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ATLAS Egamma Trigger Overview

ATLAS Egamma Trigger Overview. Xin Wu University of Geneva. Outline. Introduction LVL1 EM Trigger LVL2 EM Trigger EF EM Trigger Overall Performance Online Integration Conclusion. Introduction. Egamma Trigger: online selection of electrons and photons

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ATLAS Egamma Trigger Overview

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  1. ATLAS Egamma Trigger Overview Xin Wu University of Geneva

  2. Outline • Introduction • LVL1 EM Trigger • LVL2 EM Trigger • EF EM Trigger • Overall Performance • Online Integration • Conclusion

  3. Introduction • Egamma Trigger: online selection of electrons and photons • LVL1: hardware processors to reconstruct (isolated) EM cluster • LVL2: Seeded fast Athena clustering and tracking algorithms • EF: (seeded) offline clustering and tracking algorithms • Responsible for a large fraction of data for ATLAS physics • Inclusive electron, dielectron (e25i, 2e15i) • Main triggers for W, Z, dibosons, top, Higgs, SUSY, Exotics • Inclusive photon, diphoton (60i, 220i) • Main triggers for direct photon, H, Exotics • Exclusive (combination and topological) triggers • Dominant contributor to the trigger rate • ~65% of LVL1 rate at L=2E33 • Total LVL1: 25 KHz; EM25I: 12 kHz; 2EM15I: 4 kHz • ~35% of EF rate at L=2E33 • Total EF: 200 Hz; e25i+2e15i: 41 Hz; 60i+220i: 27 Hz TDAQ TDR

  4. LVL1 Calorimeter Trigger System Calorimeters (LAr, Tile) S 0.1x0.1 Cluster Processor RoI identification e/g/tclassification Threshold count RoI Builder analogue ~75m PreProcessor Timing alignment 10-bit FADC FIR filter BCID LUT Sum 2x2 BC-MUX Rx L1 CTP Jet/Energy Processor Sum Em+Had ETEx, Ey SET, ET Jet identification Threshold count 400 Mb/s 0.1x0.1 DAQ 0.2x0.2

  5. LVL1 EM RoI Reconstruction TriggerTower 0.1x0.1 RoI Core • RoI EM Core: a 0.2x0.2 local EM Et maximum • EM Cluster: most energetic of the four 2-tower EM clusters in th RoI Cluster • Et : LVL1 EM cluster Et • EM isolation • Total Et of the 12 EM towers around the RoI Cluster • Hadronic core isolation • Total Et of the 4 hadronic towers behind the RoI Core • Hadronic ring isolation • Total Et of the 12 hadronic towers around the RoI Core Em Cluster EM Isolation HAD core Isolation HAD ring Isolation

  6. LVL1 Calorimeter Simulation Software • Analog tower sum simulation • Need to be run at digitization stage • LArL1Sim : make LArTTL1objects from hits (Fabienne Ledroit) • TileHitToTTL1 : make TileTTL1 from hits • TrigT1Calo: trigger tower digitization and RoI building • Use either TTL1 or Cells as input • Can be run at digitization or reconstruction stage • Make TriggerTower, EmTauROI, JetROI, EnergyRoI objects • Provide simulated input (RoI’s) to HLT • Starting point for all efficiency/rate numbers ! • CTPsim: make L1 decisions for a given L1 menu • EDM in ESD/AOD • TriggerTowers • L1EMTauObjectContainer: collection of LVL1 EM clusters • LVL1_ROI: collection of LVL1 RoIs (, , threshold passed)

  7. LVL1 Egamma Performance • Benchmark numbers frequently updated with MC production and reconstruction releases • Eg. EM25i (M. Wielers) • Rome data: eff=96.7%, rate 5.6 kHz (L=1E33) • CSC validation: eff=96.5%, rate 6.0 kHz (L=1E33) • Detailed studies will be done with CSC data • Efficiency turn-on, noise effects, algorithm bias, dependence of isolation on event topology, … • Full characterization of LVL1 with data has high priority at the beginning of data taking • Tower noise threshold: 250 MeV steps • Isolation cut: HAD core, HAD ring, EM ring • Energy scale: 1 GeV or 500 MeV or 250 MeV • Efficiency turn-on • Clustering algorithm tuning, …

  8. g p0 L2 Egamma Calorimeter Algorithm 4 Processing steps of T2CaloEgamma at each step data request is made and accept/reject decision is possible Rcore= E3x7/E7X7 in EM Sampling 2 Eratio=(E1-E2)/(E1+E2) in EM Sampling 1 EtEm=Total EM Energy (add sampling 0 and 3) EtHad=Hadronic Energy (Tile or HEC)

