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A New STAR Event Reconstruction Chain

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. STAR Experiment. Multi-purpose detector for heavy ion and p-p physics Multiple detector sub-systems.

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A New STAR Event Reconstruction Chain

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  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. STAR Experiment • Multi-purpose detector for heavy ion and p-p physics • Multiple detector sub-systems 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 < pt < 20+ GeV/c; ||<4. • Large range of physics analyses. • Very large data volume; e.g. from Run 4: • 15106 Au+Au events @ 62 GeV. • 94106 Au+Au events @ 200 GeV. • 230106 p+p events @ 200 GeV. • Raw data: 200 TBytes, DST: 40 TBytes. • Evolving detector configuration: TPC, FTPC, SVT, SSD, FTPC, EMC, … 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. 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 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. Claude A Pruneau, CHEP 2004

  7. Integrated Tracker Task Force (ITTF) • Members: Manuel Calderon1, Jerome Lauret1, Lee Barnby2, Camelia Mironov2, Ben Norman2, Maria Mora Corral3, Mike Miller4, Zbigniew Chajecki5, Claude Pruneau6, Andrew Rose6 1 Brookhaven National Laboratory, 2 Kent State University, 3 Max Planck Institut fur Physik, 4Yale 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. 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. 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). Claude A Pruneau, CHEP 2004

  10. Object Factory + Memory Management Model • Double Template Class : class VectorizedFactory<T1,T2> • 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. Claude A Pruneau, CHEP 2004

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

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

  13. Prior Estimate xo- Error covariancePo- Compute Kalman Gain Kk Find best matching hits Update estimate with measurement zk. Project ahead. (Eloss Correction) Update Error covariance. Kalman Tracking/Fitting Claude A Pruneau, CHEP 2004

  14. <> ()   <> (o () (o) pt pt Reconstruction Bias & Resolution Primary + ITTF RED TPT BLUE Claude A Pruneau, CHEP 2004

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

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

  22. Performance Verification d + Au @ 200 GeV. NFitPoint15, DCA ≤ 3 cm, |h| ≤1.00, pt 0.40 GeV/c, FitPtefrac  0.55, Zvert ≤ 100. J. E. Gonzalez Yield Previous - Black Balewski New - RED S. Salur N Yield Mass (GeV/c2) A Wetzler pt (GeV/c) pt (GeV/c) Claude A Pruneau, CHEP 2004

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

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

  25. Summary Claude A Pruneau, CHEP 2004

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

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