding
• Both distributions contain the same number of
  central events
• Points are for VTX data
• No correction for detector thickness
• Histogram is for simulated VTX signals
• GEANT
• Response from test-beam
• Electronics noise
• Shulek correction

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Measuring Vertex

• Spectrometer sits very close to vertex
• High resolution tracking in 6 planes gives
  excellent vertex resolution

• Pointing accuracy describes how extrapolated
  tracks deviate from calculated vertex.
• Compares well with HIJING simulation

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Vertex Distributions
Y
X

• Beam Orbit can be calculated for each fill
• For the 130 AGeV data
• X -.17 cm, sX .17 cm
• Y .14 cm, sY .08 cm

• We make a cut in Z to define a fiducial volume

Z
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Tracklets

• VTX Tracklets
• Two hit combinations that point to the vertex
• dh h2 h1
• Good tracklets have dhlt.1

• SPEC Tracklets
• Two hit combinations that point to the vertex
• dR ? (dh2 df2)
• Good tracklets have dRlt.015

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Measuring dN/dh with tracklets

• Number of reconstructed tracklets is proportional
  to dN/dh hlt1
• To reconstruct tracklets
• Reconstruct vertex
• Define tracklets based on the vertex and hits in
  the front planes of SPEC and VTX
• Redundancy essentially eliminates feed-down,
  secondaries, random noise hits
• To determine a
• Run the same algorithm through the MC
• Folds in detector response and acceptance

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Uncorrected dN/dh
SPEC
VTX
tracklets
tracklets
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Derivation of dN/dh

• Extract a(Z) from correlation of
• Primaries in 1 lt h lt 1
• Measured number of tracklets

5ltzlt10
Number of Tracklets
VTX
SPEC
dN/dh
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Results
56 AGeV 130 AGeV
dN/dh hlt1 40812(stat) 30(syst) 55512(stat) 35(syst)
dN/dh hlt1 per participant pair 2.470.100.25 3.240.100.25
Ratio (density per participant pair) 1.310.040.05 1.310.040.05
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Systematic Uncertainties

• dN/dh
• Background subtraction on tracklets lt 5
• Uncertainty on a due to model differences lt 5
• Total contribution due to feed-down correction lt
  4 (typically 1)
• Total fraction lost due to stopping particles lt
  5
• Both are corrected via MC normalization
• Total uncertainty on dN/dh is 8
• ?Npart?
• Loss of trigger efficiency at low-multiplicity
  lt10
• Uncertainty on ?Npart ? lt1
• Uncertainty in modeling paddle fluctuations
• Uncertainty on ?Npart ? lt6
• ( dN/dh / ?Npart? )130 / ( dN/dh / ?Npart? )56
• Many uncertainties cancel in the ratio

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Comparisons with pp