1. Material budget, energy losses and multiple scattering

2. Barrel tracking Momenta resolution for low momenta tracks determined mainly by energy losses and multiple scattering Left side – momentum resolution for pion Right side - proton

3. Energy loss between vertex and TPC Left - rel. loss as a function of particle velocity Right – function of particle momenta

4. Energy losses (Bethe Bloch)  -particle velocity  material density Z - atomic number of absorber A – mass number of absorber I – mean excitation energy  – density effect correction factor – material dependent and  dependent

5. Energy losses (Reconstruction)  - particle velocity  material density K1 and K2 – Effective parameters

6. Energy loses correction Left side - correction shift as function of particle velocity Right side – correction shift as function of particle momenta (pion)

7. Energy loses correction Left side - correction shift as function of particle momenta (kaon) Right side – correction shift as function of particle momenta (proton)

8. Multiple scattering (Gaussian approximation)  -particle velocity  material density P - particle momenta

9. Energy losses correction (Current) Material budget and radiation length hardwired in the code Using symmetry of the detectors Correction layer by layer during propagation Intervals in y and z in the local coordinate frames Fast access Difficult to describe non symmetric parts (big problem in TRD)

10. Geo modeler (0) Used to get information necessary for energy loss calculation and multiple scattering Local information - in each point density, radiation length, Z, A defined (mean excitation energy missing) Mean query time ~ 15  s Mean number of queries ~15 – between 2 ITS layer ~15 – between 2 TRD layers

11. Geo modeler (1) Two option considered 1. Propagate track up to material boundary defined by modeler – get local material parameters Time consuming - too many propagations 2. Calculate mean parameters between start and end point,, Faster (only one propagation), reusable in the case of parallel hypothesis (ITS), not big changes in the tracking

12. Implementation AliKalmanTrack::MeanMaterialBudget(D ouble_t *start, Double_t *end, Double_t *param) First test Track references in inner volume of the TPC – propagated to the vertex

13. TRD tracking FollowProlongatioBackG implemented Using mean material budget 14 steps Propagate to first plane Loop over TRD planes Propagate and update in the sensitive layer Propagate to the next plane Propagate to the outer volume of TRD

14. Energy loss estimate resolution Left side - old propagation Right side – new propagation

15. Relative Pt resolution Left side - old propagation Right side – new propagation

16. Relative Pt resolution Left side - old propagation Right side – new propagation

17. Pt pulls Left side - old propagation Right side – new propagation

18. Time pulls Left side - old propagation Right side – new propagation

19. Conclusion First results in TRD tracking Indication of improvements in the momentum and the time resolution Test with propagation to the vertex using AliExternalParameter and GeoMedeler – better vertex position resolution Better interface required – without user intervention

20. Conclusion Default access to the TGeoManager required Currently loaded by hand Better energy loss parameterization- options: 1. Mean Energy loss and multiple scattering calculation using TGeoManager 2. Tuning 1 free parameter -