1. Study of influence of particle identification and resonances excitation on correlation functions mesured by ALICE setup. 1. Influence of particle identification efficiency in ALICE detectors: -TPC -ITS -TOF on correlation functions. 2. Resonances excitation and correlation function.

2. The simulation procedure consists of the following steps: 1. Generation of events without correlations. Hijing: the central rapidity region, |Y|<0.9, dNch/dy~7200 200 events, 45<θ<135, -180<φ<180, magnetic fields 0.2T, 0.4T 2. Reconstruction in TPC (ITSv2). 3. Construction of correlation function for reconstructed tracks by calculating weights for all correctly identified (π+π+) combinations; for the pairs including at least one non-pion identified as pion the weight was taken equal 1. 4. Background was generated by taking particle pairs from different events. All particles identified as pions were used

3. (π+,π+) correlation function : S(Qinv) yield of particles from the same event with p1, p2 B(Qinv) uncorrelated reference generated by the event-mixing method N normalization factor, used to normalize the CF to be unity at large Qinv

4. Particle identification in TPC by dE/dx. Method of cuts for pions selections at 0.4 T. AliTPCPid class created by B.Batyunya and S.Zaporojzets was used. The cut functions are used for the PID in the good separation region. -- The probability weights by two-three gaussians (the special one for the tail approximation) are calculated in the overlapping regions. AliHBTReaderTPCpid class was introduced for reading TPC+PID information

5. e, μ, K, p identified as π contaminations = _____________________ all particles identified as π «true» π identified as π efficiency = ____________________________ all particles identified as π Contaminations and efficiency for TPC

6. Contaminations and purity TPC

8. Particle identification in ITS by dE/dx. Method of cuts for pions selections at 0.4 T. AliITSPid class created by B.Batyunya and S.Zaporojzets was used. AliHBTReaderITSpid class was introduced for reading ITS+PID information

9. Contaminations and efficiency for ITS Contaminations and purity for ITS

11. Using of the new tracking in TPC and the new AliTPCPID method providing better separation of electrons from pions + impact parameter cut which suppressed electron and muon contaminations the «efficiency» of pion identification (averaged by pt) is ~96%, resulting in a purity of ~92% for pairs. It decreased λ on ~8%. Purity in ITS is ~ 95%. It decrease λ on ~5%. PID procedures in TPC (ITS) decrease the strength of the correlations- λ-parameter leaving radii ~ unchanged.

12. TOF: The simulation procedure consists of the following steps: 1. Generation of events without correlations. Hijing for the central rapidity region, |Y|<1, dNch/dy=7200 400 events 2. Fast simulation in TPC + matching TPC-TOF with modified AliTOFReconstructioner class which write ntuple with PID+TPC+TOF+KINE information. [Addendum to the Technical Design Report of rhe time of flight System, Alice TDR 8, 24 April 2002] 3. Reading ntuple with AliHBTTOFpid class. AliHBTTOFpid class select particles with special contur cuts (reconstructed mass versus momenta). 4. Construction of correlation function for TPC-tracks by calculation weights for all correctly identified (π+π+) combinations; for the pairs including at least one non-pion identified as pion the weight was taken equal 1. TPC-double tracks efficiency is introduce as weight. 5. Background was generated by taking particle pairs from different events. All particles identified as pions are used.

13. Some features of PID TOF procedure Well matched tracks : --tracks with «true time» Nt --tracks with «wrong time» Nw Mismatched tracks : --TOF pad is’t fired, track is matched with TOF dead region N0 -tracks for which the fired pad was matched to more than one track. N2

14. Nt +Nw+N2

15. Efficiencies for different types of events in TOF versus Qinv

16. Contaminations for different types of events in TOF versus Qinv For 0.5<Pt<2.5 GeV/c

17. TOF true time+wrong time+closed tracks TOF true time + wrong time TOF with TPC reconstructed tracks Correlation functions with PID in TOF for simulated and TPC reconstructed (fast simulation) tracks. TOF true time+wrong time+closed tracks

18. The choise of cuts ( taken from TOF-Addendum ) can be improved. If «soft» cut for pion is chosen the purity for pions in TOF (0.4T) is ~ 85%. It decrease λ on ~15%. PID procedure in TOF decrease the strength of the correlations- λ- parameter. If closed tracks (N2) are taken. Contaminations for pions increase (purity decrease) on ~3% at small Qinv<0.005 GeV/c. For pions this effect is negligible.

19. Direct pions and pions from resonances excitation (Hijing) Resonances excitation (>70% of pions are from resonances) request more realistic generators. T. Humanic generator was introduced in AliRoot: AliGenTHMFiles class allows to work with files generated by T.Humanic fortran code. AliGenTHM class is interface for C++ fortran code ( not yet completely finished). Its work with AliHBTReaderKineTreeTHM which allows to select different resonances and study the CF with pions from: - direct pions+pions from rho decay, - direct pions+pions from omega decay, - direct pions+pions from eta and eta’ decays.

20. Projections of the three-dimensional two-pion CF CF(Qout), CF(Qside), CF(Qlong) for direct pions and pions from rho decays. Cuts on the other two axes Qj<0.01GeV/c, Qk<0.01GeV/c; -1<y<1, pt < 2.5 GeV/c

21. Projections of the three-dimensional two-pion CF CF(Qout), CF(Qside), CF(Qlong) all pions. Cuts on the other two axes Qj<0.01GeV/c, Qk<0.01GeV/c; -1<y<1, pt < 2.5 GeV/c

22. Conclusions and plans: -AliGenTHMFiles is tested; -To finish AliGenTHM class; -To simulate sufficient number of events with rescattering model to study combined effects resolution+resonances excitation including different resonances by AliHBTKineTreeTHMReader.