Download - Charged-particle dN/d h from PHOBOS
Charged-particle dN/d from PHOBOS
A. H. Wuosmaa
(Argonne National Laboratory)
for the
PHOBOS Collaboration
Quark Matter 2001
The PHOBOS CollaborationARGONNE NATIONAL LABORATORY
Birger Back, Nigel George, Alan Wuosmaa
BROOKHAVEN NATIONAL LABORATORY
Mark Baker, Donald Barton, Alan Carroll, Stephen Gushue, George Heintzelman, Robert Pak, Louis Remsberg, Peter Steinberg, Andrei Sukhanov
INSTITUTE OF NUCLEAR PHYSICS, KRAKOW
Andrzej Budzanowski, Roman Holynski,, Jerzy Michalowski, Andrzej Olszewski, Pawel Sawicki , Marek Stodulski, Adam Trzupek, Barbara Wosiek, Krzysztof Wozniak
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
Wit Busza* , Patrick Decowski, Kristjan Gulbrandsen, Conor Henderson, Jay Kane , Judith Katzy, Piotr Kulinich, Johannes Muelmenstaedt, Heinz Pernegger, 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
NATIONAL CENTRAL UNIVERSITY, TAIWAN
Willis Lin, JawLuen Tang
UNIVERSITY OF ROCHESTER
Erik Johnson, Josh Hamblen, Nazim Khan, Steven Manly, Inkyu Park, Wojtek Skulski, R. Teng, Frank Wolfs
UNIVERSITY OF ILLINOIS AT CHICAGO
Russell Betts, Clive Halliwell, David Hofman, Burt Holzman, Wojtek Kucewicz, Don McLeod, Rachid Nouicer, Michael Reuter
UNIVERSITY OF MARYLAND
Richard Bindel, Edmundo Garcia-Solis, Alice Mignerey
* spokesperson
Why study dNch/d?• dNch/d is sensitive to all aspects of
charged-particle production in heavy-ion collisions:– Interplay between hard and soft processes– Effects of shadowing, jet quenching– Reaction dynamics, re-scattering– Full distribution reflects a time integral of
particle production throughout the collision and total entropy production
• Lots of existing data for pp, pA, AB,AA– How do RHIC data fit into this picture?
Charged-particle Multiplicity in Au-Au at RHIC Energies
Influence of various physical effects on dNch/din very central collisions
(Wang & Gyulassy,Private communication)
130GeV)NNs(
Octagon Multiplicity Detector
Ring Multiplicity Detectors
The PHOBOS Detector
All multiplicity detectorsare silicon pad sensors
Coverage of multiplicity detectors in
0 1 2 3 4 512345
1m2m
5m
Schematic Multiplicity Detector
coverage for vertex at Z=0.
What I will not discuss:
• Event Selection
• Vertex Determination
• Centrality DeterminationSee Talks by:
R. Pak, Tuesday 3:20 J. Katzy, Wednesday 4:40
And see Poster by: P. Decowski
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)
dNch
d =hits
O(,b) ×fB(,b)
A(ZVTX)
E depositionin multiplicitydetectors for 1 event.
“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)
Discriminating background with E 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
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
45-55% 35-45% 25-35%
15-25% 6-15% 0-6%
dNch
/d
dNch
/d
dNch/d for different centrality bins
Octagon RingsStatistical Unc. onlyStatistical Unc. only PHOBOS Prelim.
Centrality Dependence of Nch(||<5.4)
Npart
PHOBOS Prelim.
±10% Systematic Uncertainty±10% Systematic Uncertainty
HIJING
Nch
(||
<5.
4)
Shapes of dNch/d for different Npart
dNch
/d
(dN
ch/d
)/(
½N
pa
rt)
dNch
/d
Data
HIJING
HIJING
(dN
ch/d
)/(
½N
pa
rt)
Systematic error ±(10%-20%)Systematic error ±(10%-20%)PHOBOS Prelim.
354
216
102
Mean Npart% 0-3
15-20
35-40
Data
Centrality dependence of dNch/d|
Npart
(dN
ch/d
)/(
½N
pa
rt)
||
<1
5-5.4
4-4.4
3-3.4
2-2.4
PHOBOS Prelim.Symbols: Solid lines: HIJING
Errors are systematic
Summary• First multiplicity distributions over 4 now
available at for wide range of impact parameters
• Nch(||<5.4)=4100±410 for the 3% most central collisions
• Distributions are somewhat wider than predicted by some models
• (dNch/d/(½Npart) in fragmentation region drops by ~½ from Npart=100 to 350
• Outlook: coming analyses: EbyE, d2N/dd(I. Park, Wed. 5:55)
130GeVNNs
“The appetizers were truly delightful, and Iam anxiously looking forward to the main course” -N. Khrushchev
Or -
We can’t wait for 200 GeV! NNs
Data and Monte Carlo
DataMonte Carlo
Comparison of DE measuredin the Octagon at ||~3.0, with spectrum predicted by Monte-Carlo:Conclusion: MC is a good predictor of background.
Backup Method: Study E spectra
Ntr
acks
/hit
pad
E (MIPs)
Cou
nts
1 32
1hit
2hits3hits
oct rings
Occupancy reality check
Can determine from DE relative yields of events with1,2,3… hits/pad: gives independent measurement of Occupancy
Good: fewer potentially unjustified assumptionsBad: Fitting procedure somewhat unstable, occasional large errors
Very Good: We get the same answer in the end!!