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Open charm reconstruction in the ALICE experiment

Open charm reconstruction in the ALICE experiment. Elena Bruna Supervisor: Prof. Massimo Masera. Seminar for the end of 2 nd year (XIX) – Torino, Dec 2 nd 2005. Outline. Physics motivations of open charm analysis in Heavy Ion Collisions D + → K - π + π + : overview of the kinematics

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Open charm reconstruction in the ALICE experiment

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  1. Open charm reconstruction in the ALICE experiment Elena Bruna Supervisor: Prof. Massimo Masera Seminar for the end of 2nd year (XIX) – Torino, Dec 2nd 2005

  2. Outline • Physics motivations of open charm analysis in Heavy Ion Collisions • D+→ K-π+π+ : overview of the kinematics • Measurement of open charm in the ALICE experiment • Exclusive reconstruction of D+→ K-π+π+: • Event generation and reconstruction • Reconstruction of the secondary vertex • Selection strategy • Perspectives for the measurement of D+ elliptic flow • Summary and work plans Elena Bruna

  3. Motivations for the Open Charm physics in Heavy Ion Collisions Elena Bruna

  4. charm, bottomproduced at early stages of the collision (timescale ~ 1/mQ < QGP~ 10 fm at LHC) Studies of initial state effects: nuclear shadowing Because of the very low x down to ~10-4 at LHC the so many gluons merge together, affecting the partons densities at low x w.r.t. protons partons ones. thermal production  The c quark might be produced in the plasma phase: mc (~ 1.2 GeV) comparable with predicted Tplasma (~ 0.6-0.8 GeV) open QQ production (not Drell-Yan) natural normalization for QQ studies  Quarkonia enhancement at low PT and suppression at high PT. Heavy quarks as probes of nuclear medium /1 Elena Bruna

  5. charm, bottom have long lifetime (> QGP ) and can probe the bulk, strongly interacting phase Studies of final state effects: 1) radiative energy loss Hard partons radiate gluons in the medium, lose energy and become quenched. Heavy quarks are expected to lose less energy than light quarks. High E  suppression of the produced particles (at high PT)  RAA≠1 Heavy quarks as probes of nuclear medium /2 Nuclear modification factor It depends on the properties of the medium (gluon density, temperature and volume), it provides information on such properties. Elena Bruna

  6. Studies of final state effects: 2) anisotropic flow on the transverse plane EllipticFlow = collective motion of particles (due to high pressure arising from compression and heating of nuclear matter) superimposed on top of the thermal motion Heavy quarks as probes of nuclear medium /3 Correlation between azimuthal angles of outgoing particles and the direction of the impact parameter (REACTION PLANERP) Elliptic flow coefficient High opacity of the medium (strongly interacting)  high anisotropic flow  high v2 v2provides information on the opacity of the medium. Elena Bruna

  7. radiative energy loss - RAAof the D mesons ( PT spectra of e+e- from Dsemileptonic decays ) Few experimental results from RHIC /1 q = 0 GeV2/fm dNg / dy = 1000 q = 4 GeV2/fm q = 14 GeV2/fm from QM05 from QM05 • Charm is suppressed! Suppression is approximately the same as for hadrons. • Challenge for energy loss models. Also pp and pA data are needed as reference! Elena Bruna

  8. anisotropic flow – v2of the D mesons ( f spectra of e+e- from Dsemileptonic decays ) Few experimental results from RHIC /2 from QM05 from QM05 • Significant flow of charm quark as for light quarks  Strong coupling of charm quark to the medium • Indication for reduction of v2 at pT > 2 GeV/c (PHENIX) Also pp and pA data are needed as reference! Elena Bruna

