1. Integrated Tracking/Clustering Algorithm+
Supporting Tools & Infrastructure
Dmitry Onoprienko
Kansas State University
2008 Linear Collider Workshop
Chicago, November 2008

2. Hit Processing Framework & Algorithms
Talk overview:
org.lcsim - LCIO
Tracking
Virtual Segmentation
Integrated
Tracking/Clustering
Tracker Object Model
Hit Processing Framework & Algorithms
PFA

3. LCIO based persistency
Object model
MCTruth
MCTruthDriver
Simulation output
SimTrackerHit
LCIO based persistency
True pulse height in each channel
IRawTrackerData
ITrackerHit extends ITrackerObject :
List<? extends ITrackerHit> getParentHits()
List<? extends ITrackerHit> getClusters()
List<? extends ITrackerPulse> getPulses()
IRefFrame getRefFrame()
Type getType()
Hep3Vector getDimensions();
double getdEdx()
double getTime()
Hep3Vector getLocalPosition()
Hep3Vecror getLocalErrors()
Hep3Vector getPosition(IRefFrame referenceFrame)
SymmetricMatrix getCovMatrix(IRefFrame referenceFrame)
DAQ output
IRawTrackerHit
Calibrated signal in each channel
ITrackerPulse
Cluster: group of pulses that cannot be unambiguously
separated
+ measurement
ITrackerHit
ITrackerHit
Derived measurement
ITrackerHit
ITrackerHit

4. Virtual segmentation package
Applied on top of arbitrary simulation geometry
org.lcsim Geometry System
Extendable
Library of Segmenters +
machinery for chaining
SegmentationManager
Segmenter
Defines how sensitive volumes are tiled with Sensors.
uses
Hit processing framework
creates
creates
Extendable Library of SensorTypes
Hexagon
Rectangle
VSRawTrackerData
Sensor
WedgeSideParallel
SensorType
VSRawTrackerHit
Cylinder
Defines geometry and other parameters of a Sensor, how it is tiled with channels, what Type of hits it produces.
Polygon
VSTrackerPulse …
VSTrackerHit

5. Virtual segmentation – recent improvements
Geometry services
SimTrackerHit 
multiple virtual Sensors
Expanded library of SensorTypes
Automatic “trivial” Segmenter for any
planar geometry
Automated stereo partner lookup
Integration with event display

6. Hit Processing Extendable library of algorithms.
SimTrackerHit
ChargeCollectionDriver
ChargeCollector
MCTruth
MCTruthDriver
IRawTrackerData
MergeDriver
NoiseGenerator
… and other tools
DigitizationDriver
Digitizer
IRawTrackerHit
Extendable library of algorithms.
Includes both fast simplified algorithms (smearing, etc.) and full digitization (Tim Nelson, Nick Sinev)
Decoder
CalibrationDriver
Calibrator
ITrackerPulse
Shortcut drivers available
Clusterer
ClusteringDriver
HitMaker
ITrackerHit
StereoHitMaker
StereoDriver
Data exchange format:
TrackerHitMap<K extends Identifiable, V>
ITrackerHit

7. ITC package - Goals Modular, flexible, easily extendable 
Evolved from the original calorimeter assisted tracking package
Calorimeter-seeded track finder (essential for Vs, kinked tracks, etc.)
Aid “standard” track finder
Track – cluster association
High purity initial clustering with topological linking  starting point for PFA
Modular, flexible, easily extendable 
Designed to be configured for a particular use scenario

8. ITC – Basic algorithm Run “standard” track finder
Cluster hits in each calorimeter layer into
Dots (MIP trace) and Beads
Seed first Rosaries from tracks
Thread created Rosaries
For each Calorimeter Layer :
Create new Rosaries from unattached Dots
Assign quality ratings to Rosaries, cut
Remove duplicate parts
For each Rosary :
Propagate trajectory to the next layer
Try to attach Dot (may branch)
If unsuccessful, try to attach Bead
If unsuccessful,
If this is a single Dot Rosary with no attached track, try to attach Dot based on proximity
Otherwise, attach Crack
Check for Rosary termination condition
If first termination, reverse direction
If not terminated, update trajectory
Rosary – chain of clusters, possibly with a track
attached on one end.
If entering tracker, and no track is attached to this Rosary
Create track seed
Extend into tracker, picking up hits  new track(s)
See if there is orphan track nearby – if yes, try to stitch.

9. Interface to geometry, propagation
(Mostly) detector independent implementation
IGeometry interface:
List<CalModule> getModules()
CalLayer getLayer(CalorimeterHit hit)
CalModule getModule(CalorimeterHit hit)
List<CalLayer> findNeighbors(CalLayer layer, Trajectory trajectory)
void propagateToLayer(CalLayer targetLayer, Trajectory trajectory)
CalLayer propagateToNextLayer(Trajectory trajectory, CalLayer currentLayer)
CalLayer propagateToNextLayer(Trajectory trajectory)
…………………………………………………………………..
Calorimeter
CalModule
CalLayer
Default implementation available.
Custom implementations can be provided to improve performance (adapter available).

10. Calorimeter Assisted Tracking – Efficiency
Preliminary
SiD02 detector, SM 500 GeV
Run seedtracker (by Rich Partridge), than ITC
Looking at non-prompt tracks (origin outside R = 1 cm, Z = 1 cm cylinder)
Reconstructable MCParticle: hits in at least 3 tracker layers, Pt > 200 MeV

11. ITC Algorithm - Status Next… Virtual segmentation – released
Ongoing minor improvements, no changes to API
Object model – released
Minor changes to persistency mechanism expected
Hope to align with “standard” LCIO interfaces
Hit processing framework & algorithms – released
Algorithms added as needed
Integrated Tracking/Clustering package – functional, plan to release within a month
Expect to switch to better fitter
Next…
Calorimeter assisted tracking – performance tune-up and characterization
Use ITC algorithm in PFA