How Strange is ? Current Results and Future Prospects George Stephans for the Phobos collaboration 24-July-Y2K Strangeness 2000 First RHIC Physics results! Mid-rapidity dN/d  for Central Au+Au

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

Relativistic Heavy Ion Collider 13 June: 1 st Phobos  s = 56 AGeV 24 June: 1 st Phobos  s = 130 AGeV

PHOBOS Apparatus

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

First Collisions at PHOBOS For monitoring luminosity, background was rejected by requiring >2 hits in both of the paddles As soon as collisions appeared on the morning of June 13, we saw them Recorded 1000 collisions during that first night at  s = 56 AGeV

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

Examples of events Hits in VTX Hits in SPEC Tracks in SPEC 130 AGeV 56 AGeV 130 AGeV Note: These events will give low p 

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, N part Observables: dN/d  |  <1 ( where  = - ln tan (  /2) ) Charged particle density averaged over –1 <  < 1 dN/d  |  <1 / (  Npart  /2 ) Particles produced per participant pair (dN/d  |  <1 ) 130 / (dN/d  |  <1 ) 56 Scaling of density with energy Results presented will be for most central collisions

What do we learn from dN/d  |  <1 ? Initial energy density in the collision  is related to dN/dy e.g. Bjorken estimate dN/dy is related to dN/d  Difference <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 dN/d  dN/dy

Monte Carlo Simulations Event generator & detector simulation used for: A proper description of all detector effects Estimate of number of participants We use the following 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

Collision Event Selection 1: Paddle Timing  t < 8 ns selects events with vertex |z|<120 cm This sample still contains background events 2: ZDC Timing  t < 20 ns confirms selected events as collisions However, at  s=56 AGeV, this cut rejects ~10% of central collisions. At  s=130 AGeV, the loss is <1%. 3: Paddle Multiplicity Requiring PP,PN to have a large ADC sum recovers central events lost to ZDC cut. Offline event trigger is 1 AND (2 OR 3)

Centrality Selection Paddles cover 3<|  |<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 3<|  |<4.5 Hijing 130 AGeV b < 3 fm PN PP 

Extracting N part 6% most central events based on paddles gives N part Events/bin Average paddle ADC sum Data MC Shaded region is most central 6% by paddle cut on both plots

Understanding Paddle Counters DATA MC 56 AGeV 130 AGeV PN 12 PP 12

z x Measuring Vertex: Procedure Spectrometer sits very close to vertex High resolution tracking in 6 planes gives excellent vertex resolution

Measuring Vertex: Results Pointing accuracy describes how extrapolated tracks deviate from calculated vertex. Compares well with HIJING simulation Track deviation at vertex Data: points MC: line

Vertex Distributions X Y Z Beam Orbit can be calculated for each fill For the 130 AGeV data X = -.17 cm,  X =.17 cm Y =.14 cm,  Y =.08 cm We make a cut in Z to define a fiducial volume

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

Event Statistics 56 AGeV Collision Events : 6352 Central Events : 382 Central Events (–25 < z < 15) : AGeV Collision Events : Central Events : 724 Central Events (–25 < z < 15) : 151

Tracklets: Procedure VTX Tracklets Two hit combinations that point to the vertex d  =  2 –  1 Good tracklets have d  <.1 SPEC Tracklets Two hit combinations that point to the vertex dR =  (d  2 – d  2) Good tracklets have dR<.02

Tracklets: Result Peaked at ~0 so geometry is well understood Width agrees with simulation

Measuring dN/d  with tracklets Number of reconstructed tracklets is proportional to dN/d  |  <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  Run the same algorithm through the MC Folds in detector response and acceptance

Uncorrected dN/d  Final result extracted by integrating over Z

Derivation of dN/d  Extract  from correlation of Primaries in –1 <  < 1 Measured number of tracklets dN/d  Number of Tracklets 5<z<10 SPEC VTX

Final Results for dN/d  56 AGeV130 AGeV dN/d  |  <1 408±12(stat) ±30(syst) 555±12(stat) ±35(syst) dN/d  |  <1 per participant pair 2.47±0.10± ±0.10±0.25 Ratio of density per participant pair 1.31±0.04±0.05

Comparisons with pp Submitted for publication

Towards a Stranger Future Strengths of Phobos High event capability to give a large data sample Minimum bias trigger with multiple ways to select centrality and vertex location Numerous redundant quality checks to differentiate interesting rare events from rare combinations of background, pile-up, etc Broad, segmented multiplicity detector Almost complete charged particle coverage Global and local particle density fluctuations Two-arm spectrometer with low p   cutoff Sensitive to physics of large volumes Particle spectra, ratios, and correlations May be possible to detect  near p   ~ 0

A Beginning, not a Conclusion RHIC runs !!!! So does ! Now the real fun begins...