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CMS High Level Trigger Selection

CMS High Level Trigger Selection. Domenico Giordano INFN - Università di Bari. 9th Topical Seminar on Innovative Particle and Radiation Detectors Siena 23-26 May 2004. on behalf of CMS collaboration. The CMS detector at LHC. LHC environment. p-p collider

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CMS High Level Trigger Selection

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  1. CMS High Level Trigger Selection Domenico Giordano INFN - Università di Bari 9th Topical Seminar on Innovative Particle and Radiation Detectors Siena 23-26 May 2004 on behalf of CMS collaboration

  2. The CMS detector at LHC LHC environment p-p collider Beam Energy 7 TeV Bunch Crossing Rate 40 MHz Luminosity Low 2x1033 cm-2s-1 = 2x106 mb-1Hz High 1034 cm-2s-1 = 107 mb-1Hz sinel(pp) 70 mb Interaction Rate ~1GHz Interactions/Crossing ~20 (@ High Lumi.) basically minimum bias events tracks with pt > 2 GeV tracks with pt > 25 GeV IPRD04 - Siena 25/05/2004

  3. CMS Trigger Strategy CMS DAQ requirements Two Trigger Levels Event size ~1 Mbyte (zero-suppr.) Readout network 1 Terabit/s Level-1 Output 100 kHz Mass storage 100 Hz Rejection Power O(105) [40 MHz -> 100 Hz] 40 MHz • Level-1: • Custom synchronous processors • - Pipelined structure • Particle identification (e/g, muons, jets, MET ) • - Local pattern recognition and energy/momentum evaluation • - Work on coarse granularity information from calorimeters and muon detectors • - Actual Processing time ~1 ms 100 kHz 1 Tbit/s High Level Trigger (HLT): Asynchronous CPU farms - Access to full event data - Finer granularity, precise measurement - Reconstruction and selection of e, g, m, jets, MET, b, t-tagging - Matching between detectors 100 Hz IPRD04 - Siena 25/05/2004

  4. Processor farm for HLT Advantages • Benefit maximally from evolution of computing technology • Flexibility: • no built-in design or architectural limitations — maximum freedom in what data to access and in sophistication of algorithms • Code is as close as possible to offline reconstruction code • Evolution of algorithms, including response to unforeseen backgrounds or unexpected physics • Minimize in-house elements • cost • maintainability Code runs in single processor, which analyzes one event at a time IPRD04 - Siena 25/05/2004

  5. HLT requirements • Main requirements: • Satisfy CMS physics program with high efficiency • Selection must be inclusive (to discover unexpected physics) • Must not require preciseknowledge of calibration/run conditions • Efficiency must be measurable from data alone • All algorithms/processors must be monitored closely • Limitations: • CPU time • Output selection rate (~100 Hz) IPRD04 - Siena 25/05/2004

  6. Momentum resolution Full tracker Reconstruction on demand Algorithms are executed only when (and if) the corresponding piece of information is requested In order to reject backgrounds events as soon as possible: • HLT organized in logical steps (progressively more sophisticated and CPU-time consuming) • Level-2: uses calorimeter and muon detectors • Level-2.5: also uses tracker pixel detectors • Level-3: uses of full information, including tracker • Regional Reconstruction: • Use only information coming from a limited region of interest from Lvl-1 candidate objects • save CPU-time • Conditional Reconstruction (for tracker): • Use a reduced number of Hits • At HLT ultimate resolution is not needed IPRD04 - Siena 25/05/2004

  7. Level-1 ECAL reconstruction Threshold cut Full granularity Level-2 Level-2.5 Pixel matching Level-3 Photons Threshold cut Isolation Electrons Track reconstruction E/p, matching (Dh) cut HLT: e/g selection • Electrons and photons reconstruction and rejection Electron reconstruction key is recovery of radiated energy • Electron rejection • key tool is pixel detector • In addition: • Isolation cuts (ECAL, pixel, track) • Had/EM isolation • p0 rejection see P. Govoni Talk IPRD04 - Siena 25/05/2004

  8. HLT: Muon Selection Standalone Muon Reconstruction (Level-2) • Full resolution of all muon detectors (DT, CSC, RPC) • Track seeds from LvL-1 muon candidates • Regional reconstruction • - based on iterative Kalman Filter method • - Local reconstr. of track segments only in chambers • compatible with extrapolated state • Trajectory building works from inside out • Track fitting works from outside in, includes nominal interaction point • Apply c2 cut to reject bad tracks Issue: propagation of tracks through iron, in a not constant magnetic field (using GEANE) IPRD04 - Siena 25/05/2004

  9. Level-3 Muon Reconstruction PT resolution barrel • Use full tracker system • Define a region of interest through tracker based on L2 track with parameters at vertex • Create one or more pixel seeds for each L2 m • Perform regional reconstruction in all tracker + m-chambers • Resolve ambiguities Lvl-2 s = 0.12 W->mn Great gain in resolution Efficiency vs PT Lvl-3 L1 s =0.013 L2 Threshold PT >20 GeV L3 (1/pTrec-1/pTgen) /(1/pTgen) IPRD04 - Siena 25/05/2004

  10. Muon Isolation Backgrounds muons with pT < 30 GeV/c belong especially to decay chain of K, p , b, c Isolation allows to discard muons inside b/c jets Calorimeter Isolation - SET in a cone around muon - Applied @ Lvl-2 - Sensitive to pile-up Pixel/Tracker Isolation - SPT in a cone around Lvl-3 muon - Regional reconstruction - Conditional reconstruction (stop as soon as sufficient number of hits collected) Single-mTrigger rates • Cone size and thresholds optimized to get • maximum bkds rejection for 97% efficiency of reference signal (W->mn) • efficiency flat in h High Lumi IPRD04 - Siena 25/05/2004