  9. L2 Egamma Cluster Reconstruction • Samp2Fex : in sampling 2 • Find seed cell: hottest cell in the 0.2x0.2window around LVL1 RoI • sum E in 3*7 and 7*7 cells windows around seed  Rcore • Cluster center = E weighted eta, phi in a 3x7 window around seed • Cluster is a 3x7 window around the new cluster center • Samp1Fex: in sampling 1 (strips) • Update cluster energy • Find max E and second max E strips in a window of 0.125x0.196 around cluster center Eratio • SamEnEmFex • Update cluster energy with sampling 0 and 3 cells • Energy correction applied EtEm • SamEnHadFex • Calculate sum E of HEC or Tile in 0.1*0.1 window around cluster center EtHad

  10. L2 Egamma Calo. Data Preparation • RegionSelector • Return list of cells and ROB’s in the RoI window • Initialization from LAr/Tile Geometry (F. Ledroit) • Retrieve ROB data • 2 GB/s link ROS  LVL2 • ByteStream data conversion (the main bottle beck) • Coupled tightly to ROD data format, DSP processing • Continuous optimization (B. Laforge, D. Fournier, …) • Dedicated LVL2 ByteStream conversion (D. Damazio) • Cell memory allocated and geometry initialized during initialization • Organize cells in TT (Trigger Tower) • Modified decoding method • Factor of 6 faster than offline BS conversion • Not yet investigated • Handle dead/noise cells and timing information • Performance study with respect to zero suppression

  11. L2 Egamma Calo. Timing Performance D. Damazio • Fast conversion will become default for release 12 and 11.0.6 • Validation with physics performance • Further improvements • exploit the new ROD data format (B. Laforge) • fixed length block structure, hot cell index, ... • use of faster/smaller LArCell (D. Damazio) • A LVL2 Egamma Calo. code review is being planned for May-July Offline Conversion Fast Conversion

  12. LVL2 Tracking Algorithms • Seeded with LVL2 calo clusters • Search window 0.2x0.2 (could be narrowed by better Z position from T2Calo using strips) • 2 independent tacking algorithms with Pixel and SCT • IDScan: histogram method for pattern recognition; Kalman filter for track fitting • Total execution time ~4.1 ms (DataPrep ~3.5ms) • SiTrack: LUT method for finding triplet track segments straight line (R/Z) and circle (R/Phi) track fitting • Tool for track extension to TRT: TrigTRT_TrackExtensionTool • Use Probabilistic Data Association Filter • ~ 1 ms/track + DataPrep • TRT standalone and full Inner Detector tracking • TRTxK: wrapper for the offline tool Xkalman • Total TRT execution time ~4.6 ms (DataPrep ~2ms)

  13. EF Egamma Calorimeter Reconstruction TrigCaloRec • Wrap offline tools to EF environment (Cibran Santamarina) • Seeded approach, interface to trigger steering

  14. EF Egamma Tracking Reconstruction • Wrap offline newTracking tools (I. Grabowska-Bold) • All EF ID algorithms available since release 11.0.0 • The full Egamma slice is running on BS input with 11.0.5 nightlies

  15. Overall Egamma Performance • Many studies and optimizations have been done with Rome data and are being repeated for CSC data • Eg. e25i for 1E33 from M. Wielers, crack region excluded Rome data Offline = isEM = 78% CSC validation data

  16. Comment on Overall Performance • Performance numbers are only indicative due the fast evolution of software (trigger and offline) • Studies need to couple tightly with offline Egamma reconstruction (not always easy!) • Equally important and more challenging is to understand all individual variables • Geometrical, physical and topological bias • robustness against noise • efficiency calculation with data • Simplicity from the point of view of MC simulation, offline reconstruction and real data verification • correction and calibration • The final optimization can only be done with data • Get tools ready

  17. GAUDI with support for multiple threads HLT integration: Online vs. Online Simulaton vs. Offline GAUDI Online Sim Offline Online DAQ Data Flow ATHENA Environment ATHENA Environment L2PU/EFPT athenaMT/PT Steering Controller Steering Controller Algorithms Algorithms Algorithms ROS ByteStream File or Pool(RIO) File ByteStream File (RDO)

  18. Conclusions • Full HLT Egamma slice has been implemented • Basic functionalities and performance satisfactory • Great progresses have been made on more technical areas • LVL2 data preparation, EDM, EF wrappers, athenaMT, … • Next • Validation and performance studies with CSC samples • Integration on HLT pre-series with 11.0.6 • Correction and calibration schemes; Monitoring • Algorithm reviews and improvements • Trigger menu for L=1E31 • Benchmark physics channels (W, Z, top, DY, Diboson, direct , searches, …) • “Trigger-aware” analyses (physics groups) • Startup scenario for Egamma slice • Trigger/data sample/physics channel for Egamma verification, optimization and efficiency calculation • Tools for trigger commissioning with data

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