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Performance of PHOBOS Vertex Finders in 200GeV pp Collisions at RHIC Richard S Hollis University of Illinois at Chicago For the PHOBOS Collaboration Fall.

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Presentation on theme: "Performance of PHOBOS Vertex Finders in 200GeV pp Collisions at RHIC Richard S Hollis University of Illinois at Chicago For the PHOBOS Collaboration Fall."— Presentation transcript:

1 Performance of PHOBOS Vertex Finders in 200GeV pp Collisions at RHIC Richard S Hollis University of Illinois at Chicago For the PHOBOS Collaboration Fall 2002 DNP meeting: Performance of PHOBOS Vertex Finders in 200GeV PP Collisions at RHIC: Richard S Hollis, UIC

2 Collaboration ARGONNE NATIONAL LABORATORYBirger Back, Alan Wuosmaa BROOKHAVEN NATIONAL LABORATORY Mark Baker, Donald Barton, Alan Carroll, Nigel George, Stephen Gushue, George Heintzelman, Burt Holzman, Robert Pak, Louis Remsberg, Peter Steinberg, Andrei Sukhanov INSTITUTE OF NUCLEAR PHYSICS, KRAKOWAndrzej Budzanowski, Roman Hołyński, Jerzy Michałowski, Andrzej Olszewski, Pawel Sawicki, Marek Stodulski, Adam Trzupek, Barbara Wosiek, Krzysztof Woźniak MASSACHUSETTS INSTITUTE OF TECHNOLOGYMaartin Ballintijn, Wit Busza (Spokesperson), Patrick Decowski, Kristjan Gulbrandsen, Conor Henderson, Jay Kane, Judith Katzy, Piotr Kulinich, Jang Woo Lee, Heinz Pernegger, Corey Reed, Christof Roland, Gunther Roland, Leslie Rosenberg, Pradeep Sarin, Stephen Steadman, George Stephans, Carla Vale, Gerrit van Nieuwenhuizen, Gábor Veres, Robin Verdier, Bernard Wadsworth, Bolek Wysłouch NATIONAL CENTRAL UNIVERSITY, TAIWANChia Ming Kuo, Willis Lin, Jaw-Luen Tang UNIVERSITY OF ILLINOIS AT CHICAGORussell Betts, Edmundo García, Clive Halliwell, David Hofman, Richard Hollis, Aneta Iordanova, Wojtek Kucewicz, Don McLeod, Rachid Nouicer, Michael Reuter, Joe Sagerer UNIVERSITY OF MARYLANDAbigail Bickley, Richard Bindel, Alice Mignerey, Marguerite Belt Tonjes UNIVERSITY OF ROCHESTERJoshua Hamblen, Erik Johnson, Nazim Khan, Steven Manly, Inkyu Park, Wojtek Skulski, Ray Teng, Frank Wolfs Fall 2002 DNP meeting: Performance of PHOBOS Vertex Finders in 200GeV PP Collisions at RHIC: Richard S Hollis, UIC Collaboration

3 Phobos Detector 4  Multiplicity Array Octagon, Vertex and Ring Counters Mid-rapidity Spectrometer TOF wall for high momentum PID Triggering Scintillator Paddle Counters Zero Degree Calorimeter (ZDC) Č erenkov Counters Fall 2002 DNP meeting: Performance of PHOBOS Vertex Finders in 200GeV PP Collisions at RHIC: Richard S Hollis, UIC Detector

4 Octagon: View of “unrolled” detector High Multiplicity (AA) → tracks through “Vertex Detector” and “Spectrometer” Low Multiplicity (PP)→ too few tracks! – need a different method Fall 2002 DNP meeting: Performance of PHOBOS Vertex Finders in 200GeV PP Collisions at RHIC: Richard S Hollis, UIC Octagon Vertex from Monte-Carlo Hits Holes for Vertex Detector and Spectrometer.

