Multiplicity as a measure of Centrality in

1. Multiplicity as a measure of Centrality in Richard S Hollis University of Illinois at Chicago

2. Richard Hollis, UIC Focus on Multiplicity, Bari 2004 Collaboration (May 2004) Birger Back,Mark Baker, Maarten Ballintijn, Donald Barton, Russell Betts, Abigail Bickley, Richard Bindel, Wit Busza (Spokesperson), Alan Carroll, Zhengwei Chai, Patrick Decowski, Edmundo García, Tomasz Gburek, Nigel George, Kristjan Gulbrandsen, Clive Halliwell, Joshua Hamblen, Adam Harrington, Michael Hauer, Conor Henderson, David Hofman, Richard Hollis, Roman Hołyński, Burt Holzman, Aneta Iordanova, Jay Kane, Nazim Khan, Piotr Kulinich, Chia Ming Kuo, Willis Lin, Steven Manly, Alice Mignerey, Gerrit van Nieuwenhuizen, Rachid Nouicer, Andrzej Olszewski, Robert Pak, Inkyu Park, Heinz Pernegger, Corey Reed, Michael Ricci, Christof Roland, Gunther Roland, Joe Sagerer, Helen Seals, Iouri Sedykh, Wojtek Skulski, Chadd Smith, Maciej Stankiewicz, Peter Steinberg, George Stephans, Andrei Sukhanov, Marguerite Belt Tonjes, Adam Trzupek, Carla Vale, Siarhei Vaurynovich, Robin Verdier, Gábor Veres, Edward Wenger, Frank Wolfs, Barbara Wosiek, Krzysztof Woźniak, Alan Wuosmaa, Bolek Wysłouch ARGONNE NATIONAL LABORATORY BROOKHAVEN NATIONAL LABORATORY INSTITUTE OF NUCLEAR PHYSICS, KRAKOW MASSACHUSETTS INSTITUTE OF TECHNOLOGY NATIONAL CENTRAL UNIVERSITY, TAIWAN UNIVERSITY OF ILLINOIS AT CHICAGO UNIVERSITY OF MARYLAND UNIVERSITY OF ROCHESTER

3. Richard Hollis, UIC Focus on Multiplicity, Bari 2004 Outline • Considerations – Centrality in 200GeV Au+Au • Event Selection • Detector Efficiency • Choose Data η region to measure centrality • Event Generator Simulations – Npart • Other Collision Systems • d+Au 200 GeV • Au+Au 19.6 GeV

4. Richard Hollis, UIC Focus on Multiplicity, Bari 2004 The Detector ZDC Ring Counters Paddle Counters and ZDCs ZDC (hidden) Octagon and Spectrometer

5. Richard Hollis, UIC Focus on Multiplicity, Bari 2004 Considerations: Event Selection 200GeV Au+Au Collisions • A clean event selection ensures consistency of good events • Only use data within ±4ns (~±60cm) from Paddles • Red points → outside this cut the acceptance changes • Further restrictions requires ZDC signal Beam-gas collision peaks Schematic Diagram of Paddles

6. Increase >4ns due to change in acceptance Flat over the region used Paddle time difference widens due to low multiplicity → smearing effects Richard Hollis, UIC Focus on Multiplicity, Bari 2004 Considerations: Event Selection • A clean event selection ensure consistency of good events • Only use data within ±4ns (~±60cm) from Paddles • Red points → outside this cut the acceptance changes • Only use Silicon vertex range of ±10cm for physics measurements (blue)

7. Richard Hollis, UIC Focus on Multiplicity, Bari 2004 Considerations: Detector Efficiency • Trigger system incurs small bias for peripheral events • Have to account for the missing cross-section • Have two main trigger types (in Au+Au) • One or more hit in each paddle array • Estimated to have 97% efficiency • More than 2 hits in each paddle array • Estimated to have 88% efficiency

8. Richard Hollis, UIC Focus on Multiplicity, Bari 2004 Considerations: Detector Efficiency Number of hit paddle segments • Trigger system incurs small bias for peripheral events • Have to account for the missing cross-section • Estimate the efficiency • Using Data and MC simulations • Unbiased Hijing sample • 97% efficient trigger (red) Data • 88% efficient trigger (blue) Data Similar plateau observed in data

9. Richard Hollis, UIC Focus on Multiplicity, Bari 2004 Considerations: Data Centrality Region 200 GeV Au+Au data for 0-25% cross-section • Paddles are located in 3.2 < |η| < 4.5 • Monotonic anti-correlation with neutral spectators • Region appears to be usable

10. Richard Hollis, UIC Focus on Multiplicity, Bari 2004 Centrality Determination • Summary of Information • Have clean event selection • Estimated the trigger efficiency • Centrality determined from Paddles (3.2<|η|<4.5) • Observed spectators are monotonic with that signal • Need one more piece • Does MC predict monotonicity between Npart and Paddle signal?

