1. A New STAR Event Reconstruction Chain Claude A. Pruneau, M. Calderon, B. Hippolyte, J. Lauret, and A. Rose. STAR Collaboration Physics and Astronomy Department Wayne State University

2. Claude A Pruneau, CHEP 2004-2- STAR Experiment Multi-purpose detector for heavy ion and p-p physics Multiple detector sub-systems

3. Claude A Pruneau, CHEP 2004-3- Challenges Colliding systems: p+p to Au+Au collisions at 20 – 200 GeV/u. Large particle production –E.g. Few 10s of tracks (and pile-up) in pp to ~6000 tracks in central Au+Au collisions, with up to 50 hits/track in the SSD, SVT, TPC detectors. Large kinematic range of interests/detection: 0.15 < p t < 20+ GeV/c; |  |<4. Large range of physics analyses. Very large data volume; e.g. from Run 4: –15  10 6 Au+Au events @ 62 GeV. –94  10 6 Au+Au events @ 200 GeV. –230  10 6 p+p events @ 200 GeV. –Raw data: 200 TBytes,  DST: 40 TBytes. Evolving detector configuration: TPC, FTPC, SVT, SSD, FTPC, EMC, …

4. Claude A Pruneau, CHEP 2004-4- Data Analysis Challenge Analysis proceeds (roughly) in two passes: –Event Reconstruction - ideally one pass @ central facility –End-user physics analysis. Old reconstruction software –Separate track finding (TPT) and Kalman Fit (EGR) –Appropriate for TPC analysis. –Deployment of new detectors (e.g. SVT, SSD) required new tracking modules in a patch work fashion. Tracking time increases linearly with number of detectors rather than hits. –Mix of FORTRAN, C, C++ codes difficult to maintain. –Limited documentation –Developers no longer collaboration members –CPU Time/central event : 115 s.

5. Claude A Pruneau, CHEP 2004-5- Outline Need for a new reconstruction chain  New tracker –Description –Performance New Reconstruction chain –Summary of changes –Performance verification Summary

6. Claude A Pruneau, CHEP 2004-6- Goals of New Tracker Develop/Deploy an integrated event reconstruction software/environment. –Integrate track finding and Kalman fitting in one package. –Enable integration of existing and new detectors in a single analysis framework. Develop object models and algorithms that enable flexibility and growth. –Detector geometry representation –Hit and track representations. Match or Improve track reconstruction performance –Reconstruction efficiency –Resolution –Kinematic range/acceptance Eliminate legacy Fortran code. Code Robustness –Memory leak free. –Proper handling of unforeseen exceptions. –Reduce memory footprint. Reduce reconstruction time. Provide abundant documentation.

7. Claude A Pruneau, CHEP 2004-7- Integrated Tracker Task Force (ITTF) Members: Manuel Calderon 1, Jerome Lauret 1, Lee Barnby 2, Camelia Mironov 2, Ben Norman 2, Maria Mora Corral 3, Mike Miller 4, Zbigniew Chajecki 5, Claude Pruneau 6, Andrew Rose 6 1 Brookhaven National Laboratory, 2 Kent State University, 3 Max Planck Institut fur Physik, 4 Yale University, 5 Warsaw University of Technology, 6 Wayne State University. Formed : November 2000. –Mandate: Design/Develop/Deploy a new, integrated tracker for STAR. Design/Development 2001-2002. Design Review : Sept 2002.

8. Claude A Pruneau, CHEP 2004-8- Tracker Design Considerations Language/Portability/Minimal dependencies –ANSI C++ & Standard Template Libraries (STL). Modularity and Expandability –Define/Use generic interfaces for key components –Plug-and-play Components and Algorithms. Algorithms and Object Models –Non STAR detector specific. –Simple Geometry Model (Detector, Shape, Placement). –Elementary Constructs (Track, Hit, etc). –Special Containers when appropriate – Detector Geometry, Hits –Generic Algorithm/Interface Track finder and seed finder. MCS, E-loss, dE/dx Calculations Hit error parameterizations –Templated Object Factory and Memory Management. –Abstract Input/Control Parameter Representation.

