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Liang HAN University of Manchester

Central Fiber Track Trigger System. Liang HAN University of Manchester. I. CFT & CTTT II. Simulator: l1ft2b III. First real L1CTT IV. Run2a V. Run2b VI. Summary. L1 & L2 trigger. Dzero Upgrade Tracker. Picture: recod tracks in CFT. I. Central Fiber Track Trigger.

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Liang HAN University of Manchester

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  1. Central Fiber Track TriggerSystem Liang HAN University of Manchester I. CFT & CTTT II. Simulator: l1ft2b III. First real L1CTT IV. Run2a V. Run2b VI. Summary Liang HAN

  2. L1 & L2 trigger Liang HAN

  3. Dzero Upgrade Tracker Liang HAN

  4. Picture: recod tracks in CFT Liang HAN

  5. I. Central Fiber Track Trigger Provide pT Track Trigger in xy-plane a)8 cylinders: Layer A,H b) Axial doublet fibers per Layer c)f~(0,2p), h~(-1.5,+1.5) d) in rphi: 80 Sectors, 10 Octants Liang HAN

  6. Pictures of CFT Alignment cylinders: Fibers of 1 super Layer/sector: Liang HAN

  7. 1 “sector” Liang HAN

  8. CFT Axial Doublet CFT axial doublets are formed using two interleaved CFT fiber layers as follows: increasing phi (looking NORTH at SOUTH face of detector) k+1 k k-1 k+1 k k-1 Doublet[k] = { !inner(k-1) & outer(k) } ||inner(k) Liang HAN

  9. CTTT Algorithm Stable charged from (0,0) in 2T Bz where in Dzero, in cm and pT in GeV Liang HAN

  10. “Equation” Pre-programmed Trigger lookup table: Hit Paten Liang HAN

  11. Trigger pTbin & AndOr Terms: 1) Exclusive pTbin: 2) Inclusive Terms: Liang HAN

  12. L1CTT framework Liang HAN

  13. II. Simulator: lft2b Simulate CTTT system, follows Trigger framework as close as possible, aim to Run2b Algorithm study: 1)CFT axial hits(ADC cut) 2) Trigger Cluster, i.e. Doublet/Singlet (Algorithm) 3) different Equations (Algorithm) 4) Equation-Cluster match 5) matched tracks reported Online platform CTTT framework Simulator l1ft2b Liang HAN

  14. III. First real L1CTT L1CTT started working this November, many strange of online Platform have been observed. l1ft2b is considered as close to the framework as possible, so a good tool to understand what’s wrong. Focus on highest pTbin PT1 Liang HAN

  15. what understood Phi distribution of online TTK10 triggered events: Octant 2&7 screwed up!! Liang HAN

  16. what not understood yet MaxpT distribution of l1ft2b for 3747 events triggered by online TTK10 2049 out of 3747, why? Liang HAN

  17. IV. Run2a Doublet Equation PT1 eff of current online on single muon from(0,0) Liang HAN

  18. Problem of current Equation • Current online(nominal): • 80 sectors: identical • designed Layer position: eg HX 51.5cm • tracks from (0,0) • As-built: • sectors: individual!!! • Layer shift: eg HX 52.0cm • beam-spot: eg (-0.3,0.339)mm • problem:PT1 eff of nominalon pT=15 single muon 99.1% 61.1% (+20.7% PT2) • answer: new as-built equations(Graham Wilsom) Liang HAN

  19. New as-built Equation • check as-built with data: 143 recod dimuon(pT>15) 93.5% PT1 eff Liang HAN

  20. MC expect ~99% PT1 eff with current luminosity, but as-built only gives ~93% on data, i.e. 6% ineff Liang HAN

  21. Weakness of Doublet Veto Track hit Noise hit Doublet[2] Doublet[1] Liang HAN

  22. Current CFT Layer occupancy Liang HAN

  23. Causes of ineff: • multiple scattering: unlikely, ineff independent with track pT • Doublet Veto: unlikely, 1D-shift mostly occur at D Layer • beam shift: unlikely, include 250micron smearing • inperfect CFT geometry: possible, some fibers are not parellel to z • Risk: the number of equations increase, eg nominal 16k to current as-built 18kfake rate Liang HAN

  24. V. Run2b development Bad news: we may never come to 132ns in Run2b Liang HAN

  25. Weakness of Doublet Algorithm A) Veto: pT=15 muons in Pythia mb7.5, Doublet PT1 eff is 97.6% (~99% in mb0) B) Fake: pure Pythia mb7.5 events, from random noise Doublet will have 1%triggered by fake PT1 L1 can only survive with greater than 0.2% fake in Run2b luminosity Doublet can’t survive in Run2b luminosity!! Liang HAN

  26. Worst-case scenario:Isajet • A) Eff lost due to Veto: • B) Fake rate: Liang HAN

  27. Worst-case scenario(cont.) Liang HAN

  28. Solution: Singlet or mixture Liang HAN

  29. 16 Singlet • Advantage: A) no Veto: efficiency unchanged with mb B)reject fake: finer Trigger Bin • Problem: PT1 part, with nominal+1.5pe fiber efficiency cut • 4800k!!! • 300 times FPGA resources of current online Run2a Liang HAN

  30. Trim Equations Tried and tested 13 different algorithms, kill most of them and come to the “final” choice : A)Mixed Algorithm: pT>5 part, pure 16 Singlet, i.e. “abcdefgh” pT<5 part, Singlet-Doublet mixture, i.e. “ABCDefgh” B)tricky pruning: to get rid of low acceptance ones Liang HAN

  31. Tricky pruning 1) Remove equations with Doublet missing 2) Cut on “intacc”(MC hits) 3) Remove/combine redundancy Come to “16v5PT12_acc200rr” and “12v4PT34_acc10rr” Liang HAN

  32. Result of latest Run2b Algorithm “abcdefgh” “ABCDefgh” • 98% PT1 eff, and 0.031% fake in pmb7.5 • Total come to 31k, risk of overflow FPGA Liang HAN

  33. What if can’t go to 132ns in Run2b Run2b Singlet Algorithm Liang HAN

  34. How worse it would be Liang HAN

  35. VI. Summary • CTTT simulator: • online CTTT: start to work, but • Run2a: real as-built equation is under development, need more Zmumu data for calibration • Run2b: new algorithm is suggested; need Run2a inform to make Run2b real Simulator l1ft2b CTTT framework Online platform Simulator l1ft2b why? Liang HAN

  36. No. of Doublet/sector in the TTK10 triggered events, given by online Liang HAN

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