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Sebastian Fleischmann , Bergische Universität Wuppertal, Germany

new. f a st atlas t R a ck s imulation. Sebastian Fleischmann , Bergische Universität Wuppertal, Germany Tatjana Lenz, Bergische Universität Wuppertal, Germany Andreas Salzburger , CERN PH-ATC & University of Innsbruck, Austria

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Sebastian Fleischmann , Bergische Universität Wuppertal, Germany

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  1. new fast atlas tRack simulation Sebastian Fleischmann, Bergische Universität Wuppertal, Germany Tatjana Lenz, Bergische Universität Wuppertal, Germany Andreas Salzburger, CERN PH-ATC & University of Innsbruck, Austria Andreas Wildauer, CERN PH-ATC & University of Innsbruck, Austria A. Salzburger, et. al.

  2. Outline • ATLAS Detector and Tracking devices • What’s behind Fatras - the new ATLAS offline Tracking software: Extrapolation package, Reconstruction geometry • Material budget + Material effects - comparison with full simulation geometry • Fatras applications - validation of track fitters / pattern recognition - track reconstruction dependency on magnetic field/material knowledge • Outlook & Conclusion A. Salzburger, et. al.

  3. Fatras Introduction: ATLAS Experiment • Inner Detector • Pixel Detector • SCT Detector • TRT Detector • solenoidal field • of ~ 2 Tesla • Muon System • MDT Chambers • CSC Chambers • RPC Chambers • TGC Chambers • compex toroidal field • Calorimeter • LAr Calorimeter • Tile Calrimeter information: http://cern.ch/atlas H 4m decay, Geant4 A. Salzburger, et. al.

  4. Simulation EDM Trajectory Creation uses the Extrapolation Tool and Geometry of Reconstrucion EDM Track/Noise Creation uses the Fitting/Data preparation Tools of Reconstrucion EDM Track Finding Track Fitting EDM Full/Fast Simulation/Track Reconstruction EVENT GENERATION 4-vector creation SingleParticle, PYTHIA, HERWIG ... Fast Detector Simulation Full Detector Simulation interaction with detector material, hit creation/particle decay parametric smearing of track parameters according to obtained smearing functions Geant4, FLUKA, … Digitization singal + noise creation Event Data Preparation EDM Track Finding ATLFAST Track Fitting Event Data Preparation EDM Analysis, Data Persistency, Event Visualization EDM A. Salzburger, et. al.

  5. Trajectory 1 … n behind • the new fast track simulation is a spin-off of the development of the new • ATLAS offline Tracking (i.e. track reconstruction) development: • - very modular design (dedicated Tools and Algorithms) • - dynamically loading of libraries (Interfaces) • - configuration via python steering • main component of Fatras is the • newly developed track Extrapolation • engine (with navigation) • Fatras is using the reconstruction • geometry as a simulation geometry • (enhances navigation) • Fatras acts completely on the • offline track reconstruction • Event Data Model (EDM) A. Salzburger, et. al.

  6. Connective Geometry (TrackingGeometry) Navigation between Volumes: • the prediction of the trajectory is enhanced by the • native navigation of the TrackingGeometry • - between Volumes (via BoundarySurfaces) • - between Layers (via interlinking) • BoundarySurfaces and Layers extend the common • Surface base class: • - naturally used in Extrapolation • Volumes and Layers carry material information: Navigation between Layers: Material interactions can be taken into account both ways. Volume based Model of ATLAS SCT Detector Layer based A. Salzburger, et. al.

  7. TrackingGeometry: material budget Geant4 Very complex full Detector geometry ~ 106 volumes in the ATLAS Inner Detector (ID) TrackingGeometry Simplified reconstruction geometry (TrackingGeometry) ~ 50 volumes A. Salzburger, et. al.

  8. number of hits/track • Hits/track comparison: • Fatras against Full sim./reco. • First real-life Fatras test: • tuning of reconstruction Fatras Fatras Full simulated/reconstructed: 5000 mu tracks with 5 GeV Simulation: ~ 95 s/250 events Digitization: ~ 90 s/25 events Fatras: 25000 tracks mu 5 Gev Simulation/Refit: 95 s/5000 events offline Reconstruction offline Reconstruction A. Salzburger, et. al.

  9. applications: validation • Fatras was born as a VALIDATION tool, • using same services (material, magnetic field, • extrapolator) guarantees perfect controlled • testbed: • - Track Fitters (initial intention) • - Vertex Fitters • - Pattern recognition • Modular design of offline Tracking software • automatically enhanced testbed for all fitters • following a common ITrackFitter interface • Fatras was used for strategy finding: • - check EDM changes (rrec – rhit)/sr slide by A. Franckowiak A. Salzburger, et. al.

  10. applications: magnetic field dep. 5000 tracks with 5 GeV simulated with realistic field (109.80 s, 2.0 GHz, including refit) Refitted (KF) with 100% magnetic field Refitted (KF) with 100% magnetic field Refitted (KF) with 98% magnetic field Refitted (KF) with 98% magnetic field s = 1.16 s = 1.48 s = 1.22 s = 1.23 A. Salzburger, et. al.

  11. applications: Momentum scale Reconstruction of single tracks using different scale factors for the reconstruction geometry: Fine-Tuning of material budget in Reconstruction Momentum scale estimation 5000 tracks with 5 GeV simulated with realistic field (av. 98.80 s/5000 events, 2.0 GHz, including refit) A. Salzburger, et. al.

  12. applications: More ? • Fatras does • SingleTrackSimulation • - Pattern Recognition • - Fitter Validation • - Material Mapping • Fatras does • TracksFromVertexSimulation • - VertexFitter Validation • Fatras does • GenEventSimulation • - Vertexing • - Pattern recognition • - 2nd stage pattern search A. Salzburger, et. al.

  13. Conclusion • A new fast track simulation for the ATLAS Inner Detector has been deployed • Spin-off of the new extrapolation package (simulation using the new reconstruction geometry) • Enhanced by the modularity of the new ATLAS offline track reconstruction, completely written and embedded in the EDM • Usage in validation of track finding and track/vertex fitting • Powerful tool for fast checks / strategy finding • Hasn’t reached it’s full power yet ! A. Salzburger, et. al.

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