Tracking Software Status Norman A. Graf Software and Data Analysis Workshop Prague

1. Tracking Software Status Norman A. Graf Software and Data Analysis Workshop Prague September 23, 1999

2. Introduction • The goal of global tracking is to find and fit the tracks in a D0 Event using event data from one or more of the D0 subdetectors. • The input data Event is a collection of clusters from each subdetector. • The output is a collection of global tracks where each track contains a list of clusters and one or more kinematic fits based on these clusters. • Group is also responsible for overseeing algorithms for the Level 3 Trigger.

3. L3 CFT Tracking • Algorithms have been developed which successful find tracks in CFT. • Work ongoing to optimize and incorporate into D0 framework.

4. L3 Tracking • The first version of the tracking framework has been completed. • l3ftrack_base Base classes. • l3ftrack_smt SMT extensions • l3ftrack_mc MC extensions • SMT tracking tool exists. • Reconstructs tracks within a region or in the entire detector. • Uses algorithm similar to CFT link-and-tree. • Reasonably fast and efficient. • MC Tracking tool exists. • Retrieves tracks from the McTrackChunk for the entire detector or a region. • Used for efficiency and resolution studies.

5. L3 Tracking Plans • Incorporate existing CFT algorithm into framework. • Add extension capability to CFT and SMT subdetectors. • Provide multiple algorithms with varying speed and pT efficiencies. • Provide global tracking capability. • Not by subdetector. • Use L3 unpacking code as it becomes available from subdetectors. • Test and optimize.

6. TRF++ • TRF++ is an extensible object-oriented framework for finding and fitting tracks in particle physics detectors. • Written in C++. • Provides extensive base class libraries. • Modular, with acyclic package dependencies. • Track-finding strategy based on a road-following algorithm. • Track-fitting based on a Kalman-filter algorithm

7. Detector Surfaces • Implemented TRF++ surfaces:

8. TRF++ System

9. Global Tracking System • The global tracking system (GTR) defines the following event data: • GTrackChunk: holds reconstructed tracks. • McTrackChunk: holds Monte Carlo tracks. • and the following packages: • GtrFind: finds tracks • GtrMcFill: generates MC tracks. • GtrClusterSim: generates MC subdetector clusters. • GtrTuple: matches found and MC tracks and generates analysis ntuple.

10. Global System

11. Data Flow • Following figure shows the flow of data from the Central Fiber Tracker through the global tracking system. • Reconstructors which operate on or create Chunks are contained in packages indicated in ellipses.

12. Offline Tracking Status WAMUS FAMUS Calorimeter Preshower Overlap Central Forward

13. Central Tracking Regions • The Central Tracking Volume is divided into three regions of interest: • Central: Full CFT fiducial volume. • Forward: SMT-only. • Overlap: Transition region. Overlap Central Forward

14. Central Region • Tracking in Central Region has been available for quite some time. Path requires all 16 CFT layers to be hit. • Internally simulated tracks are found with 100% efficiency. • Effects of MS are correctly handled in the thin-scatterer approximation. • Tracking efficiency for GEANT simulated tracks had been less than 100%, even for high momentum single muons. • Problem was in CFT digitization. • Work is starting to optimize the current tracking, and also to develop paths which allow for missing layers.

15. Central Region Tracking Tests • Start with sample of high momentum tracks in full CFT fiducial region. • 50GeV pT • z=dca=0, -1<tan(λ)<1, 0<φ<2 π • Reconstruction efficiency • 1979/1991 events (99.40%) • Good track fit χ2 . • Good track match χ2 . • Work starting to develop additional clustering algorithms. • Current algorithm is simple Nearest-Neighbor.

16. Track χ2

17. Parameter Significances

18. Central Region Tracking Tests • Analyze sample Z  μμ with underlying event. • Use Isajet events with underlying event and require both muons to pass through the CFT fiducial volume. • 52/100 events pass cuts • 104 muons with pt>20GeV • 103/104 muons found. • Generating larger samples of Z  μμ with 0,1,2 additional minimum bias events to study efficiencies and resolutions as a function of hit density.

