Multiplicity Measurements with The PHOBOS Detector Russell Betts
Multiplicity Measurements with The PHOBOS Detector Russell Betts (UIC) for the PHOBOS Collaboration 18 th Winter Workshop on Nuclear Dynamics Nassau, Jan 20 th-27 th, 2002
The PHOBOS Collaboration 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 Mc. Leod, Rachid Nouicer, Michael Reuter, Joe Sagerer Richard Bindel, Alice Mignerey
Completed Spring 2001 • 4 p Multiplicity Array - Octagon, Vertex & Ring Counters • Two Mid-rapidity Spectrometers • TOF wall for High-Momentum PID • Triggering -Scintillator Paddles - Zero Degree Calorimeter 137000 Silicon Pad channels
Outline of Talk • Centrality Determination • Techniques for Multiplicity Measurements • • 1. Tracklets 2. Hit Counting 3. Energy Deposition Nparticipant and Ncollision Results 1. Energy Dependence for 1 2. Centrality Dependence 3. d. N/d Shapes Summary and Taster of Future Delights
Triggering on Collisions Positive Paddles Negative Paddles ZDC N Au Au ZDC Counter Events PN x ZDC P z PP Paddle Counter Valid Collision Dt (ns) • • • Coincidence between Paddle counters at Dt = 0 defines a valid collision. Paddle + ZDC timing reject background. Sensitive to 97± 3 % of inelastic cross section for Au+Au.
Trigger Selection - ZDC vs Paddles b Peripheral b Central
Counts Determining Centrality Counts Paddle signal (a. u. ) Npart • HIJING + GEANT • Glauber Calculation • Model of Paddle Response
Uncertainty on Npart • Measurement sensitive to trigger bias Counts – “Minimum-bias” still has bias – Affects most peripheral events • Estimating 97% when really 94% overestimates Npart Paddle signal (a. u. )
Multiplicity Distributions Hits in One Layer of Silicon Rings Vertex Octagon Energy Spectrum (DE) in Si pads 1 hit Data MC 2 hits
Au+Au Collision Event Display
Event Vertex Finding +z Vertex Resolution: sx ~ 450 mm sy ~ sz ~ 200 mm
Vertex Tracklet Reconstruction Tracklets are two point tracks that are constrained by the event vertex. d = 1 – 2 df = f 1 – f 2 |d | < 0. 04 |df| < 0. 3
Combinatorial Background All Pairs of Hits “Background Flip” Outer Hit Bin 10 (Data)
Backgrounds Weak Decays d Electrons
Vertex Tracklet Systematic Error • Reconstruction: Vertex selection, Tracklet algorithm etc. 1. 8% • Weak Decays: Mostly Ks and L - 2% • Background: Combinatorial, d-electrons - 1. 5% • MC Generators: Different particle production, background etc. - 5% • Total: 7. 5%
Analog and Digital Hit-Counting f -5. 5 -3 0 +3 Octagon, Ring and Vertex Detectors (unrolled) Count Hits or Deposited Energy +5. 5
Discriminating Background with d. E Monte Carlo DE (“MIP”) 12 8 4 12 8 0 4 0 DE (“MIP”) Data -6 -4 -2 0 2 4 6 h Not from vertex Si DE vs. h in the Octagon From vertex
DE deposition f in multiplicity detectors for 1 event. 1 2 3 4 Count hits binned in h, centrality (b) Calculate acceptance A(ZVTX) for that event Find the occupancy per hit pad O(h, b) Fold in a background correction factor f. B(h, b) d. Nch = Shits dh O(h, b) ×f. B(h, b) A(ZVTX)
“Measuring” the Occupancy Method: Assume Poisson statistics Ntracks/hit pad Octagon N=number of tracks/pad m =mean number of tracks/pad Rings 0 -3% (central) 50 -55% (peripheral) The numbers of empty, and occupied, pads determine the occupancy as a function of h, b
Estimating remaining backgrounds 600 400 MC “truth” 200 -6 -4 -2 0 2 Compare PHOBOS Monte Carlo “data” analyzed using occupancy corrections to “truth” - the difference gives corrections for remaining background. f. B=MCTruth/MCOcc 4 6 1. 0 0. 8 f. B( , b) d. Nch/dh MC, Occupancy Corrected 0. 6 0. 4 0. 2 -6 -4 -2 0 2 4 6
Energy Loss Multiplicity 300 mm Si Energy deposited in ith pad (truncated) corrected for angle of incidence Mean energy loss for one particle traversing pad RATIO OF TOTAL TRACKS TO PRIMARY TRACKS 0. 30 - 0. 40 Measured S/N = 10 - 20 << Landau Width Use Non-Hit pads - for Common-Mode Noise Suppression M = 240 ± 15 ± CMN for one sensor (120 channels) at = 0
Uncertainty in Theoretical Predictions
Constraining the Models
Ratio 200/130 Ge. V Ratio 200/130 averaged for four PHOBOS methods Phobos Measurement R 200/130 = 1. 14 +/- 0. 05 Moderate Increase in Energy Density? Systematic Uncertainty
Hard and Soft Processes • Soft processes (p. T < 1 Ge. V) – Color exchange excites baryons – Baryons decay to soft particles – Varies with number of struck nucleons • “Wounded Nucleon Model” (mini)jet • Hard processes (p. T > 1 Ge. V) – 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 – RAu ~ 6. 4 fm (10 -15 m) – cf. Rp ~. 8 fm • Geometrical model – Binary collisions (Ncoll) – Participants (Npart) • Nucleons that interact inelastically – Spectators (2 A – Npart) • p+A: Npart = Ncoll + 1 (Npart ~ 6 for Au) • A+A: Ncoll Npart 4/3 Spectators b Participants Spectators pp collisions p. A collisions 1200 400 Ncoll Npart b(fm) 0 9 18
Hard & Soft What about non-central events? We already expect that charged particle production can have two components: Fraction from hard processes proton-proton multiplicity We can tune the relative contribution by varying the collision centrality Is this Description unique ?
Parton Saturation • Gluons recombine at a critical • Gluons below x~1/(2 m. R) density characterized by “saturation” overlap in transverse plane with scale Qs 2 size 1/Q t • Below this scale, the nucleus looks “black” to a probe “Colored Glass Condensate” Mc. Lerran, Venugopalan, Kharzeev, Dumitru, Schaffner-Bielich… Scale depends on volume (controlled by centrality!)
Data and Models for 130 Ge. V Yellow band: Systematic Error
Data and Models for 200 Ge. V Yellow band: Systematic Error
Shapes of d. N/d Distributions at 130 Ge. V - Hit Counting • Shapes only weakly dependent on centrality • Differ in details
130 Ge. V (0 -6%) (35 -45%) AMPT (p-p) HIJING Most of “new” behavior is at mid-rapidity – detailed comparison with pp and p. A required.
Energy Dependence and Comparison to pp • Width increases with Ecm • Increase D = Dybeam • Scaling in fragmentation region HI part. Production is increased at mid-rapidity 7 -10% syst error
Scaling in the Fragmentation Region UA 5: Alner et al. , Z. Phys. C 33, 1 (1986) PHOBOS 2000/2001 7 -10% syst error Fragmentation
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 Ge. V Multiplicity at 20 Ge. V pp Data with PHOBOS at 200 Ge. V
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