  11. HLT Muon Performance HLT muon thresholds at - low luminosity - rate 29 Hz Single m: 19 GeV Doublem: 7 GeV Combined (single, di-muon) Efficiency @ Low Lumi: H (160 GeV/c2) ->WW(*)-> mmnn : 92 % H (150 GeV/c2) ->ZZ(*) -> mmmm : 98 % IPRD04 - Siena 25/05/2004

  12. HLT: Jet Selection Iterative cone algorithm: • Look for a “protojet” in a cone around a seed tower, • Calculate direction and ET of protojet • Iterate until protojet energy/direction don’t change, or until 100 iterations HLT Thresholds (GeV) Not-Regional Jet finding: Use all calorimeter towers (not only Lvl1 jet candidates) Offline reconstruction will use more sophisticated algorithms Very high thresholds With some other trigger conditions thresholds reduce at a acceptably level Jet * (ETmiss, e, m) IPRD04 - Siena 25/05/2004

  13. HLT: Missing ET Calculate ETmiss as a simple vector sum of the calorimeter towers with signal over a threshold of 500 MeV Generator level ETmiss > 60 GeV: neutrinos produced in heavy flavors decay ETmiss < 60 GeV : limited calorimeter coverage |h|<5 HLT ETmiss higher than at generator level “ETmiss” objects selection is done in association with other requirements, like a energetic jet IPRD04 - Siena 25/05/2004

  14. HLT: t tagging Selection of isolated t leptons such as those expected in MSSM Higgs decays, with final-state signature of: 1 t-jet + lepton,2 t-jet, 1 t-jet • Benchmark signal channels • A0/H0 (200, 500 GeV) -> 2t-jet, t-jet + lepton • H+(200, 400 GeV) -> tn -> t-jet n t decay hadronically in 65% of time producing narrow jet with relatively small number of charged/neutral hadrons t-jets identification involves calorimeter and tracking detectors Calorimeter Selection • reconstruction of a jet in a narrow region centered on Lvl-1 t-jet • electromagnetic calorimeter isolation IPRD04 - Siena 25/05/2004

  15. t tagging with Pixel/Tracker • t-jet direction from calorimeter jet • Regional Tracking • Look only in Jet-track matching cone • Loose Primary Vertex association Rm=0.1 • Conditional Tracking Stop track as soon as: • Pixel seed found (PXL) / 6 hits found (Trk) • If Pt<1 GeV with high C.L. PT> 3 GeV Rs=0.07 PT> 6 GeV Ri=0.2-0.45 PT> 1 GeV Reject event if no “leading track” found • Isolation • Regional tracking inside isolation cone • Conditional tracking Reject event as soon as additional track found Efficiency ~40–50 % Background rejection 103 IPRD04 - Siena 25/05/2004

  16. HLT: Inclusive b tagging Issue is the selection of hard b-jets in the final state large value of b-hadron proper time (ct 450 mm) gives rise to tracks with large impact parameters w.r.t. production vertex Tagging algorithm “track counting” : count the number of tracks exceeding a given threshold on IP significanceS (= IP value/IP error) Track Reconstruction Regional Tracking:Look only in Lvl-1 calorimeter jet cone Primary vertex reconstructed using the pixel detector ( 50 ms ) Conditional Tracking:Stop track as soon as • pixel seed found (PXL) + 6 hits founds (Trk) • if Pt < 1 GeV with high C.L. Use tracks to refine Jet axis:poor direction resolution of L1 Calo Jet due to coarse granularity of trigger cells IPRD04 - Siena 25/05/2004

  17. b tagging performance b-tag a jet if it has at least 2 tracks exceeding a threshold on IP significance Samples: back-to-back di-jets, inclusive QCD sample CPU time (dominated by track reconstruction) ~ 300 ms Low Lumi ~ 1 s High Lumi Operating point Low Lumi •  55% efficiency for b-jets • mistagging rate .1% • selection almost independent of jet ET IPRD04 - Siena 25/05/2004

  18. HLT rates & signal efficiency Startup conditions: L = 2x1033 cm-2s-1 Lvl-1 can handle 50 KHz, but only 15.1 KHz are allocated ( safety factor of 3) to account for • simulation uncertainties • beam conditions Total HLT rate: 105 Hz HLT performance with previous selection cuts IPRD04 - Siena 25/05/2004

  19. HLT: CPU usage All numbers for a 1 GHz, Intel Pentium-III CPU Time completely dominated by muons (GEANE extrapolation) Expect improvements Total 4092 • Total: 4092 s for 15.1 kHz  271 ms/event At start-up 50 kHz system requires 15,000 CPUs • Moore’s Law: 7-8 x CPU power before LHC startup (2007) •  40 ms in 2007  2,000 CPUs • basic estimate of 1,000 dual-CPU boxes in Filter Farm IPRD04 - Siena 25/05/2004

  20. Conclusions • The CMS High Level Trigger • - runs on a single farm of commercial processors • - has great flexibility • - uses code close to offline reconstruction code • - allows evolution of algorithms in order to • improve event selection • adjust to unforeseen circumstances ( high background levels, • new physics …) At startup Low Luminosity, with a DAQ bandwidth of 50KHz (Lvl-1) the CMS HLT provides a selection of O(10-3) that is - highly efficient for most physics objects - inclusive and avoid detailed topological requirements IPRD04 - Siena 25/05/2004

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