# Presentation: 685976

## Event by Event Fluctuations Studies for the ALICE Experiment 

- Chiara Zampolli
- ALICE-TOF
- Centro E. Fermi (Roma), INFN (Bologna)

## Outline

- Introduction
- Event-by-Event Fluctuations
- ALICE
- Monte Carlo Event Sample
- ALICE PID Performance
- Identified Particle Spectra
- Particle Ratios
- Summary and Conclusions

## The T-μ QCD Phase Diagram

- Continuous transition for small chemical potential at:
- 	Tc~ 170 MeV
- c ~ 0.7 GeV/fm3
- Lattice calculations: crossover at μb~ 0
- Many parameters involved

**The T-****μ**** QCD Phase Diagram**

- QCD prediction: @ very high temperatures and energy densities,
- a Phase Transition from Hadronic Matter to the QGP occurs.

*What kind of phase transition? But really a phase transition or a crossover?*

***LHC***

## QGP Signatures

- The nature and the time evolution of the hot and dense system created in a heavy-ion collision are expected to show the characteristic behaviour of a ***QGP phase transition***, which could dramatically change from one event to the other.
- Apart from the very well know probes (inclusive probes, probes related to deconfinement...), an analysis on an ***Event by Event*** basis offers the opportunity to study the QCD phase transition and to get insights into the QGP. For example:

- Thermodynamic quantities (T,S)
- Energy density fluctuations
- Jets and minijets
- DCC, Balance function...

- Properties of the system
- Order of phase transition
- Physics of the QGP
- Chiral phase transition, hadronization time...

*relying on the very high particle multiplicities produced per event (SPS, RHIC, LHC)*

## Event by Event Fluctuations

- FLUCTUATIONS

**Statistical**
- Finite number of particles produced
- Experimental acceptance and resolution

**Dynamical**
- Dynamics of the collision
- Evolution of the system

**Sources of event-by-event fluctuations:**
-  **geometrical**
-  **energy, momentum, charge conservation**
** ****anisotropic flow**
** ****Bose-Einstein correlations**
** ****resonance decays**
** ****jets and mini-jets**
** ****temperature fluctuations**

## E-by-E Fluctuations: Observables

- Mean Transverse Momentum
- Mean Energy
- Charge Fluctuations
- Particle Ratios
- Identified Particle Spectra

***Particle IDentification ***plays a crucial role!

## Some Experimental Results

- K/ratio

- STAR

- Mean pT

***What will ALICE sensitivity be?***

## A Large Hadron Collider Experiment - ALICE

- ITS
- Low *p*T tracking
- Vertexing

- TPC
- Tracking, dE/dx

- TRD
- Electron ID

- TOF
- PID

- HMPID
- PID (RICH) @ high *p*T

- PHOS
- γ, π0

- PMD
- γ multiplicity

-       = 5.5 TeV/NN
- Designed for
- dNch/dy|max = 8000
- (optimized for 4000)
- Lmax = 11027 cm-2s-1

## ALICE PID

- separation @ 3

- separation @ 2

- (dE/dx)

## ALICE PID Approach

*Weaker momentum dependence of the efficiency (contamination) *
*Efficiency (contamination) higher (lower) or at least equal than with stand-alone detectors *

- A common *BAYESIAN* approach is adopted by every ALICE detector performing PID;
- The probability w(i|s) to be a particle of type *i* (i = e, , , ...) if a signal s (dE/dx, TOF,...) is detected, is:

- r(s|i)
- conditional pdf to get a PID signal *s* in a detector, if a particle of type* i* is detected

- Ci
- a priori probability to find a particle of type *i* in the detector

- Combined PID combining (multiplying) the r(s|i) from different dets

## Monte Carlo Event Sample

|  pt> 0.15 GeV/c,
-0.9 < < 0.9 |  | K | p |
| --- | --- | --- | --- |
| # generated | 6750 | 720 | 380 |

- 300 Hijing Pb-Pb events (fully simulated and reconstructed)
- Centrality 0 ÷ 10% (0 < b < 5 fm)
- Magnetic Field B = 0.5 T
-                    ~ 4500

## PID Performance - Definitions

- The PID performance is evaluated in terms of:

- N = number of reconstructed particles to which the PID procedure is applied

## Combined PID – ITS || TPC || TOF

|  |  | K | P |
| --- | --- | --- | --- |
| ID | 5200 | 360 | 260 |
| wrongly ID | 100 | 80 | 10 |

**Combined PID – ITS || TPC || TOF**

| overall efficiency |  |  |
| --- | --- | --- |
|  | K | p |
|  | 39% | 66% |

| Efficiency |  |  | contamination |  |  |
| --- | --- | --- | --- | --- | --- |
|  | K | P |  | K | p |
| 98% | 76% | 86% | 2% | 22% | 5% |

- 0.15 < pT < 4 GeV/c

## Generated vs Identified Spectra

- K

- Generated

-   Identified, wrong

- Identified, true + wrong

## Fitting of the Spectra

-  Event by event fitting procedure for pT spectra: exponential function

- ,T = temperature of the system connected to the

-  Correction of the identified spectra taking into account:
- Limited acceptance  and reconstruction efficiency of the detectors: εacc
- PID efficiency: εPID
- PID contamination: CPID

*kinetical freeze-out temperature*

## Results – Single Event, pT spectra

| Temperature (MeV) |  |  |
| --- | --- | --- |
|  | K | p |
| 184 ± 2 | 212 ± 9  | 292 ± 13 |

*Fit range: 0.25 < *pT* < 2 *GeV/*c*

*i.e. corrected!*

## Results – T Distributions

- T/T ~ 2%

- T/T ~ 7%

- T/T ~ 7%

## Systematic Uncertainties on the Corrections

- Possible sources of systematic errors:
- Knowledge of the acceptance and reconstruction efficiencies, secondaries’ flow... (    )
- Recent results (e.g. PHENIX) suggest a level of 10% of systematic uncertainties.
- 100 virtual experiments randomly changing the efficiency (contamination) correction factors by 10%.

- (    )p from Λ and Σ decays under study

- A small relative increase of few %s in the width of the temperature distributions has been observed in both cases (efficiency/ contamination).
- The mean values of the temperatures can vary by few %s.

## Particle Ratios

- K/

- R  = 0.106
- σR = 0.007

- p/

- R  = 0.060
- σR = 0.005

- σR/R ~ few %s

## Summary & Conclusions

- Event by event fluctuations studies are an important tool to explore the QCD phase diagram, searching for the QGP, and the QCD critical point.
- Several recent experimental studies (at the SPS -NA49- and RHIC -STAR, PHENIX...- have focused on the studies of fluctuations in relativistic heavy ion collisions (high temperature and energy densities).
- Thanks to its **very high particle yield** per event, and to the excellent **PID capabilities****,** ALICE will be able to study fluctuations measuring the identified particle spectra (, K, p) and the particle ratios (K/, p/) on an Event-by-Event basis.

## Summary and Conclusions – cont’d

- Temperature fluctuations: statistical fluctuations of the order of few percents for  K and p.
- Particle ratios: statistical fluctuations of the order of few percents for both K/ and p/

- Any other contribution from dynamical fluctuations due to new physics will result in an increase of the observed values

- The results presented herein strongly depend on the assumed dNch/dy.
- HIJING simulation: dNch/dy ~ 4500;
- RHIC results suggest a reduction by a factor ~ 2÷3 in the data.

- E-by-E studies still feasible

## Back-Ups

## 3-Flavour QCD Phase Diagram 

- QCD prediction: @ extremely high temperatures and energy densities,
- a Phase Transition from Hadronic Matter to the QGP occurs.

*What kind of phase transition? But really a phase transition or a crossover?*

- Many crucial params!!
- number of light/massless quarks,
- net baryon number density,
- ...

## Pressure and Energy Density vs T(/Tc)

- Lattice QCD for EOS, pressure and energy density calculation

- Tc = (173 ± 15) MeV
- c ~ 0.7 GeV/fm3

- p* rescaled* by the corresponding ideal gas value!

