1. 1 Introduction to Geneva ATLAS High Level Trigger Activities Xin Wu Journée de réflexion du DPNC, 11 septembre, 2007 Participants Assitant(e)s: Gauthier Alexandre, Francesca Bucci, Till Eifert, Clemencia Mora MA: Olivier Gaumer, Andrew Hamilton, Phillip Urquijo (20/09/07) Physiciens: Szymon Gadomski, Xin Wu

2. 2 The Challenge of Trigger at LHC  Bunch crossing40 MHz  σ total70 mb  Event rate~1 GHz  Number of event/BC~25  Number of part./event~1500  Event size~1.5MB  Mass storage rate~200Hz Event rate  Level-2  Level-1  Offline Analyses Mass Storage   Need to have Trigger of high performance  ~6 order of rate reduction  Complex event and 140 M channels

3. 3 Brief Introduction to the ATLAS Trigger System LVL1: Hardware Trigger  EM, TAU, JET calo. clusters  µ trigger chambers tracks  Total and missing energy HLT: PC farms  LVL2: special fast algorithms  Access data directly from the ROS system  Partial reconstruction seeded with L1 Regions of Interest (RoIs)  EF: offline reco. algorithms  Access to fully built event  Seeded with LVL2 objects (full event reconst. possible)  Up to date calibrations HLTHLT 100 kHz 3 kHz 200 Hz 40 MHz RoI data LVL1 Acc. ROD LVL1 2.5  s Calorimeter Trigger Muon Trigger Event Builder EB 3 GB/s ROS ROB 120 GB/s Calo MuTrigDet Other detectors 1 PB/s Event Filter EFP EFN 300 MB/s LVL2 ~40ms L2P L2SV L2N L2P ROIB LVL2 Acc. RoI’s Event Size ~1.5 MB CTP Pipelines 2.5  s EF Acc. (Region of Interest) RoI requests ~4s

4. 4 Geneva’s Participation in High Level Trigger  Calorimeter Trigger Software (Gauthier, Olivier, Xin)  Overall coordination  LVL2 calorimeter cluster correction  HLT Steering Controller (Till)  Control the complex algorithm scheduling for ROI based reconstruction and Stepwise processing for early rejection (see Till’s talk)  Online integration of the HLT algorithms (Xin)  Integrate the HLT algorithms developed offline into the DAQ online running environment  Trigger Event Data Model (Andrew, Francesca)  Manage trigger objects stored in data (see Andrew’s talk)  EF tracking software (Andrew, Francesca)  Adapt offline track reconstruction for EF (see Andrew’s talk)  Express stream (Syzmon)  Special data stream for fast reconstruction  ATLAS Trigger Coordination (Xin)

5. 5 Calorimeter Trigger Software  Collaborative effort of many people  Common first steps for all the “slices”: electron, photon, jet, tau, missing energy  LVL1 hardware simulation  Calorimeter RegionSelector  Mapping between detector elements and  -  region for using Region of Interest  Calorimeter data preparation  Fast raw data unpacking  LVL2 calorimeter reconstruction  Specific fast clustering algorithms  LVL2 cluster calibration  Energy correction, position correction, crack correction,…  Event Filter calorimeter reconstruction  Adapt offline algorithms for EF  Overall coordination

6. 6 L2 EM Cluster Corrections (Olivier, Gauthier)  Lateral energy correction  Better Energy evaluation (10% effect)  S-shape correction (sampling 2)  Better position reconstruction  Longitudinal energy correction : Material and leakage  Better energy resolution  Energy  correction and  correction + accordion modulations for different clusters  Crack corrections (local correction)   = 0.8 : crack between the two electrodes of the barrel   = 1.4 : crack between barrel and end-cap  Currently first 2 corrections implemented using offline constants  Study effect on trigger in progress

7. 7 Energy correction - Effects Energy calibration based on offline calibration:  global factor (lateral leakage)  off : offset  w i : weights on pre-sampler and layer 3 energy M Z reconstructed from electron pairs - With energy correction - Without energy correction Used to give the best energy resolution  Get the best efficiency On set of parameters per  position From Olivier

8. 8 S-shape correction study Function proposed for this correction : Where With This function is actually modified to ensure the continuity at |u|=1 The variables are redefined to remove correlations between them At the end the actual function used is :  Only 3 parameters left tabulated as  function of energy  An interpolation in energy is done  on the parameters. Before correction. After correction 0.025<  <0.05 From Olivier