  9. D+ → K-p+p+ : overview of the kinematics Elena Bruna

  10. Why D+ → K-p+p+ ? Advantages… • D+ has a “long” mean life (~311mm compared to ~123 mm of the D0) • D+ → K-p+p+ is a 3-charge body decay  the most promising from an experimental point of view • D+ → K-p+p+ has a relatively large branching ratio (BR=9.2% compared to 3.8% for D0 → K-p+). …drawbacks • Combinatorial background for this 3-body channel is larger than for D0 → K-p+. • The average PT of the decay product is softer (~ 0.7 GeV/c compared to ~ 1 GeV/c) Elena Bruna

  11. Hadronic 3-charge-body decays of D+ D±I(JP) = ½ (0-) m = 1869.4 MeV/c2 c = 311.8 m (PDG ’04) D+K-++ BR = 9.2 % Elena Bruna

  12. Kinematics (1) K PT distributions of the generated particles (ONLY PYTHIA generation, NO propagation and reconstruction in the detector) (nonresonant events) Mean = 0.87 GeV/c D Mean = 1.66 GeV/c  Mean = 0.67 GeV/c Knowledge of the PT shapes of the decay products important at the level of the selection strategy Elena Bruna

  13. Kinematics (2) p Comparing with Pb-Pb central events (ONLY HIJING generation, NO propagation and reconstruction in the detector): PT distributions: Mean = 0.67 GeV/c Mean = 0.50 GeV/c nonresonant D+ decay K HIJING central (normalized) Mean = 0.87 GeV/c Mean = 0.65 GeV/c Kand p from D+ are harder than K and p produced in a Pb-Pb event Elena Bruna

  14. Dalitz Plots: Kinematics (3) Sharp borders due to PYTHIA cut off on the tails of distributions Non resonant Resonant Elena Bruna

  15. Measurement of open charm in the ALICE experiment Elena Bruna

  16. Time Projection Chamber (TPC) Tracking, PID (dE/dx) -0.9<<0.9 ALICE @ LHCsetup HMPID TRD MUON SPECTR.. PHOS Inner Tracking System (ITS): 6 SILICON layers (pixel, drift, strip) Vertices reconstruction, PID (dE/dx) -0.9<<0.9 Time Of Flight (TOF) Tracking, PID (time) -0.9<<0.9 Size: 16 x 26 m Weight: ~10,000 tons Elena Bruna

  17. Track Impact Parameter d0 SIGMA (fit) expected d0 resolution (s) d0 – d0 sim MEAN (fit) 0.4<Pt<0.6 GeV/c Elena Bruna

  18. Track Impact Parameter : d0 pull SIGMA (fit) Calculate the pull MEAN (fit) Elena Bruna

  19. Exclusive reconstruction of D+ → K-p+p+ Elena Bruna

  20. Simulation strategy Our purpose: exclusive reconstruction of D± in the ALICE barrel (Inner Tracking System employed in the search for secondary vertexes) Too large statistics (108 events) would be required to study the signal!! Central Pb-Pb event (b<3.5 fm, dN/dy = 6000, √s=5.5 TeV) ~ 9 D+/D- in |y|<1 Signal and background events separately generated with the Italian GRID • 5’000signal events with only D± decaying in Kpp (using PYTHIA): • Check the kinematics and the reconstruction • Optimize the vertexing algorithm • 20’000background events (central Pb-Pb events using HIJING): • cc pairs merged in addition in order to reproduce the charm yield predicted by NLO pQCD calculations (≈ 118 per event) • Tune the cuts (impact parameter cut,…) on the tracks to be analyzed by the vertexing algorithm • Evaluate the combinatorial background Elena Bruna

  21. Reconstructed signal events: Dalitz Plots Non resonant Resonant From reconstructed tracks ( : the info given by the generation are taken into account) This is done as an internal cross-check procedure Elena Bruna

  22. Reconstructed signal events: D+ invariant mass Mean Integrated over PT MEAN = 1.867 GeV/c2 RMS = 0.019 GeV/c2 this is not a complete reconstruction of the signal: tracks are grouped by means of info. stored at generation time. MINV Resolution (SIGMA of the gaussian fit) Knowledge of MINV resolution vs PT is important when selecting the signal candidates Elena Bruna

