1. Stato della preparazione dell’analisi D + → K -  +  + Elena Bruna, Massimo Masera, Francesco Prino Università di Torino e INFN Secondo convegno nazionale sulla fisica di ALICE, 30 Maggio – 1 Giugno 06, Vietri sul Mare

2. Elena Bruna2 Outline  Physics motivations for D + analysis  Selection of the signal 1.Single track cuts 2.Secondary vertex finder 3.How to combine the triplets 4.Cuts on the triplets  First preliminary results of the D + feasibility study on a sample of events: 1. Perfect PID (given by the simulation) 2. Experimental PID (combined) 3. NO PID  Time-consumption problems, first ideas to avoid these problems → new analysis strategy

3. Elena Bruna3 Why also D + (and D s …)? 1.D 0 /D + ratio: puzzle Expected to be 3.08 from spin degeneracy of D and D* and decay BR Measured by ALEPH@LEP to be 2.32 2.Different selection strategies due to: “longer” mean life D + has a “longer” mean life (c  ~311  m compared to ~123  m of the D 0 ) D + fully reconstructable from a 3-charged body decay instead of the 2 (or 4) body decay of D 0 Accurate measurement of the charm production cross section

4. Elena Bruna4 D + → K -  +  + vs D 0 → K -  + “long” mean life 1.D + has a “long” mean life (c  ~311  m compared to ~123  m of the D 0 ) large branching ratio 2.D + → K -  +  + has a relatively large branching ratio (BR=9.2% compared to 3.8% for D 0 → K -  + ). Advantages… …drawbacks 1.Combinatorial background 1.Combinatorial background for this 3-body channel is larger than for D 0 → K -  +. P T softer 2.The average P T of the decay product is softer (~ 0.7 GeV/c compared to ~ 1 GeV/c for the D 0 )

5. Elena Bruna5 D ± statistics N events for 2·10 7 MB triggers N cc = number of c-cbar pairs Includes shadowing EKS98 Shadowing centrality dependence from Emelyakov et al., PRC 61, 044904 D ± yield calculated from N cc Fraction N D± /N cc (≈0.38) from tab. 6.7 in chapt. 6.5 of PPR Geometrical acceptance and reconstruction efficiency Extracted from 1 event with 20000 D ± in full phase space B. R. D ±  K  = 9.2 % b min -b max (fm)  (%) N events (10 6 ) N cc / ev.D ± yield/ev. 0-33.60.7211845.8 3-6112.28231.8 6-9183.64216.3 9-1225.45.112.54.85 12-18428.41.20.47

6. Elena Bruna6 Simulation and analysis strategy Central Pb-Pb event (b<3.5 fm, dN/dy = 6000, √s=5.5 TeV) ~ 9 D + /D - in |y|<1 Too large statistics (10 8 events) would be required to study the signal!! Signal and background events separately generated with the Italian GRID  P T of the decay tracks is “soft” ~0.7-0.8 GeV/c  The magnetic field is low - 0.5 T - to allow the reconstruction of soft particles (~ 7000 in |y|<1)  huge combinatorial background A dedicated trigger for D + → K -  +  + seems not possible. Simulation Good secondary vertex reconstruction capability (c  (D+) ~ 300  m  resolution of 200  m would be bad, 50  m would be a dream…) Efficient system of cuts to discriminate the signal from the background Analysis

7. Elena Bruna7 1 st step: Single track cuts Cuts on P T , P T K, track impact parameter (d 0 ) on all the tracks for both signal and background events SelectionS/eventB/event S/B No cuts 0.110 9 10 -10 Cuts: P T  = 0.5 GeV/c P T K =0.7 GeV/c d 0 = 95  m (8%) 0.008 10 6 10 -8 Choices of cuts which maximise the Significance Not optimized cut: we want to preserve D + down to P T ~1 GeV/c Perfect PID is assumed

8. Elena Bruna8 2 nd step: Combining K-  pairs KiKi … 11 22 jj … IDEA IDEA: start from BKG pairs of K  tracks (once the single track cut have been performed) and cut on the distance between the 2-track vertex and the primary one K  KjKj both K  pairs are required to pass the cut