- F. Karsh ‘01

- F. Karsh, E. Laermann ‘05

## Quantum-Chromo-Dynamics: QCD

- QCD predictions under extreme temperature and energy density conditions:
- Insights in the phase transition from ordinary hadronic matter to a quark-gluon plasma @ high T and 
- Confinement / deconfinement
- Chiral symmetry breaking / restoration
- Astrophysics highlights:
- phase transition ~ 10-5 s after the Big Bang
- neutron stars, supernovae

**QCD**: theory of the colour interactions between the fundamental constituents of matter.

## QGP Signatures and PID

**QGP Signatures and PID**

- Particle spectra

- Particle ratios

## QGP Signatures and PID – cont’d

- Strangeness enhancement and resonance modification

- Open charm and beauty

## ALICE Tracking

- Track Reconstruction has to be performed in a high flux environment
- Reconstruction at low pT very delicate (multiple scattering and energy loss)

- Tracking based on a  *KALMAN FILTER *technique

-  Simultaneous reconstruction and fitting
-  Rejection of incorrect space points “*on the fly*”
-  Simpler handling of multiple scattering and energy loss effects
-  Easy extrapolation from one detector to the other

## ALICE Tracking Strategy

*dN/dy =8000 (slice: 2**o** in ****** ***

**HMPID**

**TOF**

**TRD**

**TPC**

**ITS**

-  Final *refit inwards*

-  *Primary Vertex* Finding in ITS

-  *Extrapolation* and connection
-   with outer PID detectors

- After cluster finding, start iterative process through the central tracking detectors, ITS+TPC+TRD:

-  *Propagation to the vertex*,
-   tracking in ITS

-  *Back-propagation* in TPC
-   and in the TRD

-  *Track seeding* in outer TPC

## ALICE Tracking Performance

- Tracking Efficiency / Fraction of Fake Tracks for dN/dy = 2000, 4000, 6000, 8000

- For dN/dy = 2000 ÷ 4000,
- efficiency **> 90%,**
- fake track probability     **< 5%**!!!

*Full chain, ITS + TPC + TRD*

## PT Resolution

## ALICE PID Performance

- efficiency

- contamination

- p dependence of:

**ALICE PID Performance**

- Central Pb + Pb HIJING events – kaon case

*Combining the PID information from different detectors allows a weaker momentum dependence of the efficiency (contamination) which stays higher (lower) or at least equal than with stand-alone detectors!!!  *

## ITS PID

- ITS limited separation power

- narrower momentum ranges for K and p

- PID Overall Efficiency

## TPC PID

- Slightly wider pT range than for the ITS stand-alone PID
- Still high contamination @ intermediate-high pT for K and p

- PID Overall Efficiency

## ITS and TPC Combined PID

- Slightly wider pT thanks to TPC
- Still high contamination for K and p

- PID Overall Efficiency

- K

## TOF PID

- pT > 0.3 GeV/c
- efficiency momentum dependence (K, p)
- lower overall efficiency because of absorption in the material in front

-  decrease at low pT due to interactions and decays

-  decrease at high pT due to low separation power and mis-ID (K)

- PID Overall Efficiency

## Combinatorial PID

- Combinatorial algorithm on a set of N=6 tracks, based on finding the best combination Cbest(m1,..mN) on 3N mass (,K,p) hypotesis, minimising:

- t0i(mi)  =  texpi(mi) - tTOFi

- i=****texpi(mi))+ tiTOF

- t0 offset for track i
- Error on ith t0 offset ~90 ps
- Average t0  for mass
- combination C(m1..mN)

- texp = calculated time of flight from
- 	p, L, with mass hypothesis m

- tTOF = measured time of flight

- ,

- Set mass combination: Cbest corresponding to the minimum 2** **

## Combinatorial PID performance

- N.B.: Sets with C.L. of 2 best >1% discarded (since they mainly consist of mis-ID tracks).

**Eff.** =

**Cont.** = 1 – Eff.

- Scenario b)

## Results – T Distributions

- T/T ~ 2%

- T/T ~ 7%

- T/T ~ 7%

## Efficiency Correction Variation

- No significant change!

## Contamination Correction Variation

- No significant change!

## System Evolution

- Tc – Critical temperature for transition to QGP
- Tch– Chemical freeze-out (Tch  Tc) : inelastic scattering stops
- Tfo – Kinetic freeze-out     (Tfo  Tch): elastic scattering stops

-  Hadronic ratios: Tch.
-  Resonance production:     	Tch-Tfo.
-  pT spectra: Tfo.

- QGP signals are searched
- for in the bulk properties
- of the system: