Charged particle multiplicity in proton-proton collisions with ALICE

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Charged particle multiplicity in proton-proton collisions with ALICE Introduction on the motivations for a pp physics programme with ALICE A short review on the detectors used to reconstruct charged particle multiplicity and to measure tracks. Typical features in pp running. The tracklet algorithm for the multiplicity reconstruction with the Silicon Pixel Detector. Some remarks on charged particles Jets and Underlying Event. Comparison with Minimum Bias. Tuning of MC models. Extrapolation from Tevatron to LHC energy. Bari, 17-19 June 2004 Workshop Focus on Multiplicity M. Monteno, ALICE Coll.

Introduction on pp physics at LHC o A complete understanding of the physics of collisions between protons at LHC, will require the study of all processes, included those with big cross sections (ranging around 100 mb(σ tot ), 60 mb(σ inel. ) and 12 mb(σ diff. ) ), which represent the majority of the events. They are generally characterized by the production of particles with low P T. o At the start- up of LHC, when the luminosity will be still rather low for ATLAS and CMS (10 33 cm 2 s 1 ), ATLAS, CMS, LHCb Therefore and ALICE a proton-proton will study minimum programme bias events hasin the new energy domain at 14 TeV. to be considered integral part of the ALICE experiment o Studies of minimum bias proton-proton events will be necessary also to establish a reference for the measurements with heavy ion collisions (strangeness enhancement, J/ψ and Υ suppression, jet-quenching), and to estimate the background to signals at high- P T (Higgs, SUSY, etc.).

pp physics with ALICE: luminosity A reasonable programme of Minimum Bias physics with the ALICE central detector requires 10 9 MB events to be taken. In a typical year of running (10 7 seconds) the detector can collect up to 5 10 9 events (readout time limited to 500 Hz). Therefore even a loose interaction trigger and a very low luminosity of 10 28 cm -2 s -1 would be sufficient If the luminosity increases, there is a progressive deterioration of the detector performances, due to the pile- up in the 100 µs of drift time of the TPC. Events start to overlap in the TPC for L > 2 10 29 cm -2 s -1 However piled-up This interactions luminosity in can the TPC be used will as keep a benchmark a regular pattern with virtual vertices because shifted at this along level the the drift tracking direction. can be considered safe At L = 3 10 30 cm -2 s -1 events start to pile-up also in the Silicon Drift Detectors. At this L about 20 events are superimposed in the TPC. However, the total number of tracks in the TPC is an order of magnitude smaller than in Pb-Pb, and therefore easily manageable

Complementarity of different experiments at LHC ATLAS & CMS optimized for high P T and high luminosities LHCb optimized for the B physics (only in the forward kinematic region). TOTEM is dedicated to the measurement of the total and elastic cross sections, and of diffractive processes (absolute calibration of the luminosity). ALICE is optimized for the study of Heavy Ion collisions, therefore it is ideal for low P T and high multiplicities (but good also for rather high P T in some cases). (Charged particles except muons)

The ALICE detector

Time Projection Chamber largest ever: 88 m 3, 570 k channels for tracking and PID via de/dx - 0.9 < η < 0.9 Central Electrode Prototype 25 µm aluminized Mylar on Al frame drift gas 90% Ne - 10%CO 2 Field Cage Inner Vessel ~ 3 m diameter

The Inner Tracking System SSD SDD SPD L out =97.6 cm R out =43.6 cm 6 Layers, three technologies (keep occupancy ~constant ~2% for max mult) Silicon Pixels (0.2 m 2, 9.8 Mchannels) Silicon Drift (1.3 m 2, 133 kchannels) Double-sided Strip Strip (4.9 m 2, 2.6 Mchannels)

ALICE: a soft particle tracker o ALICE is sensitive down to very low P T Magnetic field (T) P T cutoff (GeV/c) Material thickness: X/X0 (%) ALICE 02.-0.5 0.1 0.25 7 ATLAS 2.0 0.5 30 CMS 4.0 0.75 20 LHCb 4Tm 0.1* 3.2 o Moreover ALICE has remarkable capabilities of particle identification