  23. Reconstruction of the secondary vertex for D+ → K-p+p+ • First idea:adapting and improving the method already written for the primary vertex finding and fitting in p-p • Second idea: writing a new secondary vertex finder and comparing its performace with the previous ones Elena Bruna

  24. Originally developed to find the primary vertex in p-p Based on the Straight Line Approximation of a track (helix) Main steps The method receives N (N=3 in our case) tracks as input Each track is approximated by a straight line in the vicinity of the primary vertex An estimation of the secondary vertex from each pair of tracks is obtained evaluating the crossing point between the 2 straight lines The coordinates of secondary vertex are determined averaging among all the track pairs: Vertex finder Elena Bruna

  25. Add a cut on the distance of closest approach (DCA) between the two straight lines A pair of tracks is not used for the vertex estimation if their distance of closest approach is > fDCAcut Use a weighted mean of the 2 DCA points In order to take into account the errors on the tracks parameters Calculate a parameter representing the dispersion of the vertices given by the track pairs (fSigma) Improving the Straight Line Vertex Finder Elena Bruna

  26. DCA cut effect fDCAcut = 1.5 mm fDCAcut = 0.7 mm RMS=179 μm RMS=178 μm Finder- MC (mm) Finder- MC (mm) RMS=182 μm RMS=181 μm Finder- MC (mm) Finder- MC (mm) RMS=165 μm RMS=163 μm Finder- MC (mm) Finder- MC (mm) No DCAcut X coord RMS=179 μm Finder- MC (mm) Y coord RMS=183 μm Finder- MC (mm) Z coord RMS=166 μm Elena Bruna Finder- MC (mm)

  27. Weighted mean effect Weighted mean RMS=179 μm Finder- MC (mm) Improved resolution on Z RMS=183 μm Finder- MC (mm) RMS=160 μm Finder- MC (mm) Arithmetic mean X coord RMS=179 μm Finder- MC (mm) Y coord RMS=183 μm Finder- MC (mm) Z coord RMS=166 μm Elena Bruna Finder- MC (mm)

  28. Dispersion fSigma = standard deviation of the 3 vertex estimations obtained from each track pair Vertices dispersion The DCA cut (at 0.7 mm) reduces the dispersion fSigma (cm) Elena Bruna

  29. A cut fSigma < 0.4 cm cuts 0.5% of the events and ≈30% of the overflows and underflows (i.e. events for which the VertexFinder misses the true vertex by more than 1 mm) Cutting on fSigma All events RMS=700 μm Finder- MC (mm) fSigma < 0.4 cm RMS=224 μm Finder- MC (mm) fSigma < 0.07 cm RMS=151 μm Finder- MC (mm) • A cut fSigma < 0.07 cm (700 mm) cuts 6.4% of the events and gives a RMS of 151 mm (for X coordinate) Elena Bruna

  30. Based on the Distance of Closest Approach (DCA) between helices Does not use a Straight Line Approximation as the old one Main steps The method receives N (N=3 in our case) tracks as input For each pair of tracks, the coordinates of the 2 points of closest approach are calculated An estimation of the secondary vertex from each pair of tracks is obtained averaging the coordinates of the points defining the DCA. Two different implemetations: arithmetic vs. wieghted mean The coordinates of secondary vertex are determined averaging among all the track pairs: The dispersion of the vertices given by the track pairs is calculated Another improvement: Helix vertex finder Elena Bruna

  31. Results from the helix finder Helix Finder RMS=169 μm Helix finder has better resolution and also a lower number of overflows and underflows (≈400 instead of ≈650) Finder- MC (mm) RMS=171 μm Finder- MC (mm) RMS=162 μm Finder- MC (mm) Straight Line Finder X coord RMS=179 μm Finder- MC (mm) Y coord RMS=183 μm Finder- MC (mm) Z coord RMS=166 μm Elena Bruna Finder- MC (mm)