11. Richard Hollis, UIC Focus on Multiplicity, Bari 2004 Centrality Determination • Nicely correlated • Now have all the information needed • Hard work is done • Divide the data into cross-section bins • Use MC to estimate <Npart> for each bin Only use data where (Si) vertexing finding efficiency is 100% (top 50% of cross-section)

12. Centrality Complete • 200 GeV Au+Au is well established • Now investigate the centrality of d+Au collisions at 200 GeV

13. Richard Hollis, UIC Focus on Multiplicity, Bari 2004 Centrality at 200GeV d+Au Shapes agree reasonably in High multiplicity region • Same Considerations • Details of analysis is different • Event Selection • Clean-up by requiring a valid silicon vertex • Very Low multiplicity Events • Paddle timing smeared • Not always neutron in both ZDCs • Efficiency • Used a shape matching algorithm between Data and Simulations (HIJING or AMPT) • Efficiency includes Trigger and Vertex finding efficiency • Estimated to be 82.5% Hijing + GEANT Data Data inefficient for peripheral events EOct is the summed charge deposited in the Octagon detector

14. Richard Hollis, UIC Focus on Multiplicity, Bari 2004 d+Au Data Centrality Regions • Unique PHOBOS η coverage • Many regions to pick from • Not just the ‘paddles’ • All regions were used • same basic algorithm • Sum the charge deposited in these regions (from Silicon) EOct ETot EAuHem EdHem ERing

15. All Centrality methods agree when reconstructing the min-bias distribution Richard Hollis, UIC Focus on Multiplicity, Bari 2004 d+Au Data Centrality Regions • Unique PHOBOS η coverage • Many regions to pick from • Not just the ‘paddles’ • All regions were used • same basic algorithm • Sum the charge deposited in these regions (from Silicon)

16. Richard Hollis, UIC Focus on Multiplicity, Bari 2004 d+Au Data Centrality Biases • Two types of potential biases • Auto-correlation biases • Measurement of centrality interferes with physics measurement • Causes a change in shape of dN/dη distribution • Trigger-Biases • Due to inefficiency for peripheral collisions • Changes <Npart> of a bin

17. Richard Hollis, UIC Focus on Multiplicity, Bari 2004 Auto-Correlation Biases AMPT+GEANT Simulations • Mid-rapidity Centrality, EOct • Shown for 3 cross-section bins • Form a Truth distribution • Divide the Npart distribution into bins with the same <Npart> as EOct • Repeat analysis • Can see a clear bias developing due to the centrality determination EOct Npart

18. Richard Hollis, UIC Focus on Multiplicity, Bari 2004 Auto-Correlation Biases AMPT+GEANT Simulations • Mid-rapidity Centrality, ERing • Shown for 3 cross-section bins • Bias is smaller Npart ERing

19. Richard Hollis, UIC Focus on Multiplicity, Bari 2004 Centrality at 200GeV d+Au • With these two things • can make the centrality dependence • Can now integrate these distributions for the total charge • Scale by Nchpp • Results consistent with expectations from low energy data

20. Richard Hollis, UIC Focus on Multiplicity, Bari 2004 Centrality at 200GeV d+Au • With these two things • can make the centrality dependence • Can now integrate these distributions for the total charge • Scale by Nchpp • Results consistent with expectations from low energy data

21. d+Au Centrality Complete • Final Example: Au+Au collisions at 19.6 GeV

22. Richard Hollis, UIC Focus on Multiplicity, Bari 2004 Centrality at 19.6GeV Au+Au • Hit number of Paddles efficiency method • Works at 62.4 GeV • Does not work at 19.6 GeV • Too low multiplicity • No plateau observed • Multiplicity in paddle’s region too low See the same plateau

23. Richard Hollis, UIC Focus on Multiplicity, Bari 2004 Centrality at 19.6GeV Au+Au • Use summed charge in octagon • EOct as in d+Au • Could this introduce a bias? • Make new Centrality measures to check this

24. Richard Hollis, UIC Focus on Multiplicity, Bari 2004 Centrality at 200GeV Au+Au • Measure same results for • midrapidity methods (a) • away from midrapidity (b) • For midrapidity yields for the top 50% of the cross-section • Aneta Iordanova will talk about this measurement in the next talk 200GeV from (a) 200GeV from (b)

25. Richard Hollis, UIC Focus on Multiplicity, Bari 2004 Conclusions • We have established methods for centrality determination • From 19.6 to 200 GeV Au+Au • From d+Au to Au+Au collision systems • Have an array of complementary techniques for centrality cross-checks • Techniques used introduce little or no bias onto the physics measurements • Any biases introduced can be estimated and corrected for from MC studies