Reconstruction tools for the study of short-lived resonances in ALICE pp collisions at the LHC startup 1.The ALICE 2.Short-lived resonances in ALICE 3.pp collisions: preparing the tools for LHC startup 4.Results from local and distributed computing analysis Outline F.Riggi Dept. of Physics and Astronomy and INFN, Catania ACAT 2007, Amsterdam, April, 2007

Z The Large Hadron Collider CERN 4 major experiments waiting for the first beam… ALICE Point2

Point 2

ALICE: A Large Ion Collider Experiment ITS TPC TOF

P T > 1 GeV/c ALICE will track and identify products from pp and nucleus- nucleus collisions in a large multiplicity environment Main tracking detectors: ITS and TPC

The silicon Inner Tracking System (ITS) Drift (SDD) 133,120 channels Strips (SSD) 2,608,128 channels Pixel (SPD) 9,830,400 channels

Time Projection Chamber (TPC) Channels GasNe/CO 2 90/10 or + 5%N 2 Volume88 m 3 Drift length2.5 m Drift field400 V/cm Drift velocity 2.84 cm/ms Max drift time 88 ms Arrival of the TPC in the ALICE cavern

Possible ALICE physics at the LHC startup TeV?) Physics aspects Compare pp and pp data at 900 GeV Compare pp and pp data at 900 GeV Improve the precision in comparison with existing pp data at 900 GeV Improve the precision in comparison with existing pp data at 900 GeV Prepare the detector (calibration, alignment) Prepare the detector (calibration, alignment) Provide a reference for data at different cm energies (2.4 TeV, 5.5 TeV?, 14 TeV). Provide a reference for data at different cm energies (2.4 TeV, 5.5 TeV?, 14 TeV). Use first pp events to study global event properties: Use first pp events to study global event properties: Charged Multiplicity, Pseudorapidity distributions, p spectra Charged Multiplicity, Pseudorapidity distributions, p T spectra First strange particle studies First strange particle studies Short-lived resonances ? Short-lived resonances ?

Resonance Life-time [fm/c]  1.3  f 0 (980) 2.6 K*(892) 4.0   (1520) 13 ω(783) 23  (1020) 45 Short-lived resonances have typical lifetimes comparable to that of the hot and dense matter created in AA collisions Time chemical freeze-out            signal lost kinetic freeze-out signal measured late decay signal measured rescattering regeneration  e+e+ e-e- signal measured early decay  ++ -- signal measured late decay    e+e+ e-e- signal measured late decay Observation of short-lived resonances is affected by two competing effects: rescattering vs regeneration

Resonance K*(892) Φ (1020)  *(1520) Δ(1232) Decay channel (B.R.) K  (~100%) K + K - (49%) N K (45%) Nπ (100%) Width [MeV/c 2 ] Life time [fm/c] Study of short-life resonances in ALICE Main observables: ● Extraction of the signal/yields ● Mass and widths of resonances ● Transverse momentum and transverse mass spectra ● Particle ratios ● Elliptic flow ● Nuclear modification factors: RCP and RAA

pp GeV TeV ● LHC running scenario at startup: 1-2 days for physics GeV ? ● Expected no. of events: 0 to 10 6 ● To what extent is the study of short-lived resonances feasible? Results from: ● Local analysis via LSF GeV): 2 x 10 5 events ● Distributed GRID analysis TeV): 1.5 x 10 6 events Tuning of reconstruction tools: ● Study of the combinatorial background ● Perfect and realistic Particle IDentification Detailed examples for K*(892), other resonances treated in the same way

Reconstruction of short-lived resonances requires optimal performance on: primary and secondary vertex reconstruction Efficiency An example of D 0 -> K - π + decay in a large multiplicity environment σ ~ 40 μm for pp σ ~ 5 μm for PbPb 3D resolution

Kalman filter strategy allows a good tracking performance down to very low momenta Methods based on neural networks also implemented for stand-alone tracking in the ITS: 10% improvement ITS + TPC

p T resolution The inclusion of ITS, TPC and TRD results in p T resolution as good as 3 % up to 100 GeV/c

