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TWO PARTICLE CORRELATIONS IN p-A WITH IDENTIFIED AND UNIDENTIFIED TRIGGER PARTICLES

TWO PARTICLE CORRELATIONS IN p-A WITH IDENTIFIED AND UNIDENTIFIED TRIGGER PARTICLES. Debojit Sarkar VECC,KOLKATA. MOTIVATION. CMS has observed a near side ridge in high-multiplicity pp and p-Pb collisions ALICE has observed “ Double-Ridge ” in p-Pb collisions.

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TWO PARTICLE CORRELATIONS IN p-A WITH IDENTIFIED AND UNIDENTIFIED TRIGGER PARTICLES

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  1. TWO PARTICLE CORRELATIONS IN p-A WITH IDENTIFIED AND UNIDENTIFIED TRIGGER PARTICLES Debojit Sarkar VECC,KOLKATA

  2. MOTIVATION • CMS has observed a near side ridge in high-multiplicity pp and p-Pb collisions • ALICE has observed “Double-Ridge” in p-Pb collisions. • Yield associated with Unidentified trigger has contribution from both baryon and meson triggers. • Our goal is to study identified trigger dependence of ridge & jet cone yield in p-A & p-p.

  3. LONG RANGE CORRELATION—INITIAL STAGE EFFECT arXiv:0804.3858v1 • If there is no medium formation due to the collision , the correlation between two correlated • particles separated by large pseudorapidity difference must be originated at an earlier time due • to causality argument. • (carrying some signature of initial stage effect)

  4. Data,Events and Tracks selection • DATA: p-Pb at √sNN= 5.02 TeV LHC13b(pass3)+LHC13c(pass2)[AOD] • Monte Carlo: p-A ,DPMJET LHC13b2_fix_2 production • EVENTS: kINT7 triggered events with |zvertex|<10cm. • TRACK CUTS: 1.Filterbit->768(Hybrid tracks) 2.Tracks passed-> AliAODTrack::kPrimary 2.Pt >0.2 GeV.3.-0.9<η<0.9.4. No of TPC Clusters>70. 5.ChiSq/ndf ≤4.0

  5. Basic QA Plots DCAxy<2.4 DCAz<3.2 No. of TPC clusters>70 Chi2/ndf<4

  6. Two-Particle Correlations Correlation between a trigger and an associated particle in certain pT intervals (pT,assoc < pT,trig) Signal distribution S contains correlation within the same event Background B contains "correlation" between different events

  7. SAME EVENT MIXED EVENT Mixed event normalized to unity Signal/Background • Background Corrects for pair acceptance & pair efficiency • Normalized such that it is unity around (Dh, Dj) = (0, 0)

  8. STAR Results • Trigger particles are divided into two classes(only TPC is used): a) Pions • b)Protons+kaons • nσ π variablethe number of standard deviations of the particular track’s dE/dx value from the Bethe–Bloch expectation for a charged pion.

  9. Particle Identification In ALICE • In this analysis both TPC & TOF are used for identification of particles • (1.0<=Pt<=4.0 Gev/c) PlotsRoberto Preghenella ---Workshop on proton-nucleus collisions at the LHC - ECT* Trento (6th - 10th May 2013)

  10. PID in this Analysis • Trigger particles are identified into two classes—>1) Mesons(Pions+Kaons) • 2) Baryons(Protons) • Associated particles are identified into three classes1) Pions • 2) Kaons • 3) Protons • Both TPC & TOF are used for trigger and associated particle identification. • Each trigger and associated particle must have proper TPC and TOF response(i.e each track • must have to pass PID QA cuts associated with both TPC AND TOF ). • nsigma cut method(for both TPC AND TOF ) is used for particle identification . • To decide the value of the nsigma cut and to determine the purity of the sample • MC study(as a baseline) has been done.