9. Claude A Pruneau, CHEP 2004-9- Some Implementation Specifics Detector Geometry Representation and Traversal –Generic basic detector class. (Placement, shape representation, materials, hit error parameterization, energy loss calculation). –Detector groups (TPC, SVT, …) and builders to instantiate & assemble geometry. –Detector tree (e.g. sorted radially, azimuthally) for traversal Tracking algorithms (non detector specific): –Abstract interface notion of track finding. –Concrete classes for track seed finding & track finding/fitting. Hits: –Interface provides for access in local (detector) or global coordinates –Storage in tree/map for fast retrieval Hit loaders –Abstract interface define notion of hit loader (Generic). –Use one loader per hit bearing detector group (Star specific). Output to persistent STAR data model (StEvent).

10. Claude A Pruneau, CHEP 2004-10- Object Factory + Memory Management Model Double Template Class : class VectorizedFactory –First template (T1): Class to actually instantiate. –Second template (T2): Base class served by the factory. –Use STL vector class for storage. –Memory allocation and garbage collection done in one place –Nominal set of object instantiated/destroyed once at startup/finish time. –Object set expanded in large blocks as needed. Pros: –Avoid repeated calls to "new" and "delete" for each event analysis. –Enables plug and play of new components. –Enables run time choice of classes to instantiate and use. –Simplified user code – no memory management. –No memory leaks. –Promotes code speed, simplicity, and robustness. Caveat: –Reused objects must be properly reset and initialized –Large footprint.

11. Claude A Pruneau, CHEP 2004-11- Tracking Algorithm Kalman Filter/Finder Local Helix Model Local (detector) coordinates Detector geometry integrated –Multiple scattering, Energy Losses Outside-in pass Inside-out pass Seed Collision Vertex r B Find seed Outside-in Find/Fit Pass Extend Track To Vertex Extend outward? Filter/Save track Find Vertex Reset Track Container Load Hits Inside-out Find/Fit Pass Filter/Save track Done

12. Claude A Pruneau, CHEP 2004-12- B Track model: Local helix x Tracking Algorithm: Kalman Filter - Local detector frame. (x o,y o ) (y, z) y R Prediction Update

13. Claude A Pruneau, CHEP 2004-13- Kalman Tracking/Fitting Compute Kalman Gain K k Prior Estimate x o - Error covariance P o - Update estimate with measurement z k. Update Error covariance. Project ahead. (E loss Correction) Find best matching hits

14. Claude A Pruneau, CHEP 2004-14-        ptpt    ptpt Primary  + ITTF RED TPT BLUE Reconstruction Bias & Resolution

15. Claude A Pruneau, CHEP 2004-15-  p t /p t >  p t /p t ) p(GeV/c) Reconstruction Bias & Resolution Primary  + ITTF RED TPT BLUE  p t /p t ) p(GeV/c) Occupancy RED - Low BLUE - High

16. Claude A Pruneau, CHEP 2004-16- Efficiencies vs p t Cuts : N MC Hit > 10; -1<  <1; DCA<3 cm p t (GeV/c) ITTF TPT Low Multiplicity High Multiplicity   p t (GeV/c)

17. Claude A Pruneau, CHEP 2004-17- ITTF Review New Tracker Performance Review –STAR Internal Panel Review - Aug 2003. –Found New Tracker to have equivalent or better performance –Recommended adoption of the new software for integration in STAR data reconstruction production. Official Adoption of the new tracker by STAR –Aug 2003 Collaboration Meeting.

18. Claude A Pruneau, CHEP 2004-18- New Reconstruction Chain Goals: –Integrate the new (ITTF) tracker in the STAR reconstruction chain. –Eliminate obsolete/legacy code; e.g. tables. –Use StEvent as object model both for processing and persistency. Integration/Development Team –J. Balewski, M. Calderon, L. Didenko, Y. Fisyak, B. Hippolyte, J. Lauret, M. Oldenburg, C. Pruneau, A. Rose. Duration: ~ 7 months.

