Francesco PrinoINFN – Sezione di Torino

INFN, Commissione III, Genova, September 22nd 2009

First-day observables in p-p First-day observables in p-p and Pb-Pb with ALICEand Pb-Pb with ALICE

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9 years ago: first data at RHIC9 years ago: first data at RHICResults published in the first year after RHIC startup: Multiplicity of unidentified particles at midrapidity

PHOBOS, sent to PRL on July 19th 2000 PHENIX, sent to PRL on Dec 21th 2000

Elliptic flow of unidentified particles STAR, sent to PRL on Sept 13th 2000

Particle to anti-particle ratios STAR, sent to PRL on Apr 13th 2001 PHOBOS, sent to PRL on Apr 17th 2001 BRAHMS, sent to PRL on Apr 28th 2001

Transverse energy distributions PHENIX, sent to PRL on April 18th 2001

Pseudorapidity distributions of charged particles PHOBOS, sent to PRL on June 6th 2001 BRAHMS, sent to Phys Lett B on Aug 6th 2001

Elliptic flow of identified particles STAR, sent to PRL July 5th 2001

… then came the high pT particle suppression from PHENIX (sent to PRL on Sept 9th 2008)

First 10k-20k events, fast analysis

statistics<≈100k events,longer analysis time due to the need of PID, detector calibration, combination of different detectors

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OutlineOutlineThree examples of “first day” observables Multiplicities of unidentified particles

First-day analysis from the first 10-20 k events both in p-p and Pb-Pb

Abundances and pT spectra of identified hadrons (, K, p)

Small statistics needed both in p-p and Pb-Pb, longer analysis time

Elliptic flow First-day analysis from the first 20 k Pb-Pb events

For each observable Physics motivation (in p-p and Pb-Pb) What do we need? The tools

Interaction vertex reconstruction, centrality determination, tracking, PID ...

Analysis algorithms, corrections and systematics

Where we are? Analysis readiness

First tool: ALICE at the LHCFirst tool: ALICE at the LHC

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Second tool: the GridSecond tool: the GridProductions Several production

dedicated to p-p first physics in 2009 4 M events generated,

reconstructed and analyzed specifically for first physics

Plus 108 min. bias p-p events

142 k Pb-Pb events

Analysis Organized as analysis

tasks (wagons of a common analysis train) running on the grid on ESD/AOD

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Multiplicity of unidentified Multiplicity of unidentified particlesparticles

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Nominal LHC

energy

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Physics motivationPhysics motivationp-p @ √s=900 GeV First measurement at the LHC Comparison with existing

measurements

p-p @ √s=7-14 TeV Test (soft) particle production

models in a new energy regime In hadronic and nuclear collisions

particle production is dominated by (non-perturbative) processes with small momentum transfer. Many models, but understanding of multiplicities based on first principles is missing.

Multiplicity in Pb-Pb contains information about: Energy density of the system (via Bjorken formula) Geometry (centrality) of the collision

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Factorized dependence of dNch/dmax on centrality and s reproduced by models based on gluon density saturation at small values of Bjorken x

RHIC results and modelingRHIC results and modeling

increasing s – decreasing x

Armesto Salgado Wiedemann, PRL 94 (2005) 022002

Kharzeev, Nardi, PLB 507 (2001) 121.

3

1

0

0

][2

partch

part

NGeVsNd

dN

N

Pocket formula:

and from ep and eA data

N0 only free parameter

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Towards the LHC (I)Towards the LHC (I)

Models prior to RHIC

Extrapolation of dN/dln s

5500

Saturation modelArmesto Salgado Wiedemann, PRL 94 (2005) 022002

16502.82/

/

00

d

dN

N

ddN ch

part

ch

Central collisions

Extrapolation of dNch/dmax vs s Fit to dN/d ln s Saturation model (dN/d s with =0.288) Clearly distinguishable with the first 10k events at the LHC

11005.52/

/

00

d

dN

N

ddN ch

part

ch

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Towards the LHC (II)Towards the LHC (II)Extrapolation of limiting fragmentation behavior Persistence of extended longitudinal scaling implies that

dN/d grows at most logarithmically with s difficult to reconcile with saturation models

Log extrapolationdN/d ≈ 1100

Saturation modeldN/d ≈ 1600

Borghini Wiedemann, J. Phys G35 (2008) 023001

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ALICE: figure of meritALICE: figure of meritWide angular coverage about 9 units in pseudorapidity

Different detection techniques Tracks in central barrel (ITS+TPC) Tracklets in SPD Occupancy in FMD

Tools: trigger and tagging of Tools: trigger and tagging of diffractive events in p-pdiffractive events in p-p

Minimum Bias trigger: SPDFastOr or V0A or V0C Also ZDCs and ZEM can provide a p-p MB

trigger (ZPA or ZNA or ZPC or ZNC or ZEM) Trigger efficiency (from Pythia @ 3.5+3.5 TeV) =91% Trigger efficiency independent of multiplicity in central barrel

