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

Charged Particle Multiplicity Near Mid-Rapidity in Central Au+Au Collisions at  s=56 and 130 AGeV. Wit Busza for the PHOBOS collaboration 19 July 2000 Brookhaven National Laboratory. 12 June : 1 st Collisions @  s = 56 AGeV 24 June : 1 st Collisions @  s = 130 AGeV.

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

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  1. Charged Particle Multiplicity Near Mid-Rapidity in Central Au+Au Collisions at s=56 and 130 AGeV Wit Busza for the PHOBOS collaboration 19 July 2000 Brookhaven National Laboratory

  2. 12 June: 1st Collisions @ s = 56 AGeV 24 June: 1st Collisions @ s = 130 AGeV Relativistic Heavy Ion Collider

  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

  4. PHOBOS Apparatus

  5. 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 Commissioning Run Setup Acceptance of SPEC and VTX

  6. x z PHOBOS Trigger • Very loose coincidence of paddle counters (38ns) • Includes collision & background • Allows clean separation of collisions and background offline Positive Paddles Negative Paddles ZDC N ZDC P Au Au PN PP

  7. 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 First Collisions at PHOBOS

  8. Examples of events Hits in SPEC Tracks in SPEC Hits in VTX 130 AGeV 130 AGeV 56 AGeV

  9. Event selection • Paddle Timing • Dt < 8 ns selects events with vertex |z|<120 cm • Still contains background events • ZDC Timing • Dt < 20 ns confirms selected events as collisions • However, at s=56 AGeV, rejects ~10% of central collisions. < 1% at s=130 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)

  10. Event Statistics • 56 AGeV • Collision Events : 6352 • Central Events : 382 • Central Events (–25 < z < 15) : 103 • 130 AGeV • Collision Events : 12074 • Central Events : 724 • Central Events (–25 < z < 15) : 151

  11. 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 | |h|<1 ( where h = - ln tan (q/2) ) • Charged particle density averaged over –1 < h < 1 • dN/dh | |h|<1 /(Npart/2) • Particles produced per participant pair • (dN/dh | |h|<1 )130 / (dN/dh | |h|<1 )56 • Scaling of density with energy • Results presented will be for most central collisions

  12. What do we learn from dN/dh | |h|<1 • Initial energy density in the collision • e is related to dN/dy • e.g. Bjorken estimate • dN/dy is related to dN/dh • < 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

  13. 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

  14. Paddles cover 3<|h|<4.5 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 Centrality Selection PP PN Hijing 130 AGeV b < 3 fm 3<|h|<4.5 h

  15. Understanding Paddle Counters 56 AGeV 130 AGeV PP12 MC PN12 DATA

  16. ZDC Sum vs. Paddle Sum 130 AGeV

  17. 6% most central events based on paddles gives Estimating Npart Events/bin Npart

  18. 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 Signal Distributions in Si

  19. Pointing accuracy describes how extrapolated tracks deviate from calculated vertex. Compares well with HIJING simulation Spectrometer sits very close to vertex High resolution tracking in 6 planes gives excellent vertex resolution z x Measuring Vertex

  20. 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 Vertex Distributions Y X • We make a cut in Z to define a fiducial volume Z

  21. VTX Tracklets Two hit combinations that point to the vertex dh = h2 – h1 Good tracklets have dh<.1 Tracklets • SPEC Tracklets • Two hit combinations that point to the vertex • dR =  (dh2 + df2) • Good tracklets have dR<.015

  22. Measuring dN/dh with tracklets • Number of reconstructed tracklets is proportional to dN/dh | |h|<1 • 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

  23. Uncorrected dN/dh SPEC VTX tracklets tracklets

  24. Derivation of dN/dh • Extract a(Z) from correlation of • Primaries in –1 < h < 1 • Measured number of tracklets 5<z<10 Number of Tracklets VTX SPEC dN/dh

  25. Results

  26. Systematic Uncertainties • dN/dh • Background subtraction on tracklets < ±5% • Uncertainty on a due to model differences < 5% • Total contribution due to feed-down correction < 4% (typically 1%) • Total fraction lost due to stopping particles < 5% • Both are corrected via MC normalization • Total uncertainty on dN/dh is ±8% • Npart • Loss of trigger efficiency at low-multiplicity <10% • Uncertainty on Npart  <1% • Uncertainty in modeling paddle fluctuations • Uncertainty on Npart  <6% • ( dN/dh / Npart )130 / ( dN/dh / Npart )56 • Many uncertainties cancel in the ratio

  27. Comparisons with pp

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