19. Forward Tracking • Tracks pass through SMT Barrels and some portion of F and H disks. • Start tracks with hits in H or F disks. • Propagate inwards:

20. Forward Tracks • Require tracks to have at least 4 hits. Most hits are 2D, therefore 3 hits constrain the track parameters. • Only one miss allowed in track. • Constrain track to come from beam axis and apply minimum pT cut to improve performance. • Prune track list at each layer to remove tracks with hits in common. • Studies conducted with GEANT samples of 10GeV muons.

21. Forward Tracking • Preliminary Results: Tracks/event eff. Misreco* s/event 1 0.971 0.010 0.71 2 0.911 0.012 1.08 10 0.931 0.048 7.3 20 0.906 0.06 24.1 • Match χ2 points to possible problems with SMT cluster uncertainties. • Cluster residuals have been intensively studied and appear to be understood. • Studies are underway to understand track quality and improve efficiencies and timing. • Real “Physics” events not yet confronted.

22. Overlap Tracking • Work just getting underway to develop paths appropriate to this topology. • Tactic is to use the equivalent of the current CFT Path and remove successive outer layers. • Make these paths orthogonal to existing path by requiring z of stereo hits to lie appropriately close to edge. • Object-reader capabilities of GTR system allow paths to be defined in external file. No coding required! • First tracks have been found in single muon GEANT files.

23. Muon Tracking • Code implementing the trf interface for the muon detector and muon hits has been developed. • Modifications to the gtr system made. • Tracking uses uniform toroid field. • Studies of the WAMUS using internally generated events have started. • ~100% efficiency for 10 hit planes. • ~55% overall acceptance*efficiency • Plan to: • Analyze GEANT data. • Integrate FAMUS. • Use field map (TIM package).

24. Muon Tracking Results

25. Material Interaction • Effects of Multiple Scattering and energy loss are handled via Interactors. • Code for Thin Surface Multiple Scattering on cylindrical and planar (xy and z) surfaces is released. • TRF interacting detectors currently account for MS on measurement surfaces and some passive elements ( beampipe, SMT support, solenoid) • Energy loss code written, being incorporated into the interacting detectors. • All parameters under RCP control.

26. Interacting Propagators • Current Propagators simply transport tracks from one surface to another. Interactions (MS & dE/dx) are handled by the surfaces. • Work is underway to develop Propagators which allow tracks to be arbitrarily transported, and have the track modified by any surfaces it may have crossed in the interval. • D0Propagator exists as well as CFTPropagator implementation. • Work proceeding for other subdetectors.

27. Status • The D0 global tracking software system is composed of a number of packages which define and implement the interface between the individual detector components (e.g. CFT) and the actual track finding and fitting software (TRF++). • The system defines and manages the interface to global tracks, which are composed of a list of constituent clusters and a list of kinematic fits. • MC tracks are also defined and utilities exist to facilitate the association to and comparison between simulated and found tracks.

28. Global Visualization • VRML scene of single muon track in Central Fiber Tracker showing hit axial and stereo fibers.

29. Recent Activities Agenda of Sept. 15 Meeting • David Adams - Status of t00.59.00 • David Adams - New Propagator interface • Bruce Knuteson - CFT tracking • Slava Kulik - Forward tracking • Anna Goussiou - Overlap tracking • Daniel Mihalcea - Energy loss • Valentin Kuznetsov - Interacting propagator • John Krane - Propagator verification • Maria Roco - MC track finder • Daria Zieminska - Muon system tracking • Daniel Whiteson - L3 tracking trigger • Norman Graf - CFT cluster status • Norman Graf - GTR refitter status

30. Tracking on the Web • The global tracking home page can be found at: http://www.bonner.rice.edu/adams/d0/gtr/ • User’s Guide • How to generate, find and analyze. • Software • Links to GTR, TRF and subdetectors. • Projects • What is (and isn’t) being done. • Results • Canonical Plots. • Project Status • Milestones and schedules. • Meetings • Agendas and Proceedings.

