1. Forward Tracking in the ILD Detector
Robin Glattauer
LCWS11 ,

2. Forward Tracking Disks

3. Standalone track search for the FTDs (Forward Tracking Disks)
the goal
Standalone track search for the FTDs
(Forward Tracking Disks)

5. The Problem

6. The Solution

7. Methods
Cellular Automaton
Kalman Filter
Hopfield Neural Network

8. The Cellular Automaton

9. The Cellular Automaton

10. It's about rules

11. IP

12. cell ( segment)

13. state 0

18. Kalman Filter KalTest + KalDet + MarlinTrk
Quality Indicator: χ ² probability

21. The Hopfield Neural Network
Track ↔ Neuron
Goal: the global minimum

23. Once more for the FTDs

29. And now some reality

30. Background Inner 2 disks are pixel detectors How many bunch crossings?
100 BX * hit density ≈ 900 hits / pixel disk

31. Ghost hits
Outer 5 disks are strip detectors

32. At the moment Criteria Analysis tools
Step Analyser
Criteria Analyser
True Track Analyser
Jet Analyser
Adding flexibility (strategy pattern)

33. Thanks to Winfried Mitaroff Steve Aplin, Frank Gaede and Jan Engels
Rudi Frühwirth
And Jakob Lettenbichler (Belle 2)

34. Thank you!

35. Back Up

36. Future staggered / tilted petals Neural Network
Intermediate Region: TPC + FTD
Robustification (DAF, GSF)

37. Dependencies FTD drivers and gear Time stamps?
Number of integrated bunchcrossings

39. tracks will
Skip a layer
Connect directly to the IP

41. regions