Particle Correlations Results for PDC04 data Alice Week June 2004

1. Particle Correlations Results for PDC04 dataAlice Week June 2004 Zbigniew Chajęcki, Grzegorz Gałązka, Hanna Gos, Daniel Kikola, Jan Pluta, Piotr Skowroński Piotr Skowroński Alice Week June 2004

2. Resolutions • Dispertions and means are calculated by fitting Gaussians • Particles were selected if their PID probability was higher then 0.5 Piotr Skowroński Alice Week June 2004

3. Single Paricle Resolutions: Pions Piotr Skowroński Alice Week June 2004

4. Sngl. Part. Resol. Kaons Piotr Skowroński Alice Week June 2004

5. Sngl. Part. Resol. protons Piotr Skowroński Alice Week June 2004

6. Cuts Study (1) • We have examined possibility of reducing non-Gaussian tails • 2 given of track fit • reduces the tails of angular coordinates • Improves  resolution • Distance of Closest Approach to Primary Vertex • Does not remove the tails • Very strongly influences  resolution Piotr Skowroński Alice Week June 2004

7. Cut Study (2) • Diagonal elements of the covariance matrix • C22 • reduces tails in angular components • In order to remove the tails comletely it is necessary to set value that rejects 40% of the statistics • Improves  resolution • C33 • No influence • C44 • Setting treshold even on relatively high value reduces very efficienly tails in pt • No influence on RMSs • C11 and C22 • Their distributions depend very strongly on an event multiplicity • Not suitable for multi-event analysis • All detailed plotots are available athttp://aliweb.cern.ch/people/skowron/results/PDC04/cent1/CutStudy/res.single.pi+pi+.html Piotr Skowroński Alice Week June 2004

8. Cut Study (3) • 2<3 C22<3e-6 C33<10e-6 C44<12e-3 vx&vy&vz<40mm • reduces statistics to 60% (1628 out of 2419 p+) Piotr Skowroński Alice Week June 2004

9. Cut Study (4) Piotr Skowroński Alice Week June 2004

10. Two Particle Resolutions (1) Piotr Skowroński Alice Week June 2004

11. Two Particle Resolutions (2) • Resolution values are very close to the ones in Technical Proposal • Improvement in Qout is connected to better pt resolution and higher magnetic field Piotr Skowroński Alice Week June 2004

12. Two Particle Resolutions (2) Piotr Skowroński Alice Week June 2004

13. Systematic skews - identical • Systems of identical particles are not affected much by the skews of the single particle properties • Almost everywhere skews are below 1 MeV Piotr Skowroński Alice Week June 2004

14. Systematic skews – non-ident • However it looks much worse for non-identical systems Piotr Skowroński Alice Week June 2004

15. Track Splitting (1) • Stand alone ITS tracking introduces artificial correlations • Around 100 tracks per event are already found tracks • We get rid of this problem requiring fit from TPC Piotr Skowroński Alice Week June 2004

16. Track Splitting (2) • We did not observe track splitting in our data • Tracking program filters them out itself • Anyway we have implemented STAR algorithm • Fq can range from -0.5 (low likelihood of being splitted track) to 1.0 (high likelihood) • In sample of 150 events we did not found a single pair having Fq bigger then 0.6 Piotr Skowroński Alice Week June 2004

17. Track Merging – ident. (1) • Anti-Merging cut as implemented by STAR • Cutting on average distance between two tracks in TPC • Space coordinates of tracks are calculated assuming helix shape using track parameters as reconstructed in the inner part of TPC Piotr Skowroński Alice Week June 2004

18. Track Merging – ident. (2) • In ALICE it does not work because we have ITS • Two tracks emitted with close momenta can appear in TPC far away from each other due to the multiple scattering • ITS has very fine granularity and ITS tracking is able to reconstruct such pairs • However, with lower efficiency • It means that the effect persist. Piotr Skowroński Alice Week June 2004

19. Track Merging – ident. (3) • Df Dq Dpt correlation functions (no BE) Piotr Skowroński Alice Week June 2004

20. Track Merging – ident. (4) • At the first glance effect was removed • However, there still persisted some effect that influences only shape of Qside and Qlong correl. fctns. • More detailed analysis is needed Piotr Skowroński Alice Week June 2004

21. Track Merging – non-ident. (1) • On the first glance track merging effects should not be present in non-identical analysis • They are bended in opposite directions by the magnetic field • However, it is also present in this kind of analysis Piotr Skowroński Alice Week June 2004