9. Elena Bruna9 3 rd step: Combining the Triplets Single track cuts: applied Cut on the 2-tr vertex: applied K  are combined together according to the sign of their impact parameter Signal Background d 0 K x d 0  1 d 0 K x d 0  2 empty When (d 0 K x d 0  1)<0 & (d 0 K x d 0  2)<0. Due to the kinematics of the decay Cut on d 0 … d 0 K x d 0  1

10. Elena Bruna10 ZOOM BLACK: signal RED: BKG K  Triplets BLACK: signal RED: BKG K  Triplets P 1 (x 1,y 1,z 1 ) Secondary Vertex (x 0,y 0,z 0 ) d1d1 Secondary Vertex Finder on the Triplets BLACK: signal RED: BKG K  Triplets Cut on the quality of the Vertex. Sigma: track

11. Elena Bruna11 Cuts on the Triplets 1.Quality of the vertex: Sigma (prev. Slide) 2.Distance between primary and secondary vertices The signal is peaked at 1 cosθ point 3.Cut on the cosine of the pointing angle defined by the P T of the D + and the line connecting primary and secondary vertices BLACK: signal RED: BKG K  Triplets

12. Elena Bruna12 First strategy adopted for the analysis For each variable (in the order Sigma, distance, cosθ point ): 1. loop on all the triplets (both signal and background) 2. Keep the value of the cut with Max Significance S/√(S+B) in the range |M INV K  -M D + |<1  3. Use this value to maximize the Significance for the next cut variable Different ranges of the reconstructed p T of the triplet Perfect PID, PID and without PID Statistics Statistics used in this preliminary analysis: BKG BKG: 500 HIJING events SIG SIG: 8.5 X 10 5 reconstructed signal triplets

13. Elena Bruna13 Perfect PID – p T integrated Chosen cuts: Sigma=0.018 cm Dist=1900  m cos  point =0.995 Signif = 44±11 S/ev = 0.001 B/ev = 0.004 Significance Significance Significance Sigma Distance cosθ point The Significance is normalized to 10 7 central events

14. Elena Bruna14 SIGNAL – BKG at different cut levels NO cuts Single track cuts Dist 2tr-vert sigma Distance prim-sec cosθ point NO cuts Single track cuts Dist 2tr-vert sigma Distance prim-sec cosθ point Number of SIGNAL triplets per event (full inv mass range) Number of BACKGROUND triplets per event (full inv mass range)

15. Elena Bruna15 PID Combined Bayesian PID (ITS+TPC+TOF+TRD+HMPID) is used Prior probabilities used in input: P(p)=0.055 P(K)=0.072 P(  )=0.864 P(e)=0.006 P(  )=0.003 PID in the ITS done with:  Clusters from all the 4 layers (2 SDD+2 SSD)  Convoluted Landau-Gaussian fits to the response functions in each layer  See AliITSpidESD2 implemented in AliRoot Track tagged as type i when the corresponding combined Bayesian probability is P(i|track)>0.85

16. Elena Bruna16 PID – p T integrated Chosen cuts: Sigma=0.019 cm Dist=2000  m cos  point =0.995 Signif = 40±15 S/ev = 0.0007 B/ev = 0.002 Significance Significance Significance Sigma Distance cosθ point

17. Elena Bruna17 Without PID – p T integrated No selection of tracks based on the particle identity Chosen cuts: Sigma=0.019 cm Dist=1800  m cos  point =0.999 Signif = 39±12 S/ev = 8 X 10 -4 B/ev = 0.004 Significance Significance Significance Sigma Distance cosθ point

18. Elena Bruna18 Significance p T integrated results Perfect PID PID No PID Significance44 ±1140 ± 1539 ± 12 Low p T under study : 1.Rebinning 2.Additional cuts Preliminary global results Analysis feasible also without PID, but more time consuming

19. Elena Bruna19 D + elliptic flow: measurement perspectives Error bars quite large  Would be larger in a scenario with worse event plane resolution (lower dN ch /dy or v 2 )  May prevent to draw conclusions in case of small anisotropy of D mesons  v 2 vs p T requires a semi-peripheral trigger 2·10 7 Minimum Bias events

20. Elena Bruna20 Conclusions  The reconstruction of D + → K -  +  + is a promising study. analysis is feasible  The preliminary results show that the analysis is feasible with a pretty good Significance.  More statistics is mandatory for a more accurate optimization of the cuts.  There still is room for optimization: work in progress.

