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Online Measurement of LHC Beam Parameters with the ATLAS High Level Trigger

Online Measurement of LHC Beam Parameters with the ATLAS High Level Trigger. David W. Miller on behalf of the ATLAS Collaboration 27 May 2010 17 th Real-Time Conference Lisbon, Portugal. The Inner Tracking Detectors. Silicon Strips 4 barrel layers + 2 x 9 end-cap disks

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Online Measurement of LHC Beam Parameters with the ATLAS High Level Trigger

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  1. Online Measurement of LHC Beam Parameters with the ATLAS High Level Trigger David W. Miller on behalf of the ATLAS Collaboration 27 May 2010 17th Real-Time Conference Lisbon, Portugal ATLAS Online Beam Parameter Measurment - RealTime 2010

  2. The Inner Tracking Detectors • Silicon Strips • 4 barrel layers + 2 x 9 end-cap disks • σrϕ~ 17μm; σZ~580μm • 6.3 million channels • Silicon Pixels • 3 barrel layers + 2 x 3 end-cap disks • σrϕ~ 10μm; σZ~115μm • 80 million channels TRT SCT PIX • Transition Radiation Drift Tubes • 73 barrel straws + 2 x 160 end-cap disks • σr~ 130μm • 350,000 channels ATLAS Online Beam Parameter Measurment - RealTime 2010

  3. The ATLAS Trigger System Hardware Level‐1 Trigger Calorimeter Muon System Hardware based Coarse granularity 2.5us Access to inner tracking detectors • Level-2 is first opportunity to perform track reconstruction • Limited to 40ms per algorithm • Can pull datafrom nearly 90 million channels Level‐2 Trigger RoI e/γ, μ, jet, .. Full granularity in RoI ~ 500 PC (multi‐core) ~40ms Event Filter ~1800 PC (multi‐core) High bandwidth data network ~4s • 3-level trigger system • L1: Hardware/firmware algorithms • L2: Software algos: regions of interest • L3 (EF): Software: full detector ATLAS Online Beam Parameter Measurment - RealTime 2010

  4. The LHC Machine • It is not enough to simply collect data, we have to collect gooddata • Measure and monitor the LHC beams inside of ATLAS every two minutes • Optimal ATLAS and LHC performance depends on high beam quality and operational efficiency • Feedback information on beam quality within ATLAS to LHC operators ATLAS Online Beam Parameter Measurment - RealTime 2010

  5. Introduction to the online beam spot measurement Motivation and Goals Design and Constraints RobustL2 tracking algorithms with Silicon-based pattern recognition Full Tracking:~100s ms (subset of evts) Fast L2 vertexing using decorrelating transformation Vertexing:~0.2 ms (10-2 of time budget) Expect ~kHz rates into L2, run also on rejectedevents: factor >10 more stats Gather (“pull”) and sum data from 1000’s of processor nodes • Measure and monitorthe interaction point position (x, y, z) profile (σx, σy, σz) and tilt • Communicate the “luminous region” parameters to the ATLAS and LHC control rooms • Feedback to Level-2 (L2) algorithms (e.g. b-tag) for optimal performance • Provide relative luminosity monitor via vertex counting Estimate the vector R (vertex position) using the measurements at the reference surface ATLAS Online Beam Parameter Measurment - RealTime 2010

  6. The LHC came online in record time ATLAS Online Beam Parameter Measurment - RealTime 2010

  7. Before we can safely turn on the silicon tracking detectors to see beam, LHC operators must “declare stable beams”…we were very happy ATLAS Online Beam Parameter Measurment - RealTime 2010

  8. First ATLAS Data with the HLT • With first stable beams came the first opportunity to catch a glimpse of the LHC beams within ATLAS • Activate full HLT farm (= hundreds-thousands of nodes) • Pull data from Inner Detector read-out drivers • Perform full track pattern recognition and fitting • Use fast vertex-fitterto reconstruct individual event vertices • All within the time budget of a ~40ms at L2 See PDAQ-28 from I. Christidi ATLAS Online Beam Parameter Measurment - RealTime 2010

  9. Routine online luminous region measurements • Within days, the high-level trigger became a routine component of operations • Position measured every ~2 min. • Online “beam spot” (luminous region) parameter determination based on massively parallel monitoring infrastructure ATLAS Online Beam Parameter Measurment - RealTime 2010

  10. Complementing the beam instrumentation • By measuring the longitudinal vertex position we can compare to (and calibrate) the LHC beam instrumentation • The BPTX sensors provide precise ToF measurements of the Z-position • We calibrated the ToF (remove offsets) and provided feedback to the LHC operators on the positioning of the interaction point in ATLAS BPTX: electrostatic sensors to provide time-of-flight measurements of the Z-position of individual proton bunches (See talk by J. Lundberg) ATLAS Online Beam Parameter Measurment - RealTime 2010

  11. Bunch-to-bunch Measurements • Ultimate LHC design: 2808 colliding bunches per orbit • Crucial to understand if all bunches “look the same” • Monitor the bunch-to-bunch positions and vertex count • Provides estimate of background • i.e. “do we see vertices where we shouldn’t?” --- Answer today: No! First LHC fill with > 4 colliding bunches Only find vertices in 9 colliding bunches ATLAS Online Beam Parameter Measurment - RealTime 2010

  12. Online luminosity monitoring • By continuously monitoring the vertex count we obtain a direct measure of the relative luminosity • Comparison with “standard” luminosity detectors indicates excellent shape agreement over large range of luminosity • Orthogonal acceptance ranges • Implies very little background ATLAS Online Beam Parameter Measurment - RealTime 2010

  13. Measuring the luminous region at 7 TeV ATLAS Online Beam Parameter Measurment - RealTime 2010

  14. “Real-time” interaction point characterization Luminous region tilt Bunch-to-bunch position Time evolution Independent track-only fit Relative Luminosity Beam instrumentation calibration ATLAS Online Beam Parameter Measurment - RealTime 2010

  15. Full circle: feeding back measurements to the HLT • Primary clients of online beam spot measurement: • Tracking (generally) • b-Tagging • Precise knowledge of the LHC beams in ATLAS is crucial for optimal trigger performance • But need to redistribute parameters determined in quasi-real time to thousands of running processes • Extremely challenging • Real-time reconfigurationof HLT farm made possible via proxy-tree • ~810 nodes, 10-100s MBs of configuration data • Configuration data cached in proxy tree See PDAQ-15 for the details ATLAS Online Beam Parameter Measurment - RealTime 2010

  16. Real-time configuration changes Process result (fit beamspot position, update DB) • Must ensure consistent and reproducible configuration across the entire HLT farm… • …without incurring deadtime or disrupting data-taking • Each proxy caches the result of DB queries • Client applications are “notified” of conditions update and read new beam spot information Gather data from nodes Feedback to L2 nodes and algos See PDAQ-15 for the details ATLAS Online Beam Parameter Measurment - RealTime 2010

  17. Summary and Conclusions • We have successfully deployed and utilized a set of algorithms for measuring and monitoring the LHC luminous region parameters in ATLAS in real-time • Measurements at both 900 GeV and 7 TeV indicate that these algorithms are robust and crucial for optimal performance of L2 trigger algorithms • The redistribution of these measurements to thousands of running processes within the L2 trigger farm has been successfully tested and will be used for real-time updates of the LHC parameters ATLAS Online Beam Parameter Measurment - RealTime 2010

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