Information on impact parameter mainly provided by the ITS Transverse impact parameter resolution

with ITS and TPC at low momenta… and TOF at high momenta… w(i | s)= r(s | i) C i Σ k r(s | k) C k Bayesian PID for each detector

Inside same event, correlations between K + and π - candidates K - and π + candidates Evaluate invariant mass spectrum Combinatorial background Signal extraction (unlike-sign) Mixed-event technique Like-sign technique Example: K*(892)  Kπ (~100%)

The AliROOT framework STEER Base classes, overall control AliReconstruction  ESD Reconstruction Event Summary Data Particle generation DPMJET HIJING HBTP PYTHIAPDF ISAJET Transport of particles GEANT3 GEANT4FLUKA Analysis HBTJETPWG0-4 Detectors ZDCPHOS EMCALHMPID TOF TRD TPC ITS T0V0PMDMUON Response Geometry Calibration Alignment

Selection of primary and identified tracks Size reduction by 200 AOD: Analysis Object Data Analysis Cuts,histograms,… From generation and reconstruction ESD: Event Summary Data Kinematics … Local analysis of 200,000 pp min bias events via LSF (Load Sharing Facility, A general purpose distributed computing system) For such application: ● Cluster of 60 multiprocessors CPU (up to 30 simultaneous jobs running) ● Generation and full reconstruction of events (1 job= 100 events) ● CPU time/event: GeV ( 230 TeV) ● Total CPU time: approx. 200 days (about 10 effective days)

No event selection Only events with Δm<5 and Δz v < 3 cm mixed Effect of event selection (multiplicity and vertex location) on mixing procedure Selection in multiplicity is more effective than in primary vertex location (True Background) (Mixed events background) True background = (Signal) – (True pairs)

Like-sign technique Signal Background

Effect of particle identification on the results PID information from TPC and TOF used in the present analysis, with Bayesian procedure Different scenarios ● Perfect PID ● Realistic PID with no threshold on max_probability ● Realistic PID with improvement both in K and pion identification ● Realistic PID with improvement in K identification /no PID on pions K*(892) invariant mass with perfect PID

Improving kaon identification in the Bayesian algorithm by a threshold on max.probability From max_prob > 0 to max_prob > 0.7

No thresh on maxprob Maxprob > 0.7 (K) No PID (π) Maxprob > 0.7 (K) Maxprob > 0.7 (π) Perfect PID Realistic PID Summary of PID influence on K*(892) reconstruction True Found S/B = 0.11 S/√B = S/B = S/√B = 20.01

Φ(1020) Λ*(1520) Similar analyses also done on other short-lived resonances Yields and particle ratios uncertainties expected at 900 GeV with 200K pp events Particle ratios Statistical K*/K % Λ*/Λ 9 % Φ/K* 8 % Φ/Λ* 12 % K*/Λ* 9 %

REAL DATA (MB)MonteCarlo (MB) RawESDAODEv. CatalogRawESD pp / event pp / year (x 10 9 ) HI / event HI / year (x 10 9 ) More detailed analyses require a large number of events Distributed analysis of 1.5 Mevents pp min bias 14 TeV from PDC06 on the GRID via AliEn (ALICE Grid Environment)

Submitting and monitoring jobs on the GRID via AliEn

Distributed computing on the GRID: ~1.5 Mevents TeV) processed on the grid via AliEn middleware Monitoring the jobs on the GRID in ALICE

Typical results at 14 TeV from distributed analysis on the GRID

p T -analysis with realistic PID p T = p T = p T =

Correction matrix p T =0-4 GeV/c (8 bins) Y = -1.5 – 1.5 (4 bins)

Summary ● Study of short-lived resonances in pp and PbPb LHC energies could be studied in ALICE from the very beginning ● With a small sample of events [O(10 5 )] and realistic PID: ● Extraction of yields at least for K*(892), Φ(1020), Λ*(1520) ● Rough p T - distribution for K*(892) up to GeV/c ● Particle ratios Φ/K*, Λ*/K*, Φ/Λ* measurable ● Analysis of O(10 6 ) pp events at 14 TeV fully reconstructed on the GRID ● Resonance yields with large statistics ● p T -analysis ● Correction matrix (y,p T ) ● Extension to other resonances in progress