  32. DCA cut effect on helix finders fDCAcut=1.5 mm fDCAcut=0.7 mm RMS=168 μm RMS=167 μm Finder- MC (mm) Finder- MC (mm) RMS=170 μm RMS=169 μm Finder- MC (mm) Finder- MC (mm) RMS=161 μm RMS=158 μm Finder- MC (mm) Finder- MC (mm) fDCAcut=1 cm X coord X coord RMS=169 μm Finder- MC (mm) Y coord RMS=171 μm Finder- MC (mm) Z coord Z coord RMS=162 μm Elena Bruna Finder- MC (mm)

  33. Weighted mean effect on helix finder Weighted mean RMS=168 μm Finder- MC (mm) Improved resolution on Z RMS=169 μm Finder- MC (mm) RMS=154 μm Finder- MC (mm) Arithmetic mean X coord RMS=169 μm Finder- MC (mm) Y coord RMS=171 μm Finder- MC (mm) Z coord RMS=162 μm Elena Bruna Finder- MC (mm)

  34. Same distribution as for Straight Line finder Vertices dispersion on Helix Finder The DCA cut reduces the dispersion fSigma (cm) Elena Bruna

  35. A cut fSigma < 0.4 cm cuts 0.5% of the events and ≈35% of the overflows and underflows (i.e. events for which the VertexFinder misses the true vertex by more than 1 mm) Cutting on fSigma All events RMS=480 μm Finder- MC (mm) fSigma < 0.4 cm RMS=209 μm Finder- MC (mm) fSigma < 0.07 cm RMS=140 μm Finder- MC (mm) • A cut fSigma < 0.07 cm (700 mm) cuts 5.6% of the events and gives a RMS of 140 mm (for X coordinate) Elena Bruna

  36. New secondary vertex finder Straight Line Approximation used → analytic method Vertex coordinates (x0,y0,z0) from minimization of: Where:d1,d2,d3are the distances (weighted with the errors on the tracks) of the vertex from the 3 tracks: P1 (x1,y1,z1) SecondaryVertex (x0,y0,z0) σx = σy d1 Elena Bruna

  37. Resolution of the vertex finder RMS x RMS y At high Pt of D+ (Pt>5-6 GeV/c), the RMS in the bending planeincreases, instead of going down to ~15µm (spatial pixel resolution) as expected. RMS z Conclusion New method improves RMS of ~40μm for PtD+ ~ 2GeV/c for x, y and z with respect to previous Helix vertex finder based on DCA of pairs of tracks. Elena Bruna

  38. Resolution at high Pt /1 Checks with events only made of pions show that the RMS on the bending plane: • Decreases down to 50 µm if the 3 tracks have Pt ~ 2 GeV/c • Reaches a value of ~20 µm (in agreement with spatial pixel resolution) if the 3 tracks have Pt =100 GeV/c 3 pion vertex:RMS in the bending plane vs. Pt Elena Bruna

  39. Resolution at high Pt /2 y y x’ y’ rotated x x In the signal events, as the Pt of the D+ increases, the “daughters” become more and more co-linear, resulting in a worse resolution along the D+ direction. π+ π+ K- bending plane D+ Elena Bruna

  40. Resolution in the rotated frame /1 Along the Pt of the D+ (x’ coord.) Orthogonal to the Pt of the D+ (y’ coord.) → Along the Pt of the D+: as Pt increases (for Pt>5-6 GeV/c) the angles between the decay tracks become smaller: in this coordinate the RMS increases → Orthogonal to the Pt of the D+: the RMS decreases as expected Elena Bruna

  41. Resolution in the rotated frame /2 RMS along Pt RMS orthog Pt RMS along Pt RMS z RMS orthog Pt RMS z Ratios: Elena Bruna

