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High Level Trigger Studies for the ATLAS Detector Efstathios (Stathis) Stefanidis

Detailed report on the ATLAS Detector, Trigger System, and High-Level Trigger with performance studies on IDScan, e/γ analysis, RoI size optimization and future plans. Includes physics studies and software details.

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High Level Trigger Studies for the ATLAS Detector Efstathios (Stathis) Stefanidis

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  1. High Level Trigger Studies for the ATLAS Detector Efstathios (Stathis) Stefanidis 1st Year Transfer Report, University College London Stefanidis E.

  2. OUTLINE • The ATLAS Detector : Overview. • The Trigger System. • Overview. • High Level Trigger. • Performance Studies. • IDScan. • e/γ vertical slice. • RoI size. • Future Plans. Stefanidis E.

  3. The ATLAS Detector: Overview. • pp colliding beams 14 TeV c.m. energy. • Design Luminosity: L=1034 cm-2s-1. • Three Parts: • Inner Detector • Calorimeter (EM – HAD) • Muon Spectrometer • Magnet System: • Solenoid: 2 T • Toroid: 0.4 T Stefanidis E.

  4. High Level Trigger (HLT) The Trigger System: Overview. • LVL1: • 40 MHz  75 kHz • < 2.5 μs • Hardware trigger • Reduced granularity information • LVL2: • 75 kHz  2 kHz • 10 ms • Full granularity information from both ID and Calorimeter • RoI mechanism • Event Filter (EF): • 2 kHz  100 Hz •  2s • Sophisticated algorithms • Alignment data available Stefanidis E.

  5. The Trigger System: HLT. • Event Selection Strategy: • Signature validation • Checks for signatures coming from interesting physics events • REJECT UNINTERESTING EVENTS VERY EARLY • RoI mechanism • (i) Defines the area where HLT • will start from. • (ii) Seeded by LVL1 • (iii) Only the data needed are • transferred •  MINIMISE THE PROCESSING TIME AND NETWORK TRAFFIC Stefanidis E.

  6. Hit Filter Group Cleaner z-Finder Track Fitter The Trigger System: HLT. • Event Selection Software: • ATHENA • Written using GAUDI architecture • Provides common services (Transient Data Store, Histograms, Auditing etc) • Well-defined interface not only to developers but also to the end-users • IMPROVE COHERENCY OF THE DIFFERENT SOFTWARE DOMAINS • IDScan • LVL2 track reconstruction algorithm • SPACE POINTS as input – Track parameters as output • Runs several times per event and once per RoI Stefanidis E.

  7. I. σ=179.9 μm II. III. Total Efficiency Efficiency: |Zgen – Zrec | < 1 mm Performance Studies: IDScan. z-Finder Stefanidis E.

  8. Performance Studies: IDScan. Pattern Recognition • |pTgen – pTrec|<15 GeV • |ηgen – ηrec|<0.01 • |φgen – φrec|<0.01 rads Stefanidis E.

  9. Electron selection • Weνe sample 22.5 GeV Performance Studies: e/γ slice. • Determine selection efficiencies and rates at each Trigger Level. • Apply isolation, energy, tracking matching etc cuts. Stefanidis E.

  10. Performance Studies: RoI size. • Preliminary study • Current size of RoI: ΔηxΔφ = 0.2x0.2 • COULD IT BE LESS ?  Reduce requested data + processing time Stefanidis E.

  11. η resolution: STRONG DEPENDENCE ON Z POSITION OF VERTEX ! ! ! φ resolution: 3mrad Cut at z  2 mm Barrel: σZ =0.86 cm EndCap: σρ =0.35 cm Performance Studies: RoI size. Stefanidis E.

  12. Physics Studies • Low Mass Higgs (mH<150 GeV) • Hγγ • Hbb • Study the full production/simulation/reconstruction chain. Future Plans. • Performance Studies • IDScan : Optimize the size the RoI • e/γ analysis : Improve, validate, optimize the cuts • 2004 TestBeam : Study the timing perfomance Stefanidis E.

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