Russell Betts (UIC) for the PHOBOS Collaboration Multiplicity Measurements with The PHOBOS Detector 18 th Winter Workshop on Nuclear Dynamics Nassau, Jan 20 th -27 th,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  Multiplicity Array - Octagon, Vertex & Ring Counters Two Mid-rapidity Spectrometers TOF wall for High-Momentum PID Triggering -Scintillator Paddles - Zero Degree Calorimeter Silicon Pad channels

Outline of Talk Centrality Determination N participant and N collision 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) Events Triggering on Collisions Negative Paddles Positive Paddles ZDC NZDC P Au x z PP PN Paddle Counter Valid Collision ZDC Counter

Trigger Selection - ZDC vs Paddles Peripheral b Central b

Determining Centrality N part HIJING + GEANT Glauber Calculation Model of Paddle Response Paddle signal (a.u.) Counts

Estimating 97% when really 94% overestimates N part Uncertainty on N part Measurement sensitive to trigger bias –“Minimum-bias” still has bias –Affects most peripheral events Paddle signal (a.u.) Counts

Octagon Rings Hits in One Layer of Silicon Vertex Energy Spectrum (  E) in Si pads 1 hit 2 hits Data MC Multiplicity Distributions

Au+Au Collision Event Display

Event Vertex Finding +z Vertex Resolution:  x ~ 450  m  y ~  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 K s and  2% Background: Combinatorial,  -electrons - 1.5% MC Generators: Different particle production, background etc. - 5% Total: 7.5%

Analog and Digital Hit-Counting Octagon, Ring and Vertex Detectors (unrolled) Count Hits or Deposited Energy  

Discriminating Background with dE  E (“MIP”)  E (“MIP”) Data Monte Carlo Si  E vs.  in the Octagon From vertex Not from vertex  

1Count hits binned in , centrality (b) 2Calculate acceptance A(Z VTX ) for that event 3Find the occupancy per hit pad O( ,b) 4Fold in a background correction factor f B ( ,b)    E deposition in multiplicity detectors for 1 event. dN ch dd =  hits O( ,b) ×f B ( ,b) A(Z VTX )

“Measuring” the Occupancy N=number of tracks/pad  =mean number of tracks/pad The numbers of empty, and occupied, pads determine the occupancy as a function of ,b Method: Assume Poisson statistics N tracks /hit pad  0-3% 50-55% Octagon Rings (central) (peripheral)

MC, Occupancy Corrected MC “truth”   Compare PHOBOS Monte Carlo “data” analyzed using occupancy corrections to “truth” - the difference gives corrections for remaining background. fB(,b)fB(,b) f B =MC Truth /MC Occ dN ch /d  Estimating remaining backgrounds

Energy Loss  Multiplicity 300  m Si Measured S/N = << Landau Width Use Non-Hit pads - for Common-Mode Noise Suppression M = 240 ± 15 ± 5 ± CMN for one sensor (120 channels) at  = Energy deposited in i th pad (truncated) corrected for angle of incidence Mean energy loss for one particle traversing pad RATIO OF TOTAL TRACKS TO PRIMARY TRACKS

Uncertainty in Theoretical Predictions

Constraining the Models

Ratio 200/130 GeV Phobos Measurement Ratio 200/130 averaged for four PHOBOS methods R 200/130 = / Moderate Increase in Energy Density? Systematic Uncertainty

Hard and Soft Processes Soft processes (p T < 1 GeV) –Color exchange excites baryons –Baryons decay to soft particles –Varies with number of struck nucleons “Wounded Nucleon Model” Hard processes (p T > 1 GeV) –Gluon exchange in a binary collision creates jets –Jets fragment into hadrons, dominantly at mid-rapidity (mini)jet

Multiple Collisions with Nuclei Nuclei are extended –R Au ~ 6.4 fm ( m) –cf. R p ~.8 fm Geometrical model –Binary collisions (N coll ) –Participants (N part ) Nucleons that interact inelastically –Spectators (2A – N part ) p+A: N part = N coll + 1 (N part ~ 6 for Au) A+A: N coll  N part 4/3 Participants Spectators b(fm) b N coll N part pp collisions pA collisions

Hard & Soft What about non-central events? We already expect that charged particle production can have two components: We can tune the relative contribution by varying the collision centrality proton-proton multiplicity Fraction from hard processes Is this Description unique ?

Gluons recombine at a critical density characterized by “saturation” scale Q s 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 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 E cm Increase  =  y beam Scaling in fragmentation region HI part. Production is increased at mid-rapidity 7-10% syst error

Scaling in the Fragmentation Region Fragmentation UA5: Alner et al., Z. Phys. C33,1 (1986) PHOBOS 2000/ % 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