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ZP

ZN

M

Single Diffraction(SD) ≈10mb

-10 -5 0 5 10 η

Φ

-10 -5 0 5 10 η

Φ

-10 -5 0 5 10 η

Φ

Double Diffraction(DD) ≈7 mb

Non-diffractive inelastic (ND) ≈65 mb

From 50k PYTHIA p-p @ 7 TeV (LHC09b12)SD trigger efficiency: 52%SD trigger purity: 50%ND events in MB sample: 68%ND events tagged as SD: 5.2%

From 50k PYTHIA p-p @ 7 TeV (LHC09b12)SD trigger efficiency: 52%SD trigger purity: 50%ND events in MB sample: 68%ND events tagged as SD: 5.2%

Tagging of diffractive events: based on signal only on one

side Signal in ZNC or ZPC No signal in ZNA and ZPA and ZEM

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Tools: centrality determination in Pb-PbTools: centrality determination in Pb-PbCentrality measurement from EZDC (deposited energy in ZDC) vs. EZEM (=deposited energy in ZEM) correlation Centrality classes defined by selecting events from the correlation

corresponding to certain fractions of the inelastic cross section

EZDC vs. EZEM b Nparticipants

Glauber model

Nparticipants

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Tools: Vertex reconstruction (I)Tools: Vertex reconstruction (I)

SPD RecPoints

Good (crossing the beam pipe, small DCA) tracklets

Fake (rejected by the vertexing algo) tracklets

Primary vertex

Reconstruction from SPD tracklets Tracklets = pairs of associated reconstructed points in the two

innermost ITS layers

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Tools: Vertex reconstruction (II)Tools: Vertex reconstruction (II)Reconstruction from SPD tracklets Available before tracking, used to seed the Kalman filter OK for multiplicity analyses (high efficiency, sufficient

resolution) For 80% of triggered events reconstruction in 3D available, for 15% (low

multiplicity) of triggered events only Z coordinate

Multiplicity from trackletsMultiplicity from tracklets

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Features: Large and pT acceptance

Less stringent calibration needs Suitable for the very first data

First measurement that ALICE will be able to perform in p-p and Pb-Pb

Several corrections needed Background from secondaries Algorithm efficiency Detector efficiency+acceptance Vertexing efficiency Trigger efficiency

p-p @ 7 TeV (Pythia) - LHC09b12

Multiplicity and pMultiplicity and pTT spectra of spectra of

identified particles identified particles

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Physics motivation: spectraPhysics motivation: spectrap-p @ 900 GeV Comparison with existing measurements

p-p @ 7/10/14 TeV Test for particle production models that combine perturbative QCD

for the description of hard partonic interaction and phenomenological approaches for the soft component of the spectrum

Reference for pT spectra in Pb-Pb

Pb-Pb: slope of pT spectra in the soft-pT region (< 1 GeV/c) sensitive to temperature at thermal freeze-out and radial flow Flow = collective motion superposed on top of

the thermal motion Due to large pressures arising from compressing and

heating the nuclear matter

Test of hydrodynamics models

x

y

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Physics motivation: abundancesPhysics motivation: abundancesHadron abundances: Small s (< 5 GeV):

fireball dominated by stopped particles

High baryonic content

Importance of isospin and quarks “stopped” from colliding nuclei

Large s (> 20 GeV):Fireball dominated by

produces particles

Low baryonic content

Mass hierarchy ( N > NK > Np )

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Statistical hadronization modelsStatistical hadronization modelsFit measured particle abundances (or ratios) with hadron densites from grand canonical partition function Temperature T and chemical potential B are free parameters

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22

)1(

2

)ln(1),(

k

ii

ki

ki

i

GCi

ii T

kmKm

k

TgZT

VTn

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Towards the LHCTowards the LHCExtrapolations to LHC of T and B trend vs. √s TLHC = 161±4 MeV B

LHC=0.8 MeV

A. Andronic et al. in arXiv:0711.0974 [hep-ph]

MC simulations: p-p

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Tools: tracking - ITS+TPC+TRDTools: tracking - ITS+TPC+TRDTrack reconstruction: Start from TPC signals in the outer pads + SPD vertex -> move

inward Match TPC tracks to points in outer ITS layer -> follow the track until

the innermost ITS layer Back propagate to outer TPC radius and attach TRD points

Extrapolate to outer detectors (TOF, PHOS, HMPID, EMCAL)

Refit the track inward (TRD, TPC, ITS) and propagate to SPD vertex

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Tools: tracking - ITS standaloneTools: tracking - ITS standaloneGroup clusters in , windows on the 6 layers Starting point (seed): SPD vertex + a cluster in

one of the inner ITS layers (1, 2 or 3) Extrapolation to next layer taking into account

trajectory curvature N iterations increasing at each step the ,

window sizeTrack fitted with Kalman filterGoals: Recover tracks missed by the TPC Extend low-pT reach w.r.t. TPC+ITS tracks

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Tools: PIDTools: PIDHadron identification in ALICE barrel based on: Momentum from track parameters Velocity related information (dE/dx, time of flight, Čerenkov

light...) specific for each detector

Different systems are efficient in different momentum ranges and for different particles