Particle Identification π, K, p identified in large acceptance (2π * 1.8 units η) via a combination of de/dx in Si and TPC and TOF from ~100 MeV to 2 (p/k) - 3.5 (K/p) GeV/c Electrons identified from 100 MeV/c to 100 GeV/c (with varying efficiency) combining Si+TPC+TOF with a dedicated TRD In small acceptance HMPID extends PID to ~5 GeV Photons measured with high resolution in PHOS, counting in PMD TPC + ITS (de/dx) π/k K/p e /π TOF e /π π/k K/p HMPID (RICH) 0 1 2 3 4 5 p (GeV/c) π/k K/p TRD e /π PHOS γ /π 0 1 10 100 p (GeV/c)

Acceptance of multiplicity measurements in ALICE In ALICE the Minimum Bias trigger is provided by a coincidence between the V0 counters, scintillator layers that cover the pseudorapidity interval 5<η<-3.2 and 1.6<η<4.8. That corresponds to a visible inelastic cross section of ~60 mb. 12 10 Multiplicity measurement Momentum & Multiplicity measurement Multiplicity measurement Arbitrary units 8 6 4 2 FMD FMD 0-6 -4-2 TPC ITS Pixel 2 4 6 The charged particle multiplicity is measured over 8.8 rapidity units, whereas the momentum is measured in the TPC and in the Inner Tracking System (ITS) over 1.8 rapidity units with optimal resolution, and up to 3 units in total. η

Forward Multiplicity Detector Detector composed by 5 rings of Silicon Strips devoted to provide(offline) the charged particle multiplicity in the range 3.4<η<-1.7 and 1.7<η<5.1 While occupancies for Pb+Pb collisions are typically in the range 1-5, occupancies for p+p collisions will be less than 0.01 per strip and per collisions. Thus analysis of multiplicities can be done cleanly

Tracking in the central barrel dn/dη max =8000 (in Pb-Pb) tracking in the central barrel is a great challenge! Requirements (TPC+ITS): Good efficiency (> 90% ) for p T > 0.2 GeV/c @ 0.4 Tesla magnetic field Momentum resolution (dp/p) ~ 1 2% at low momenta and few % at 5 GeV/s Good vertexing capabilities: V0, charm Particle identification (de/dx, kinks)

Tracking solutions Tracking finding and fitting: Kalman filtering Track seeding: outer TPC (lower track density) Tracks prolonged to ITS In ITS: Kalman + vertex constraint (σ z =100 µm) From ITS: back propagation to TRD and TOF Needs Primary vertex position measurement Remark: The size of the luminous region (vertex spread) for LHC pp beams is σ = 5.4 cm (in the approximation of Gaussian shaped bunches)

Vertex determination Z v is estimated starting from a correlation between the first 2 ITS layers (PIXEL) in a narrow azimuthal ( φ) window (here high multiplicity HELPS!) R Layer 2 Z v R 1 4 cm R 2 7 cm Layer 1 The coordinates in the bending plane are measured in a similar way. More precise results can be obtained by using the reconstructed tracks necessary for secondary vertices in p-p collisions

Vertex determination /2 Z v resolution (µm) p-p Pb-Pb σ z 5 10 µm p-p σ z 150-200 µm (better when using tracks) No dependence on B

Example of a p-p event in ALICE (PYTHIA + AliROOT)

Multiplicity reconstruction with the ITS pixels / 1 Main problems respect to Pb-Pb: lower hit density statistical fluctuations become very large; the vertex position is not always reconstructed (also, in some cases the reconstruction is poor). That affects sizeably the method that uses tracklets for the reconstruction of the multiplicity, based on the alignment of hits on the two pixel layers with the guessed vertex position.

