CARF

1. CARF an Analysis&ReconstructionFramework for CMS Vincenzo Innocente CERN/EP/CMC

2. CARF Development Philosophy • Tailored to CMS analysis and reconstruction • Serves present ORCA applications • priorities driven development • backward compatibility, legacy code and data! • Bottom-up (concreteabstract) development in synergy with other sub-systems • It is also a prototype of 2005 software • offers more than one solution to a single problem Vincenzo Innocente CARF Fundamentals

3. CARF layered Structure Core mechanisms and “data structures” Generic Application G3 TestBeam H2 T9/X5 Raw Data Raw Data Raw Data Generic Clients Vincenzo Innocente CARF Fundamentals

4. Framework Basic Dynamics • No central ordering of actions, no explicit control of data flow: only implicit dependencies • External dependencies managed through an Event Driven Notification to “subscribers” • Internal dependencies through an Action on Demand mechanism Vincenzo Innocente CARF Fundamentals

5. Framework Main Services • Define the events to be dispatched and links them to the their actual source • Allow the selection among available resources (user plug-in’s) • Manage the “not yet removed” sequential components Vincenzo Innocente CARF Fundamentals

6. Framework Ancillary Services • User Interface • Error Report (Exception management) • Logging facilities • Timing facility (statistics gathering) • Utility library • Notably Objy utilities, wrappers and generic persistent capable classes Vincenzo Innocente CARF Fundamentals

7. Framework middle layer • A CARF Application is characterized by the events it dispatches • Implementation of generic clients to specific services (events) • simplified API • uniform detailed design • uniform use of ancillary services • Requires synergy with detectors’ sub-systems Vincenzo Innocente CARF Fundamentals

8. Use Cases L1 Trigger Simulation Track Reconstruction “Physics” reconstruction

9. L1 Trigger Simulation detectors Front-end trigger logic Local trigger Global trigger Final trigger decision Vincenzo Innocente CARF Fundamentals

10. L1 Trigger Simulation • Accurate simulation of real electronics • In the real experiment only “final decision data” are propagated forward • Also required • Monitoring of single trigger units • Comparison of L1 trigger w.r.t. full reconstruction • ability to simulate just a part of the system • “save” computing intensive intermediate results Vincenzo Innocente CARF Fundamentals

11. Track Reconstruction For each “detector element” there are local measurements of trajectory state-vector (just position or more complex) Local measurements are affected by the detector element state (calibrations, alignments) Pattern recognition “navigates” in the detector to associate local measurements into a track Vincenzo Innocente CARF Fundamentals

12. “Physics” reconstruction • 4-vector-like objects are built out of trajectories and localized energy deposits • A wide range of PID, jet, vertex etc algorithms can be applied to produce others 4-vector-like objects • Access to the “original” detector data maybe required Vincenzo Innocente CARF Fundamentals

13. Reconstruction Sources Vincenzo Innocente CARF Fundamentals

14. Reconstruction Scenario • Reproduce “Detector Status” at the moment of the interaction: • front-end electronics signals (digis) • calibrations • alignments • Perform local reconstruction as a continuation of the front-end data reduction until objects “detachable” from the detectors are not obtained • Use these objects to perform physics reconstruction and analysis Vincenzo Innocente CARF Fundamentals

15. Components • Reconstruction Algorithms • Event Objects • Other services (detector objects, parameters, etc) • Legacy not-OO data (GEANT3) Vincenzo Innocente CARF Fundamentals

16. CARF Fundamentals(inside the black box) Detector Components Event Driven Notification Action on Demand

17. Detector Components Sim Hit Loader Local Geometry Load simulated hits from MC Generates Digis from SimHits (or loads them from db) Global Geometry Digitizer Detector Element Time Dependent Parameters Reconstruct measured trajectory state-vector from Digis Reconstructor Vincenzo Innocente CARF Fundamentals

18. Event Driven Notification Dispatcher Obs1 Obs2 Obs3 Obs4 Observers Vincenzo Innocente CARF Fundamentals

19. Active and Lazy Observers Dispatcher Lazy Obs2 Lazy Obs2 obsolete Lazy Obs2 uptodate Obs Lazy Obs1 Lazy Obs1 obsolete Lazy Obs1 uptodate Vincenzo Innocente CARF Fundamentals

20. Action “on Demand” Rec Hits Rec Hits Rec Hits Detector Element Hits Event Rec T1 T1 T2 Rec T2 Analysis Vincenzo Innocente CARF Fundamentals

21. “Events” currently dispatched Start Xing G3 Geom Ready to build new G3 simulated event SimPileUp New pile-up event ready in Zebra memory SetUp SimTrigger New trigger event ready in Zebra memory SetUp Observers are Objects which depend on geometry G3Event New event “ready” to be analyzed Vincenzo Innocente CARF Fundamentals

22. “RecObj” Object Model Vincenzo Innocente CARF Fundamentals

23. Object identification • A Detector object collection is identified by: • object type (or super-type) • detector element it belongs to • implicitly belongs to the “current crossing” • Required the detector to be “in place” and “operational” Vincenzo Innocente CARF Fundamentals

24. Object identification • A RecObj collection is identified by: • object type (or super-type) • name of the Reconstructor (same as RecUnit) • event it belongs to • Does not require the RecUnit to be in place or operational Vincenzo Innocente CARF Fundamentals