1 / 20

Material budget, energy losses and multiple scattering

This study focuses on improving particle tracking in detectors by optimizing energy loss correction and multiple scattering. It explores the impacts of material budget, energy losses, and multiple scattering on momentum resolution for various particles. The research delves into energy loss mechanisms, Bethe Bloch equations, and reconstruction methods. The implementation details an approach using Geo Modeler for energy loss calculation and provides results on the enhancement of momentum and time resolution in tracking. The study concludes with suggestions for better interface and energy loss parameterization.

dgibbs
Download Presentation

Material budget, energy losses and multiple scattering

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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) • b -particle velocity • r - material density • Z - atomic number of absorber • A – mass number of absorber • I – mean excitation energy • d – density effect correction factor – material dependent and b dependent

  5. Energy losses (Reconstruction) • b - particle velocity • r - 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) • b -particle velocity • r - 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 ms • 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 • <density>, <density*Z/A>, <radiation length> • Faster (only one propagation), reusable in the case of parallel hypothesis (ITS), not big changes in the tracking

  12. Implementation • AliKalmanTrack::MeanMaterialBudget(Double_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 -

More Related