  42. Vertices dispersions/1 Δx = XVertex FOUND – XVertex MC Δx < 1000 μm 1000<Δx <3000 μm 3000<Δx <5000 μm Δx > 5000 μm fSigma bigger for bad vertices fSigma (cm) Elena Bruna

  43. Vertices dispersions/2 Cut on fSigma (for X coordinate) Vertices taken / Vertices Tot (“True” vertices) “Fake” vertices (tracks coming from 3 different D+ vertices) RMS x (μm) Mean x (μm) • fSigma < 0.7 cm cuts ~1% of the events and gives a RMS of 130 μm • fSigma < 0.5 cm cuts ~6% of the events and gives a RMS of 110 μm Elena Bruna

  44. The Straight Line vertex finder: DCA cut: negligible effect on the RMS of the residual distributions, slightly reduced number of overflows and underflows The use of a weighted mean: improves Z resolution by ≈6 mm Cutting on the dispersion fSigma: removes the events for which the VertexFinder misses the true vertex by more than 1 mm and improves the resolution Conclusions on the finders • The Helix vertex finder: • Has better resolution w.r.t. Straight Line finder (by approximately 10 mm) • Has less overflows and underflows w.r.t. Straight Line finder • DRAWBACK: the DCA between helices is obtained by minimization • DCA cut, weighted mean and fSigma cut: improve the resolution • The Minimum Distance vertex finder: • Has better resolution w.r.t. Helix finder (by approximately 30 mm) • Has less overflows and underflows w.r.t. previous finders • Is an analytic method • Weighted mean and fSigma cut: improve the resolution • Is presently THE candidate for first D+ analysis • A cut on fSigma has to be tuned (it can be done at analysis level) Elena Bruna

  45. D+ selection strategy Elena Bruna

  46. Tuning the cuts GOAL: tune the cuts on both signal and background events and find the cuts giving the best S/B. (S/B = 11% was found for the D0K-p+) • CUT TIPOLOGIES: • On the single tracks used to “feed” the vertexer (Particle Identification,pT, track impact parameter) •  reduce the number af all the possible combinations of track-triplets in a central Pb-Pb collision (~ 1010 without any initial cut!!). It MUST be cut by 4-5 orders of magnitude before using the more time-consuming vertexer. • In progress. • Once the triplets are combined, additional cuts (invariant mass and eventually pT, impact parameter) are mandatory before using the vertexer. These cuts are done on the triplets. • To be done. • The third kind of cuts is applied on the quality of the secondary vertices found (vertex dispersion-fSigma, pointing angle,…) • To be done. Elena Bruna

  47. Single track cuts /1 GOAL: find a compromise between the number of background triplets and the number of signals we want to take HOW: for each triplet (both signal and bkg) a loop on all the possible cuts (d0,Ptp,Pt K) is done Cut on the track impact parameter (d0) Particle Id. given by the generation: initial approach The number of BKG triplets is reduced by a factor of ~100 when doing the cut on the Invariant Mass within 3s (see slide 22) Elena Bruna

  48. Single track cuts /2 The number of BKG triplets is reduced by a factor of ~100 when doing the cut on the Invariant Mass within 3s (see slide 22) Bkg=Triplets No cut on the track impact parameter (d0) Cut on d0 lower cuts on Pt (useful up to Bkg ~105) Particle Id. given by the generation: initial approach Elena Bruna

  49. Tuning the single track cuts /2 When tuning a cut, one has to keep in mind how the Pt distribution of the D+ is modified Pt reconstructed D+ Mean=2.5 GeV/c Pt reconstructed D+ Pt cut (p) = 0.75 GeV/c Pt cut (K) = 0.6 GeV/c Mean=1.8 GeV/c Ratio: With cut / Wo cut Elena Bruna

  50. Perspectives for the measurement of D+ elliptic flow Elena Bruna

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