Tracking Software Status Tracking Software Status Norman A. Graf for the tracking group ( prime architect: David Adams ) Software and Data Analysis Workshop Prague September 23, 1999

Introduction 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.

L3 CFT Tracking Link-and-Tree algorithm has been implemented which successfully finds tracks in the CFT. Can search in selected  region, or all CFT. Adjacent fibers (up to 3) are clustered. Search for tracks as circular arcs passing near the origin using axial fiber information. Matching stereo fiber hits are then found. A fast circle fit is performed in the x-y plane, along with a straight-line fit in s- z.

L3 CFT Tracking Tracking efficiencies and resolutions have been studied; clearly functions of event complexity. Efficiency versus Purity is clearly an issue, but efforts underway to quantify. Timing obviously a functon of minimum pT cut, but also dependent on samples used; currently under investigation.

L3 CFT Tracking tt +2MB Clusters... Links... Trees... Tracks... Done Done...D one

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.

L3 Tracking Plans Improve existing CFT algorithm.  Correct high-pT inefficiencies in r- .  Make r-z code more efficient. Incorporate CFT algorithm into the framework. Add extension capability from CFT to SMT. Provide multiple algorithms with varying speed and p T efficiencies. Use L3 unpacking code as it becomes available from subdetectors. Test, debug and optimize.

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

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.

Data Flow Following figure shows the flow of data from the Central Fiber Tracker through the global tracking system. Data is indicated within horizontal bars. Reconstructors which operate on or create Chunks are contained in packages indicated in ellipses. The GTR system is shown in red, the CFT system is shown as an example implementation and is in green.

Offline Tracking Status

Central Tracking Regions The Central Tracking Volume is divided into three regions of interest:

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.

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

Track Quality Metrics The quality of the reconstructed tracks is represented by the following quantities: Track χ 2 :  For the CFT, requiring 16 hits results in a track χ 2 with 11 d.o.f. (5 constraints). Probability to exceed χ 2 :  Produces a distribution flat between 0 and 1 if the values really are χ 2 distributed.

Track Fit χ 2

Track Quality Metrics Match χ 2 :  χ 2, i.e. ( fit-MC ) 2 /  2 fit, which should be distributed with 5 d.o.f. Parameter Significances:  Normalized residuals, ( fit-MC )/ , giving gaussian distributions with mean of 0 and width of 1.

Track Match χ 2

Central Region Tracking Tests Start with sample of high momentum tracks in full CFT fiducial region.  z=dca=0, -1<tan(λ)<1, 0<φ<2 π  50GeV p T : find 1980/1991 events (99.4%)  3GeV p T : find 1976/2000 events (98.8%)  1GeV p T : find 1874/2000 events (93.7%)

Central Region Tracking Tests Multimuon sample in CFT fiducial volume.  0.5 GeV< |p T | < 10 GeV  dca=0, z gaussian σ=28cm.  π/4 < Θ < 3π/4  0<φ<2 π  4856/4959 found (98%) Tracking done only in CFT. Adding SMT to tracking in multi-track events causes slight inefficiency and poorly understood track and match χ 2.

Central Region Tracking Tests Analyze Z  μμ sample 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 and 2 additional minimum bias events to study efficiencies and resolutions as a function of hit density.

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

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 p T 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.

Overlap Tracking Work started to develop appropriate paths. Tactic is to use the equivalent of the current CFT Path and remove successive outer layers. 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.

Muon Tracking The trf interface for the muon detector and muon hits has been coded. Modifications to the gtr system made. WAMUS internally generated events :  ~100% efficiency for 10 hit planes.  ~55% overall acceptance*efficiency Plan to:  Analyze GEANT data.  Integrate FAMUS.  Use field map (TIM package).

Muon Tracking Results

Material Interaction Effects of Multiple Scattering and energy loss are handled via Interactors. 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.

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.

Status 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.

Short Term Goals Add and integrate central and forward. Add and integrate muon system. Improve performance for complicated events. Optimize fitting to account for material. Account for non-uniform magnetic fields. Produce tracks with optimal fits everywhere. Add Monte Carlo Fitter. Develop and release L3 filters.

Tracking on the Web 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.

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. Have not yet demonstrated capability to reconstruct “real” events in reasonable time with requisite efficiency.

Conclusions Welcome contributions from non- coders:  Systematically investigate efficiencies, resolutions and timing.  Generate “Physics” samples and analyze standard ntuples.  Contribute to path algorithms. Many of the building blocks are in place, but much more work still needs to be done to have a fully working system. Optimize, optimize, optimize.