9. 9 Online Integration of HLT Algorithms  Integrate the HLT algorithms developed offline into the DAQ online running environment  HLT algorithms developed in the offline framework because they use many offline reconstruction tools (more on EF, less on LVL2)  Read MC pool RDO files and use transient BS  Run together with Reconstruction  Well suited (fast turn-around) for trigger performance studies  Online running is quite different from offline  Transition controlled by DataFlow software rather than Athena  Read ByteStream raw data from ROS through DAQ  Need to interface to online monitoring/error reporting tools  Need to be thread-safe for multithreaded running  Online integration involves many components of the HLT:  Algorithms, trigger configuration, database, Steering Controller, Data Collection, …  Follow through integration steps from offline, quasi-online (Athena MT/PT) tests all the way up till final online validation at point-1

10. 10 Steps of Online Integration Simulated Online Environment 1) Test offline –RDO input –Raw (BS) input Offline Environment athena Steering Controller Algorithms 2) Test with athenaMT –simulate online –BS input –use TDAQ release 3) Test at Point 1 –actual DAQ –BS input (through ROS) athenaMT/PT Steering Controller Algorithms DAQ Data Flow L2PU Steering Controller Algorithms

11. 11 DAQ/HLT Technical Runs  Dedicated Technical Runs (1 week each) are used to test DAQ/HLT and HLT algorithm integration  So far two in 2007 (March and May). Next in end of September  Brief Summary of the May TR (21/5-25/5)  ‘Final’ Hardware ROIB (+ LVL1 emulator), 120 ROSs 4 HLT racks (130 dual quad-core 1.8 GHz), ~5% final system  tdaq-01-07-00, AtlasHLT 2.0.5-HLT, Offline 12.0.5-HLT-1  All basic HLT slices integrated e10, g10, mu6, tau10, jet20, cosmic, Bphysics, met combined : e10+g10+mu6+tau10+jet20  ~ 6k events (mixed physics processes, ~60% jets and ~40% W/Z)  Main achievement :  Validated TDAQ and HLT infrastructure with final hardware  Measurements with dummy algorithm LVL2 and EF with final hardware  Functionality test with combined algorithm  Tested DBProxy and triggerDB configuration  Next Technical Run: Sept 24-30

12. 12 LVL2 Timing for Rejected Events mean = 5.3 mean = 6.0 ms Data requests per event Data collection time per event mean = 31.5 ms Total time per eventProcessing time per event mean = 25.7 ms

13. 13 Express Stream (Szymon)  ATLAS data streams Calibration streams contain incomplete events. Complete physics events used for calibration are in the Express.

14. 14 Express Stream of ATLAS data What is the Express Stream One of the data streams produced by ATLAS online, O(10%) of the physics data. To be reconstructed and looked at rapidly. Results in a few hours, before the reconstruction starts. Calibration, check of data quality, monitoring of the detector status, rapid alert on interesting events… Role of Geneva S.Gadomski coordinates the work on the trigger menu. Trigger rates are calculated on Swiss ATLAS Grid resources, in collaboration with Bern (Sigve Haug). From Szymon

15. 15 Conclusion  ATLAS HLT project is in good progress  Trigger algorithm development in advanced stage  Trigger menu for early data-taking being completed  HLT being integrated online and performance being studied in Technical Runs  Over the pas year Geneva expanded its effort in the ATLAS High Level Trigger and made many important contributions  We are becoming key players in several areas  Calorimeter Trigger Software, Steering, EDM, Online Integration, Express Stream, Trigger Coordination  See Till and Andrew talks for some more details  Expertise in HLT is a great advantage for the group to access and understand real data at the earliest stage

16. 16 LVL2 Egamma Reconstruction Algorithm  00 Rcore= E 3x7 /E 7X7 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) 4 Processing steps of T2CaloEgamma at each step data request is made and accept/reject decision is possible

17. 17 Calorimeter Timing Results from the May TR mean 27ms / RoI mean 65ms /RoI TrigCaloCellMaker TrigCaloTowerMaker TrigCaloClusterMaker mean 16ms / RoI T2CaloEgamma mean 6.2ms / RoI