  11. nSigma TOF MC 2.5<=Pt<=3.0 Gev/c 2<=Pt<=2.5 Gev/c 2.5<=Pt<=3.0 Gev/c 2<=Pt<=2.5 Gev/c counts counts nσ π nσ π TRIGGER Pt REGION counts 3.0<=Pt<=3.5 Gev/c counts 3.5<=Pt<=4.0 Gev/c 3.5<=Pt<=4.0 Gev/c 3.0<=Pt<=3.5 Gev/c nσ π nσ π

  12. nSigma TOF DATA counts counts 2<=Pt<=2.5 Gev/c 2.5<=Pt<=3.0 Gev/c nσ π nσ π TRIGGER Pt REGION counts counts 3.5<=Pt<=4.0 Gev/c 3.0<=Pt<=3.5 Gev/c nσ π nσ π

  13. nSigma TOF MC 2.5<=Pt<=3.0 Gev/c 2<=Pt<=2.5 Gev/c Counts(Log Scale) Counts(Log Scale) nσ π nσ π TRIGGER Pt REGION 3.0<=Pt<=3.5 Gev/c 3.5<=Pt<=4.0 Gev/c Counts(Log Scale) Counts(Log Scale) nσ π nσ π

  14. nSigma TPC MC Counts Counts 2<=Pt<=2.5 Gev/c 2.5<=Pt<=3.0 Gev/c nσ π nσ π TRIGGER Pt REGION Counts Counts 3.0<=Pt<=3.5 Gev/c 3.5<=Pt<=4.0 Gev/c nσ π nσ π

  15. nSigma TPC MC 2.5<=Pt<=3.0 Gev/c 2<=Pt<=2.5 Gev/c Counts(Log Scale) Counts(Log Scale) nσ π nσ π TRIGGER Pt REGION 3.5<=Pt<=4.0 Gev/c 3.0<=Pt<=3.5 Gev/c Counts(Log Scale) Counts(Log Scale) nσ π nσ π

  16. nSigma TPC DATA 2.5<=Pt<=3.0 Gev/c 2<=Pt<=2.5 Gev/c Counts(Log Scale) Counts(Log Scale) nσ π nσ π TRIGGER Pt REGION 3.0<=Pt<=3.5 Gev/c 3.5<=Pt<=4.0 Gev/c Counts(Log Scale) Counts(Log Scale) nσ π nσ π

  17. Trigger particle Identification • To remove electrons from pion sample(in trigger & associated regions) particles • having (TPC)>=3.9 are rejected. nσ π • In case of TPC, in this Pt region(2.0<=pt<=4.0 Gev/c) the kaon and proton curves are top of each other, so using TPC baryon meson separation is not effective. nσ π • At present , TOF is used for that purpose: • For 2.0<=pt<=2.5 if 6.9<= TOF<=14.0 if -3.5< TOF<=5.6 • For 2.5<=pt<=3.0 if 4.57<= TOF<=10.0 if -3.5< TOF<=4.04 • For 3.0<=pt<=3.5 if 3.45<= TOF<=7.5 if -3.5< TOF<=2.9 • For 3.5<=pt<=4.0 if 2.85<= TOF<=6.2 if -3.5< TOF<=2.3 • identified as baryons(protons) identified as mesons(pions+kaons) nσ π nσ π nσ π nσ π nσ π nσ π nσ π nσ π • Purity of trigger mesons99.3903% • Purity of trigger baryons93.1217% • May be a combined TPC-TOF nsigma cut can provide better purityTo be studied in future

  18. nSigma TOF MC 1<=Pt<=1.2 Gev/c 1.2<=Pt<=1.4 Gev/c Counts(Log Scale) Counts(Log Scale) nσ π nσ π Associated Pt Region 1.6<=Pt<=1.8 Gev/c 1.4<=Pt<=1.6 Gev/c Counts(Log Scale) Counts(Log Scale) nσ π nσ π

  19. nSigma TOF DATA 1<=Pt<=1.2 Gev/c 1.2<=Pt<=1.4 Gev/c Counts(Log Scale) Counts(Log Scale) nσ π nσ π Associated Pt Region 1.6<=Pt<=1.8 Gev/c 1.4<=Pt<=1.6 Gev/c Counts(Log Scale) Counts(Log Scale) nσ π nσ π

  20. nSigma TPC MC 1<=Pt<=1.2 Gev/c 1.2<=Pt<=1.4 Gev/c Counts(Log Scale) Counts(Log Scale) nσ π nσ π Associated Pt Region 1.6<=Pt<=1.8 Gev/c 1.4<=Pt<=1.6 Gev/c Counts(Log Scale) Counts(Log Scale) nσ π nσ π

  21. nSigma TPC DATA 1<=Pt<=1.2 Gev/c 1.2<=Pt<=1.4 Gev/c Counts(Log Scale) Counts(Log Scale) nσ π nσ π Associated Pt Region 1.4<=Pt<=1.6 Gev/c 1.6<=Pt<=1.8 Gev/c Counts(Log Scale) Counts(Log Scale) nσ π nσ π