EMCAL +

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Particle identification with TOFParticle identification with TOF

K p

i

i

specieofparticles generated

identifiedcorrectlyspecieofparticlesEff

i

i

specieas identifiedparticles

specieas identifiedwrongly particlesCont

Features: Large acceptance (surface = 140 m2) High efficiency (>95%) Excellent time resolution (<100 ps)

Nominal resolution including all possible contributions = 80 ps

High granularity (105 channels)

5 modules in z

18 modules in

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Hadron spectra with PID in TOFHadron spectra with PID in TOF

Efficiency x acceptance for , K , p including: Tracking (ITS+TPC+TRD)

efficiency Track-TOF matching efficiency

≈80% for with 1.75<pT<2 GeV/c (including dead regions of TOF)

Identification efficiency

Spectra from few 106 p-p MB events (first day of data taking) Good accuracy up to pT

2.5 GeV/c For pT > 2.5 GeV/c

correction for contamination in PID needed

Elliptic flowElliptic flow

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Anisotropic transverse flowAnisotropic transverse flowIn heavy ion collisions with b≠0 the impact parameter selects a preferred direction in the transverse plane The fireball shows an initial geometrical anisotropy with respect to

the reaction plane Re-scatterings among produced particles convert this initial

geometrical anisotropy into an observable momentum anisotropy

Anisotropic transverse flow is a collective motion giving rise to a correlation between the azimuth [=tan-1 (py/px)] of the produced particles and the impact parameter (reaction plane) The initial particle momentum

distribution is isotropic Pressure gradients in the

transverse plane are anisotropic (= dependent)

Larger pressure gradient in the x,z plane (along impact parameter) that along y

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x

yz

Reaction plane

Elliptic flow = 2nd harmonic in Fourier expansion of particle distributions

At time = 0: Geometrical anisotropy Isotropic distribution of momentaInteraction among constituents Transform initial spatial anisotropy into a momentum anisotropy Hydrodynamics to describe the system evolution from equilibration

time until thermal freeze-outThe mechanism is self quenching The driving force dominate at early times

Elliptic flow Elliptic flow

RPv 2cos2

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Towards the LHC (I)Towards the LHC (I)Ideal hydro reproduces central collisions at RHIC Fluid created in Au-Au at RHIC has exceptionally low viscosity But also hints for incomplete equilibration / non zero viscosity

E.g. no hint for saturation in v2 vs. dN/dy

0.3

40 45 50

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Towards the LHC (II)Towards the LHC (II)Extended longitudinal scaling of v2 vs Naturally accounted in a low-density limit scenario (with

v2dN/d) Extrapolations of ideal hydrodynamics from RHIC to LHC

predict values not exceeding v2=0.06 at =0

The first 20,000 Pb-Pb events at LHC will bring new pieces of evidence to understand the picture

Tools: estimate the reaction planeTools: estimate the reaction planeReaction plane estimated from the (second harmonic) anisotropy of reconstructed tracks in ITS+TPC+TRD Event plane = estimator of the unknown reaction plane

Event plane resolution depends on v2 of produced particles Event multiplicity

Correct v2 for event plane resolution:

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ii

ii

w

w

2cos

2sintan

2

1 12

RP

v

2

22 2cos

2cos

GEANT-based simulation

Centroid resolution vs Neutron Multiplicity <cos(φZN-

φRP)> vs centrality

Tools: reaction plane from ZDCTools: reaction plane from ZDCReaction plane estimated by measuring the bounce-off of the spectator neutrons in ZDC Independent estimate, reduced non-flow correlations Allow to study v1 and the sign of v2

Resolution on ZDC event plane depends on: v1 of spectator neutrons Neutron multiplicity (on a lesser extent) 33

V1=20%

Elliptic flow: analysis methodsElliptic flow: analysis methodsComparison between three different analysis methods implemented in ALICE analysis framework and applied to 28000 Pb-Pb like events (GeVSim) Methods based on multiparticle correlation (LYZ, v2{4}) less

biased by non-flow correlations (jets, particle decays)

If non flow correlations are not included in simulations all methods correctly estimate flow

In presence of two-particle non-flow, method based on two-particle correlations (v2{2}) give biased results

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ConclusionsConclusionsSuccessful commissioning of detectors involved in “first day” observables ITS, TPC and TOF took cosmics since August 17th till September

13th. Data being analyzed for calibration and alignment. More cosmics in the next weeks.

Analysis tools ready for analysis of “first day” observables Analysis code ready and tuned on the Monte Carlo samples

produced on the Grid Acceptance/efficiency corrections extracted from the Monte

Carlo samples produced on the Grid Study of systematics on-going and in good shape

Everything ready for first p-p collisions at LHC

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Thanks to …Thanks to …

Nora De Marco, Grazia Luparello, Chiara Oppedisano, Francesco Noferini, Mariella Nicassio, Luciano Ramello For providing me a significant fraction of the material shown in

this presentation

Paolo Giubellino, Massimo Masera and Luciano Ramello For suggetions/discussions/criticism on the topics and the

analyses to be presented