5 Particle along y,  = 0 D D cm of silicon Particle in y-z plane,  > 0 D/sin(  ) cm of silicon  Step 1 Particles traversing more material will deposit more energy – this is the principle behind the cosh(η) dependence (next slide). Fall 2002 DNP meeting: Performance of PHOBOS Vertex Finders in 200GeV PP Collisions at RHIC: Richard S Hollis, UIC Step 2 Z, beam axis

6 Step 2 Extract energy deposited in the octagon, as a function of pseudorapidity. Familiar cosh(η) dependence, lines for guidance. Fall 2002 DNP meeting: Performance of PHOBOS Vertex Finders in 200GeV PP Collisions at RHIC: Richard S Hollis, UIC Step 1 Single Event, Monte-Carlo 1000 Events, Monte-Carlo

7 Step 3 Divide out the cosh(η) dependence → independence of energy with pseudorapidity at low pseudorapidity → smaller energy deposits at high pseudorapidity. Step 4 Apply a simple merging technique → sum energies at high eta Fall 2002 DNP meeting: Performance of PHOBOS Vertex Finders in 200GeV PP Collisions at RHIC: Richard S Hollis, UIC Step 3 and 4 Single Event, Monte-Carlo 1000 Events, Monte-Carlo

8 Step 5 Make a cut on the data around the nominal MIP position → count the number of ‘Mip Hits’. Fall 2002 DNP meeting: Performance of PHOBOS Vertex Finders in 200GeV PP Collisions at RHIC: Richard S Hollis, UIC Step 5 Single Event, Monte-Carlo 1000 Events, Monte-Carlo

9 Optimised Mip Hits – best vertex Scan over possible vertices The process is repeated for all possible vertex positions (-90 to 90 cm). → ‘best’ position is found for most Mip Hits (for a given trial Z). This is due to the correction applied being ‘vertex’ dependent. Fall 2002 DNP meeting: Performance of PHOBOS Vertex Finders in 200GeV PP Collisions at RHIC: Richard S Hollis, UIC Iterations Single Event, Monte-Carlo True = -3.5 cm, Reconstructed = -3.9cm

10 Fall 2002 DNP meeting: Performance of PHOBOS Vertex Finders in 200GeV PP Collisions at RHIC: Richard S Hollis, UIC Accuracy, Purity, Efficiency Accuracy – how close to the true vertex Purity – how many within 1 sigma (2cm) of truth. Efficiency – how often is a vertex found Truth – Found Z position Monte-Carlo Eff,Acc,Pur 1

11 Fall 2002 DNP meeting: Performance of PHOBOS Vertex Finders in 200GeV PP Collisions at RHIC: Richard S Hollis, UIC Eff,Acc,Pur 2 Accuracy, Purity, Efficiency Accuracy – how close to the true vertex Purity – how many within 1 sigma (2cm) of truth. Efficiency – how often is a vertex found

12 Fall 2002 DNP meeting: Performance of PHOBOS Vertex Finders in 200GeV PP Collisions at RHIC: Richard S Hollis, UIC Eff,Acc,Pur 2 Accuracy, Purity, Efficiency Accuracy – how close to the true vertex Purity – how many within 1 sigma (2cm) of truth. Efficiency – how often is a vertex found

13 Fall 2002 DNP meeting: Performance of PHOBOS Vertex Finders in 200GeV PP Collisions at RHIC: Richard S Hollis, UIC Eff,Acc,Pur 2 Accuracy, Purity, Efficiency Accuracy – how close to the true vertex Purity – how many within 1 sigma of truth. Efficiency – how often is a vertex found

14 Black → original (unsmeared) dN/d  distribution Red → simulates the mip-based vertex finder (above) Green → simulates the track-based vertex finder (left) Fall 2002 DNP meeting: Performance of PHOBOS Vertex Finders in 200GeV PP Collisions at RHIC: Richard S Hollis, UIC Effect of Vertex Accuracy on Multiplicity Distribution Effect on Multiplicity Change in pseudorapidity vs pseudorapidity Change in pseudorapidity density shape Uncertainty in Z → shift in pseudorapidity ‘Peaks’ at η = ± 2 → more pronounced ‘Dip’ at midrapidity → deeper Monte-Carlo

15 Conclusions Fall 2002 DNP meeting: Performance of PHOBOS Vertex Finders in 200GeV PP Collisions at RHIC: Richard S Hollis, UIC Conclusion s Vertex Finding Procedure Works. Accuracy→ Strong Function of Hits → Width ≈ 2cm → Known Effect on Pseudorapidity Density


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