  22. nSigma TOF MC nSigma TPC MC 1.8<=Pt<2.0 Gev/c 1.8<=Pt<2.0 Gev/c Counts(Log Scale) Counts(Log Scale) nσ π nσ π Associated Pt Region nSigma TPC DATA nSigma TOF DATA 1.8<=Pt<2.0 Gev/c 1.8<=Pt<2.0 Gev/c Counts(Log Scale) Counts(Log Scale) nσ π nσ π

  23. Associated Particle Identification • To remove electrons from pion sample(in trigger & associated regions) particles • having (TPC)>=3.9 are rejected. nσ π • To identify associated hadrons combined TPC-TOF 3 sigma cut has been applied: Purity of associated pions 98.8775% Purity of associated kaons97.2526% Purity of associated protons98.7177% • In this presentation associated particle(1.0<=pt<2.0) means (pions +kaons +protons) with • the above mentioned purity.

  24. Ratio of Signal to Mixed to get the Correlation function baryontrigallasso—0-20% centrality alltrigallasso----0-20% centrality ∆η ∆η Dj Dj mesontrigallasso—0-20% centrality ∆η Dj

  25. alltrigallasso—60-100% centrality Baryontrigallasso—60-100% centrality ∆η ∆η Dj Dj mesontrigallasso—60-100% centrality ∆η Dj

  26. Projections to Dh 0-20% centrality 60-100% centrality ∆η ∆η Dj • Raw Correlation projected onto ∆η averaged over for 0-20% & 60-100% • centrality events

  27. Projections to Dj 0-20% centrality 60-100% centrality Dj Dj • Raw Correlation projected onto ∆φ averaged over |∆η| < 1.7 on the near side & away side

  28. Can we separate the jet and ridge components? • No ridge seen in 60-100% and similar to pp • what remains if we subtract 60-100%? Shifted to same baseline by subtracting the value at Dj = 1.3 arXiv:1212.2001v1 • Low multiplicity class agrees with results from pp collisions • arXiv:1212.2001v1

  29. Ridge • Associated yield per trigger particle for the 0–20% centrality class, after • subtraction of the associated yield obtained in the 60–100% centrality class. • Associated yield per trigger • particle(unidentified) in ∆φ and ∆η (0-20%)-(60-100%) ∆η Dj ∆η ∆η Dj Dj • Associated yield per trigger particle • (MESON) in ∆φ and ∆η • Associated yield per trigger particle • (BARYON) in ∆φ and ∆η

  30. Projections to Dj (0-20%)-(60-100%) [+-0.9] [+-0.8] Dj Dj [+-1.0] [+-1.1] Dj Dj

  31. Projections to Dj (0-20%)-(60-100%) [+-1.3] [+-1.2] Dj Dj [+-1.5] [+-1.4] Dj Dj

  32. Projections to Dj (0-20%)-(60-100%) [+-0.8] [+-1.6] Dj Dj [(+-1.6)-(+-0.8)] Dj

  33. TODO: We observe small difference in pion and proton+kaon triggered yield in different ∆η and Dj regions . It need to be checked rigorously. Need to check purity of the trigger sample with combined TPC-TOF nsigma cut and to repeat the study. Need to repeat this analysis with identified associated to know the chemistry in jet & ridge regions. Need to apply the efficiency correction. Do the same for pp & and PbPb2.76 TeV

  34. Thank You

  35. BACKUP

  36. Efficiency with Pt

  37. Efficiency with Eta

  38. Since some parts of the SPD were switched off during many run periods, inefficient regions for common track reconstruction are apparent.To ensure uniform distributions in the (η,φ) plane, an approach of hybrid tracks of following types is used:

  39. Phi distribution Eta distribution

  40. TRACKING EFFICIENCY CORRECTION Efficiency with Eta Efficiency η

  41. Normalized such that it is unity around (Dh, Dj) = (0, 0) Mixed event normalized to unity

  42. EVENT MIXING TO CONSTRUCT BACKGROUND • Centrlity is divided into{ 0, 1, 2, 3, 4, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100.0}; • Zvertex of the events are divided into{-10,-8,-6,-4,-2,0,2,4,6,8,10} • Corresponding to a particular centrality & Zvertex bin, trigger particles from a particular • event are paired with associated particles from 5 other events of the same centrality & • Zvertex bin to construct the background. ∆η Dj • Is there any problem in the binning of centrality & Zvertex(definition of pool)?

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