31. Conclusions • The tracking software continues to improve both in quality and performance. • Doing more and doing it better. • More people are (slowly) becoming involved. • Just starting to seamlessly incorporate subdetectors. • Welcome contributions from non-coders: • Systematically investigate efficiencies, resolutions and timing. • Generate “Physics” samples and analyze standard ntuples. • Contribute to path algorithms. • Much more work still needs to be done to optimize, optimize, optimize.

32. Spares

33. D0 Track Model • For a charged particle in a magnetic field, six parameters are required to specify the track. • Tracks are always defined at a surface, which provides one constraint. • For a cylindrical detector, e.g. • r : radius of cylinder. • F : position polar angle. • z : position along beam line. • a : F dir- F pos . • l : dip angle. • q/pT : curvature.

34. D0 Cylindrical Track Parameters

35. Subdetector Interface I • Detector • Subdetector is responsible for interacting with geometry system and constructing the corresponding TRF++ layers (composed of surfaces). • Detector Filler • Responsible for extracting data, converting into TRF++ clusters, registering the association and assigning the TRF++ clusters to the layer. • Generic cluster access • Reconstructed tracks include pointers back to generic constituent clusters. Subdetectors are responsible for reconstituting the detector clusters.

36. Subdetector Interface II • Path Builder • Each subdetector must provide class or function which extends an existing path to carry out track finding. (Attempt to move some of the path building down from global tracking to the subdetector level.) • Cluster Simulator • Extracts MC tracks and uses them to internally generate clusters. This reconstructor replaces full propagation, digitization and clustering ( GEANT, for example ) with a quick simulation.

37. CFT Digitization • Internal simulation of hits in CFT results in ~100% track finding efficiency for single tracks. • Lower efficiency in GEANT files suspected to arise at least in part from CFT digitization. • Other sources might be dE/dx, non-uniform field, showering, etc. • Identified and resolved problems: • Reviewed geometry code which intersects SFTSegment with a fiber; algorithm and code OK. • Fixed defect in code which selects which fibers to query.

38. CFT Digitization • Problem due to phi-wrap in V stereo layers. • Fixes are in cvs, and tagged for production MC, but not part of release. • Raise track-finding efficiency from ~97% to >99% for high pT single muons. • Remaining inefficiency under investigation: • Low-energy fibers displace cluster center? • Showering or decays of particles?

39. CFT Clustering Tests • Digitize GEANT hits only for primary tracks, no delta rays, etc. This replicates internal simulation, producing only singlet and doublet clusters.

40. Central Region Tracking Tests • Analyze multimuon sample in CFT fiducial volume. • 1GeV< |pT | < 50 GeV • z=dca=0 • -1<tan(λ)<1 • 0<φ<2 π • 1116/1137 found (98.15%) • Tracking done only in CFT for this study; adding SMT to tracking does not lose any tracks, only improves fit. • Matching shown both to original track at production vertex and MC track state at inner CFT layer. • Differences indicate effects of multiple scattering and dE/dx.

41. Track χ2

42. Parameter Significances

43. GTR Utilities • Simplified internal simulation of detector response is available for testing and verification. • Ntuple generation is implemented. • Timing and performance utilities are being implemented. • Visualization tools are being developed.

44. D0 Event Data • Data accumulated by the D0 detector associated with one triggered crossing is called and Event. • Cohesive units of data ( e.g. unpacked data from a single subdetector) are grouped together into Chunks. • Framework packages interact with the Event by extracting necessary input Chunks, processing the data, the creating and inserting new Chunks into the Event. • Chunks are immutable and define the quanta of persistence.

45. Physical Structure • We follow the ideas and terminology of Lakos • J. Lakos “Large Scale C++ Software Design,” Addison-Wesley (1996). • A component is made up of: • header file (MyClass.hpp). • Source implementation (MyClass.cpp). • Test file (MyClass_t.cpp). • A component typically contains one class and its associated free functions. • A package is a collection of components. • Components and packages have acyclic dependencies. • Packages which serve a common global purpose are systems.