ITS “parallel” tracking Marian Ivanov

ITS tracking Parallel TPC tracking included to the ESD schema ITS - Momentum resolution improvement Full Hijing dPt/pt ~ 0.8 % old( non parallel) TPC tracking dPt/pt ~ 0.75 % new (parallel) TPC tracking ITS tracking efficiency improvement But also increase of the fake tracks amount

ITS clusterer Why so many fakes ?  Change in the AliITSclustererV2 Many of them not real fakes – only cluster labels were not properly assigned  Change in the AliITSclustererV2 Track labels assigned according digits label in full cluster Before only at the cluster center Decrease of fake ratio - mainly for high pt tracks Clustering algorithm not modified Plan to implement: new unfolding Write cluster shape information – as a analog to the TPC cluster

Old ITS tracker Required all 6 clusters on the track But cluster funding efficiency is not 100 % (~98.5% for full event) Forbids cluster sharing between the track But clusters are (with some probability) shared Asymmetric algorithm for cluster removal First track take all the clusters If is fake, this algorithm by default produce another fake track Big plus ITS tracker – recursive tracking schema implemented Tree of the track hypothesis checked Decision which track hypothesis to accept – made according position chi2

New ITS tracking (1) Based on old ITS tracking Differences: Cluster sharing allowed (fNShared data member in ITStrack) Cluster skipping allowed (fNSkipped data member) Cuts – fNShared (currently<2), fNSkipped (currently<2), fNShared+fNSipped (currently<2) dEdx mismatch taken to the account Cluster signed as used only if not another almost equally probable hypothesis exists Probability of i_th hypothese being correct is defined as follows:

New ITS tracking (2) Differences: Decision which track from the tree of the hypothesis to accept postponed Additional information used dEdx matching coefficient Usage of the cluster “Parallel tracking” weight for each cluster in the track is calculated where P(i) is the probability that cluster belong to track I weighted chi2 used

Performance - Hijing peripheral 2 event Pt dPt/Pt[%] Efficiency [%] no fake cluster Efficiency[%] one fake cluster accepted Efficiency[%] two fake clusters accepted Pt>0.2 0.70 93.7 94.7 95.5 Pt>0.4 0.65 95.2 95.9 96.5 Pt>0.6 0.62 95.1 96.4 96.6

Performance – Full Hijing Pt dPt/Pt[%] Efficiency [%] no fake cluster Efficiency[%] one fake cluster accepted Efficiency[%] two fake clusters accepted Pt>0.2 0.755 84. 89. 91.8 Pt>0.4 0.72 88 91.5 93.2 Pt>0.6 0.71 90.5 92.7 93.6 V0 tracking efficiency Based on one event K0S – 62% (5/8) -1 Fake Planned to use production to improve statistic and to tune its tracking

Full Hijing event

Performance – Full Hijing Left side – ITS dEdx as function of the momenta Right side – relative Pt resolution as a function of pt

V0 Performance – K0S K0s event produced to estimate V0 finding efficiency 2000 primary K0s TPC occupancy – corresponds to hijing peripherial2 Efficiency ~80 % K0s peak centered at 0.4972+-0.0025 GeV (K0S mass = 0.4976 GeV)

Conclusion First version of ITS parallel tracking implemented Efficiency and pt resolution improved V0 efficiency Need to apply algorithm using bigger statistic