Multiplicity reconstruction with the ITS pixels / 2 Two methods are compared: - counting of clusters on one layer - counting of tracklets With 1 or 2 layers of ITS Silicon Pixel Detectors η < 0.5 Analyzed a sample of 7900 MC events (gen. with PYTHIA 6.150, CTEQ4L as pdf) T. Virgili

Multiplicity reconstruction: efficiency η < 0.5 T. Virgili After rejection of events with vertex not reconstructed All events

Multiplicity reconstruction: relative error T. Virgili η < 1.4

Multiplicity distributions: η < 1.4 Generated (line) and reconstructed (symbols) multiplicity distributions (using tracklet method) Only events with reconstructed vertex position are considered. T. Virgili

dn/dη reconstruction (with pixel detector) Clusters Layer1 Clusters Layer2 Tracklets Cut on event multiplicity to exclude events without reconstructed vertex position T. Virgili

Conclusions on Multip. Rec. with pixels Good reconstruction of both charged multiplicity and dn/dη, for both p-p and Pb-Pb interactions; A detailed investigation of the physical and methodological effects on the reconstruction has been performd; Errors determination shows a good resolution at both low and high multiplicity.

Another issue: the correlation <p T > vs multiplicity One interesting issue is the study of charged tracks <P T > as a function of multiplicity. The increase of <P T > discovered by UA1, also observed by E735 for exclusive states is still not well understood. Correlations, attributed to the onset of gluon radiation and the formation of minijet, seem to depend on the type of particle. While DPMJET fits the pion data, it does not fit the kaon data well and completely misses for antiprotons. These studies can be an interesting subject for ALICE, with its powerful PID system. Since the bulk of the produceed particles has a p T less than 0.5 GeV/c the low-p T cutoff of ALICE is an important asset for the measurement of <p T >.

Multiplicity in Min.Bias and Underlying Event Most of the the events in a Min.Bias sample are produced by soft collisions of the beam projectiles, featuring lower multiplicity in the hadronic final state (and showing KNO-scaling of multiplicity distributions and of the correlation <p T > vs multiplicity (CDF analysis by Rimondi et al.) As energy increases, a larger fraction of p-p collisions is due to hard interactions, where the scattered energetic partons undergo a fragmentation process that produces clusters of hadrons called jets (or mini-jets, for lower energy scale of the hard process) Hard Scattering Outgoing Parton PT(hard) The underlying event consists of hard initial & final-state radiation plus the beam-beam remnants and possible multiple parton interactions. Proton Underlying Event Outgoing Parton Final-State Radiation AntiProton Underlying Event Initial-State Radiation Underlying Event is all the rest of the event other than the hard scatter

Charged jet evolution and the Underlying Event The standard jet definition used in p-p experiments rely on a calorimetric criterion. The challenge for ALICE, where no extensive hadronic calorimetry is available (at least so far), is to define and construct jets out of tracking measurements Recent progress in this respect has been reported by CDF at Tevatron. They have extensively studied the properties of jets in proton-antiproton collisions measuring only the charged particle in the jets. In Min.Bias data they observed jets with total charged particle momenta of ~2 GeV/c (with two charged particles on average), while for jets up to 50 GeV/c ~10 charged particles were observed. QCD Monte Carlo models (PYTHIA 6.2 and HERWIG) describe quite well jet observables such as the multiplicity distributions of charged particles within the leading jet, the radial distribution of charged particles and their transverse momentum. The models fail to describe correctly the next few jets at a lower p T None of the QCD models describes correctly all the properties of the UE

Underlying Event as defined by Charged particle Jets Charged Jet #1 Transverse region Direction is very sensitive to the underlying event! Transverse Toward Toward-Side Jet φ Transverse Charged Particle φ Correlations P T > 0.5 GeV/c η < 1 Charged Jet #1 Direction φ Transverse Toward Transverse φ 2π Away Region Transverse Region Leading ChgJet Toward Region Look at the charged particle density in the transverse region! Away Away Transverse Region Away-Side Jet Perpendicular to the plane of the 2-to-2 hard scattering Away Region 0-1 η +1 Look at charged particle correlations in the azimuthal angle φ relative to the leading charged particle jet. Define φ φ < 60 o as Toward, 60 o < φ φ < 120 o as Transverse, and φ φ > 120 o as Away. All three regions have the same size in η-φ space, ηx φ φ = 2x120 o = 4π/3. R.Field - CDF