22. Track Merging – non-ident. (2) • Here is shown effect recognized as merging on the first layer of pixels • Occurs only for Qside > 0 and small Dq • Cut which rejects pairs passing from each other closer than 200mm in z and 800mm in rf (at radius of 4cm) solved the problem Piotr Skowroński Alice Week June 2004

23. Track Merging – non-ident. (3) • We observed other merging effect that origin we still do not understand • Following potential sources are already excluded • Merging at the second layer of pixels • Inefficiency when doing prolongation from TPC to ITS Piotr Skowroński Alice Week June 2004

24. Track Merging • If we go to fine binning we see correlations due to the pixel granularity! • Claster position is always reconstructed at the center of the pixel • One should be carefull not to go to too small bin size Piotr Skowroński Alice Week June 2004

25. Particle Identification • PID was found to be very high and not dependent on Q components • Thus does not influence much the shape of the correlation function • It was not the case only for very small values of Qs • Pairs falling into this phase space region are automatically excluded from analysis by the merging cut • Problems with PID are coupled with cluster sharing (for a given pt) Piotr Skowroński Alice Week June 2004

26. PID (2) • It was found that pair PID probability distribution (calculated as product of two particle probabilities) has completely different shape that PID efficiency distribution • It makes impossible to use PID probability to correct for its inefficiency Piotr Skowroński Alice Week June 2004

27. Correlation Functions • Clear merging effect in Qside and Qlong • Very good resolution and PID • We will anyway correct it but first we have get rid of the merging effect Piotr Skowroński Alice Week June 2004

28. Fits to Correl. Functions: 3D • 3D fit, (range 0-50MeV): • Qout=7.92 ± 0.03 fm • Qside=7.84 ± 0.02 fm • Qlong=8.16 ± 0.02 fm • l=0.87 ± 0.01 • 2/NDF=1.48 • 2 depends strongly on the maximum range • If wide range is used 2 is good, of course • Fitted values does not depend on it • Fitted values depend on minimum of the range • Already mentioned merging effect Piotr Skowroński Alice Week June 2004

29. Fit to 2D Qout-Qside CF • In central events cross-term should be always 0 due to the symmetry constraints • Used as merging-detection tool in real data analysis • Fitted values: • Qout=8.01 ± 0.03 fm • Qside=7.50 ± 0.02 fm • Qout-side=-2.42 ± 0.5 fm • 2/NDF=1.23 (range 50MeV) • Again, clearly visible influence of the merging effect Piotr Skowroński Alice Week June 2004

30. Fits to 1D projections Piotr Skowroński Alice Week June 2004

31. Event by Event Piotr Skowroński Alice Week June 2004

32. CorrFit • CorrFit is a tool developed in STAR by Adam Kisiel • CorrFit is able to find parameters that fits correlation function taking to the account: • Final State Interaction (Coulomb and strong) • They are not corrected for! • Detector resolution • Can work with any model of the freeze-out distribution • Not limited to Gaussian source distribution • Is able to fit non-identical particles correlation functions Piotr Skowroński Alice Week June 2004

33. CorrFit - Algorithm (1) • For given set of parameters (f.g. l, Rout) map of 2 is created • For given values of the parameters, 2 describes how theoretical correlation function fits to the experimental correlation function • Theoretical function is created • Using mixed pairs (coming from different events) • No correlation between particles • Realistic two- and one-particle spectra • Assuming some modelof position distribution at freeze-out (f.g. Gaussian) • particles are given (randomized) positions at freeze-out • For each pair weight is calculated • Plane wave approximation (Lednicky or Pratt afterburner) • It takes to the account both, BE and FSI Piotr Skowroński Alice Week June 2004

34. CorrFit – Algorithm (2) • Afterwards, particles momenta are smeared according to detector resolution • Histogram is filled at position corresponding to the smeared momenta with weight calculated with not-smeared momenta • This reproduces distortions introduced by the detector • Map is fitted with paraboloid • Its minimum defines measured parameters Piotr Skowroński Alice Week June 2004

35. PPR statatus • We prepare extensive Alice note which contains all detailed results • It will become the draft of the section 6.3 of PPR • All detailed plots and descriptions are available at: http://aliweb.cern.ch/people/skowron/results/PDC04/cent1 Piotr Skowroński Alice Week June 2004

36. To Do List • Get rid of all merging effects • Fit CFs with CorrFit • Estimate systematic errors • Do analysis for other systems and other centralities and pp Piotr Skowroński Alice Week June 2004

37. Backup Piotr Skowroński Alice Week June 2004

38. Piotr Skowroński Alice Week June 2004

39. Piotr Skowroński Alice Week June 2004