21. Elena Bruna21 Outlook New cut strategy: For each event fill 2 multi-dimesional matrices (one for Signal and one for BKG), each cell containing the number of triplets corresponding to all the possible combinations of cut variables. Es. with 5 cut variables and 30 steps for each variable  30 5 cells (~200MB per ev for Signal+BKG) Sum all the multi-dimesional matrices (Signal and BKG) on all the events Maximize the multi-dim matrix of the Significance Apply LDA pp studies to come on the PDC06 events and on italian production with parametrized TPC

22. Elena Bruna22 Backup slides

23. Elena Bruna23 D +  K -  +  + BR = 9.2 % D ± I(J P ) = ½ (0 - ) m = 1869.4 MeV/c 2 c  = 311.8  m (PDG ’04) D + →K -  +  + Non ResonantBR = 8.8 % D + →K *0 (892)  + →K -  +  + ResonantBR = 1.3 % D + →K *0 (1430)  + →K -  +  + ResonantBR = 2.3 % D + →K *0( 1680)  + →K -  +  + ResonantBR = 3.8·10 -3 % Hadronic 3-charge-body decays of D +

24. Elena Bruna24 D K  P T P T distributions of the generated particles (ONLY PYTHIA generation, NO propagation and reconstruction in the detector) (nonresonant events) Mean = 1.66 GeV/c Mean = 0.87 GeV/c Mean = 0.67 GeV/c Kinematics (1) Knowledge of the P T shapes of the decay products important at the level of the selection strategy

25. Elena Bruna25 Non resonant Resonant Sharp borders due to PYTHIA cut off on the tails of distributions Dalitz Plots: Kinematics (2)

26. Elena Bruna26 Combining K-  pairs /2 Best Significance: cut distance of the 2-tr vertex = 700  m  63% Signal triplets pass the cut S/ev=0.006  10 5 remaining BKG triplets per event. P t reconstructed D + Mean=2.66 GeV/c Low P T D + still kept S/B = 6 X 10 -8 still low… Full invariant mass range

27. Elena Bruna27 Display D + decay (made with the kinematics) Impact parameter: Definition: segment of minimum distance of the (prolonged) track from the primary vertex Sign: + : primary vertex in the track “circle” - : primary vertex out of the track “circle” K+K+ 1-1- 2-2- Primary vertex Secondary vertex Points on the 3 prolonged tracks defining the impact parameter d 0 K + : d 0 >0  1 - : d 0 >0  2 - : d 0 >0

28. Elena Bruna28 Measurement of v 2 Calculate the 2nd order coefficient of Fourier expansion of particle azimuthal distribution relative to the reaction plane –The reaction plane is unknown. Estimate the reaction plane from particle azimuthal anisotropy: –  n = Event plane = estimator of the unknown reaction plane Calculate particle distribution relative to the event plane Correct for event plane resolution –Resolution contains the unknown  RP –Can be extracted from sub-events Unknown reaction plane Event plane resolution

29. Elena Bruna29 Worse resolution scenario Low multiplicity and low v2 Large contribution to error bar on v 2 from event plane resolution

30. Elena Bruna30 Semi-peripheral trigger v 2 vs. p T that would be obtained from 2·10 7 semi-peripheral events ( 6<b<9 ) p T limitsN(D ± ) sel  v 2 ) 0-0.56450.03 0.5-112900.02 1-1.518000.017 1.5-216500.018 2-324700.015 3-411600.02 4-812250.02 8-152200.05