Average transverse charge particle density ( η <1, P T >0.5 GeV) versus P T (leading charged jet) "Transverse" Charged Density 1.00 0.75 0.50 0.25 0.00 "Transverse" Charged Particle Density: dn/dηdφ CDF Run 1 data uncorrected theory corrected Min-Bias Mean Charge density= 0.24 PYTHIA 6.206 Set A 0 5 10 15 20 25 30 35 40 45 50 PT(charged jet#1) (GeV/c) Factor ~2 1.8 TeV η <1.0 PT>0.5 GeV/c The Underlying Event has an higher multiplicity than an average MB event. Normalized multiplicity in the Transverse region is twice that of the ordinary MB events.

P T distribution of the transverse charged particle densities The Underlying Event has a harder p T spectrum than a average MB event The harder is the hard scattering, the more energy enters into the Underlying Event outside the hard scattering Charged Density dn/dηdφdpt (1/GeV/c) 1.0E+00 1.0E-01 1.0E-02 1.0E-03 1.0E-04 1.0E-05 CDF Min-Bias CTEQ5L Charged Particle Density PYTHIA 6.206 Set A 1.8 TeV η <1 PT>0.5 GeV/c "Transverse" PT(chgjet#1) > 5 GeV/c 0 2 4 6 8 10 12 14 PT(charged) (GeV/c) CDF Run 1 data uncorrected theory corrected "Transverse" PT(chgjet#1) > 30 GeV/c

MC tuning to collider data and extrapolation to LHC Recent studies on PYTHIA tuning performed within CDF (R.Field et al, Analysis of UE event) and within ATLAS (A.Moraes et al), as reported at the last MC4LHC workshop (July 2003) These two groups have performed some cross-checks: finally on Dec.1 2003 there was an ATLAS SM Working group meeting, where A.Moraes (Sheffield Univ.) presented his final results on the tuning of PYTHIA 6.214 (actually the best on the market, to reproduce collider data from ISR to Tevatron energies). He made comparisons also with PHOJET 1.12 PYTHIA 6.214-tuned and PHOJET 1.12 generate LHC predictions with ~30% difference for Min.Bias events, and a factor ~2 for UE distributions. When extrapolating from Tevatron to LHC energy PYTHIA 6.214 predicts an increase of a factor ~2 in the UE activity, whereas PHOJET 1.12 suggests that the ratio UE/Min.Bias will remain the same.

Jet Rates in Central ALICE ( η <0.9) ALICE will reconstruct charged particles with sufficient accuracy to allow similar measurements up to charged particle momenta ~100 GeV/c Benchmark luminosity for pp runs: pp L = 10 30 cm -2 s -1 Reasonable rate up to E T ~200 GeV

Charged particle jets via leading particle in TPC 1) Find the leading particle 2) If leading particle has a p t > 4 GeV/c use it as max a seed for jet. 3) Particles with pt> 2 GeV are associated to the jet if R= ( φ 2 + η 2 ) < 0.7 4) Calculate sum of momentum vectors. 5) Mark all used particles. 6) Repeat until no more seeds are found. 2-Jet in pp

Summary and prospects Crucial importance of the pp programme for the ALICE project: first ALICE papers will come out from the measurements on pp collisions at the LHC start-up!!! Promising studies of Physics Performances in the reconstruction of multiplicity and dn/dη with ITS pixels already performed In progress a massive production of full MC events (Data Challenge 2004) to complete the study of ALICE performances on several aspects of its physics programme Exciting physics in front of us (less than 3 years before Day- 1!!)