19. Claude A Pruneau, CHEP 2004-19- Changes and Improvements… ITTF Track Reconstruction (ITTF Team) Generic Vertex Maker (L. Barnby, J. Balewski, T. Ulrich) –Façade/Interface deployed to enable multiple vertex finding algorithms. –New Maker based on Minuit TPC cluster finder (DAQ Team: J. Landgraf, T. Ljubicic ) –Fast finder, re-written from scratch in C++. Kink finder (C. Mironov, S. Margetis) –K  reconstruction –C++ re-write of FORTRAN code. TPC Hit Calibrations (J. Lauret) –Coordinate transformation, calibration adjustment) –Formerly entangled with old tracker TPT, now a new module “StTpcHitMover”. Addition of chain options for increased flexibility (J. Lauret, Y. Fisyak, M. Calderon) –Module ordering no longer static, but predicated on components included in the Chain.

20. Claude A Pruneau, CHEP 2004-20- Changes and Improvements… SVT Code –Modified to use StEvent (the persistent data model) or tables. FTPC Code –Modified to use StEvent. Trigger data detectors –Formerly in StEventMaker, now part of a compendium maker (“foure-tout”) Performance Evaluation Codes (J. Lauret, Y. Fisyak, M. Calderon) –Included propagation Geant particle ID in hit/track reconstruction to dominant contributor evaluation (key to dominant, number of hits, avg quality). –Generic track-track comparison maker was developed. Integration of SSD. R&D for a new pixel detector

21. Claude A Pruneau, CHEP 2004-21- Performance Verification Goals –Verify code integrity - produce sensible numbers –Verify physics performance Tester team –Representatives from each STAR Physics working group –Event structure - Aya Ishihara –Spin - Jan Balewski –HBT - Zbigniew Chajecki –Heavy Flavor - Alex Suaide –EbyE - Paul Sorensen –Spectra - Johan E. Gonzalez, Alexander Wetzler –High-pT - Marco van Leeuwen –Strangeness - Sevil Salur. Camelia Mironov, Ying Guo Duration: June 16, 04 to September 22, 04. Hard work! –Data samples reproduced 14 times. –Multiple (minor) bug fixes.

22. Claude A Pruneau, CHEP 2004-22- Performance Verification N Balewski d + Au @ 200 GeV. N FitPoint  15, DCA ≤ 3 cm, |  ≤  1.00, p t  0.40 GeV/c, FitPtefrac  0.55, Z vert ≤ 100. p t (GeV/c) Yield p t (GeV/c) Mass (GeV/c 2 ) A Wetzler Previous - Black New - RED S. Salur J. E. Gonzalez

23. Claude A Pruneau, CHEP 2004-23- Performance Review - HBT Analysis - Track Merging/Splitting d +Au data Previous New Zbigniew Chajecki CF Average Separation (cm) Merging Splitting Zbigniew Chajecki

24. Claude A Pruneau, CHEP 2004-24- Previous New BETTER!!! Zbigniew Chajecki

25. Claude A Pruneau, CHEP 2004-25- Summary ITTF Tracker Completed! Integration in Reconstruction Chain Completed! Performance Comparison/Validation Completed! Production of Run 4 data Started!

26. Claude A Pruneau, CHEP 2004-26- Integration of new detectors Work in progress (K. Schweda, et al.) Addition of SSD and R&D for a new pixel based  vertex detector

27. Claude A Pruneau, CHEP 2004-27- Epilogue ITTF originally conceived as a 2 years effort –To be conducted by a handful of people. STAR is a successful on-going experiment. –Taking data, and publishing physics. Code development + deployment –Took quite a bit longer than anticipated. –Required participation of very many people to establish code integrity, and for performance evaluation.

28. Claude A Pruneau, CHEP 2004-28- Worth the effort –Powerful, Flexible, Integrated Tracker Robust - Memory leak free, Good exception handling. Faster. Allows evolution –Proven Performance Performance comparable or better than that of old tracker. All STAR PWGs signed-up on its value based on performance achievements in a wide spectra of analyses and level of details. –Easy Maintainability. –Documented. –Ready for the Future decade!!!! On time for STAR R&D developments