# Presentation: 665941

## 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

## Relativistic Heavy Ion Collider

**12 June**: 1st Collisions @ s = 56 AGeV
**24 June**: 1st Collisions @ s = 130 AGeV

## 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**

## PHOBOS Apparatus

## 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

## 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 N

- ZDC P

- Au

- Au

- PP

- PN

## First Collisions at PHOBOS

- 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

## Examples of events

- Hits in VTX

- Hits in SPEC

- Tracks in SPEC

- 130 AGeV

- 56 AGeV

- 130 AGeV

## Event selection

**Paddle Timing**
- t < 8 ns selects events with vertex |z|<120 cm
- Still contains background events
**ZDC Timing**
- t < 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)**

## 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**

## 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/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
- < 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

## 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

## 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

- 

## Understanding Paddle Counters

- DATA

- MC

- 56 AGeV

- 130 AGeV

- PN12

- PP12

## ZDC Sum vs. Paddle Sum

**ZDC Sum vs. Paddle Sum**

- 130 AGeV

## Estimating Npart

- 6% most central events based on paddles gives

- Npart

- Events/bin

## 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

## Measuring Vertex

**Measuring Vertex**

- 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

## 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

## Tracklets

**Tracklets**

- 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<.015

## 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

- SPEC

- VTX

- tracklets

- tracklets

## 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

## Results

|  | 56 AGeV | 130 AGeV |
| --- | --- | --- |
| dN/d | <1 | 408±12(stat)     ±30(syst) | 555±12(stat)     ±35(syst) |
| dN/d | <1
per participant pair | 2.47±0.10±0.25 | 3.24±0.10±0.25 |
| Ratio
(density per participant pair) | 1.31±0.04±0.05 |  |

## Systematic Uncertainties

- dN/d
- Background subtraction on tracklets < ±5%
- Uncertainty on  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/d 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/d / Npart )130 / ( dN/d / Npart )56
- Many uncertainties cancel in the ratio

## Comparisons with pp