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TT in Trigger Part III

TT in Trigger Part III. The Issues. Momentum (p T ) resolution B∙d l Pattern Recognition Efficiency (want 100%) vs Ghosts (want 0%) Low occupancy Timing Quick decisions Reject low momentum tracks (say p<3 GeV) Select high pT tracks (say p T >1.25 GeV)

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TT in Trigger Part III

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  1. TT in TriggerPart III

  2. The Issues • Momentum (pT) resolution • B∙dl • Pattern Recognition • Efficiency (want 100%) vs Ghosts (want 0%) • Low occupancy • Timing • Quick decisions • Reject low momentum tracks (say p<3 GeV) • Select high pT tracks (say pT>1.25 GeV) • Optimal pitch? Smaller pitch near beamline? Detection element size? • Material between VELO and TT • Correlation with calorimeter high energy shower deposits?

  3. TT Detector Review • Four layers of silicon • X1, U(+5o), V(-5o), X2 • ~200 um pitch • Initially intended for “L1” trigger • Idea abandoned (efficiency, ghosts, resolution) • Instead use CALO clusters & large IP Velo tracksas seed to do local PR in T-stations. • More efficient, better p determination, lowerghosts (presumably more CPU intensive though)

  4. TT Layers TTa – X1 TTa – X2 TTa – U • Sensor (LxW): 110 mm x 780 mm • Regions 1,2 and 3 have stripsof length 1L, 2L and 3L, resp. • 330 mm length at large Y • Minimal Y information 3 readout sectors 4 readout sectors

  5. Field in Velo-TT Region Z of TT stations: 232  265 m Bymax ~ 0.15 T Not very large

  6. VeloTT Tracking Strategy X projection • Search window 1/pz • Different tune for online (not used anymore) and offline • In offline, we are mainly interested in low momentum tracks • Additional tolerance window – hits in TT should be nearly on a line (could be many candidate tracks within the search window)

  7. VeloTT TrackingY Search Window 33 cm long strips 22 cm long strips 11 cm long strips Large Y window necessary A X,U,V hit by itself carries no Y information

  8. Performance at 2x1032 cm-2 s-1 4 GeV 2 GeV 1 GeV 0.5 GeV Efficiency Ghosts • P>4 GeV: • Eff ~ 90%, Ghosts ~10% • Not great if to be used in trigger • Rapid increase in ghosts asmomentum is reduced • Large X search window req.

  9. But, on the good side …Momentum Resolution Does improvemomentum resolution(at least in MC) Dp/p TT hits not used in track fit TT hits used in track fit p (GeV) M. Needham 2007-144

  10. pT resolution Using only straight linefits to hits in VELO andhits in TT (Was meant to be fast for (now defunct) L1 trigger) Trigger TDR • For tracks we’d like to trigger on, s(pT)/pT ~ 20% - 35% • Improvement possible with Kalman fit, but here you’d wantaccess to the detector material description (costly in CPU) • See next slide

  11. Y. XieLHCb 2003-100 Offline Eff What room is there to be gained, if CPU were not an issue pT(GeV) Ghost rate ~20% pT resolution in theregion we care about… compared To ~25% for no Kalman (see previous slide) pT(GeV)

  12. pT Resolution LHCb 2003-110, H. Dijkstra, et al pT(true)=1 GeV sp/p = 30% Large fraction of Trackswhere pT is significantlyoverestimated

  13. The backgrounds -- MinBias 2e32 • Use MCHits after full simulation. No Pattern Recognition • Look at DX between linear projection of Velo MCHit and all TT hits within a given Y search window. P range (X range for S/B): P<5 GeV: (-50.0, 5.0) 5<P<20 GeV (-10.0, 2.0) P>20 GeV (-2.5, 0.5) |DY|  5 mm(see Slide 17) S/B~23 S/B~98 S/B~16 Hits within readoutsector pointed to by track. If close to boundary,also take a secondreadout sector. Meant to mimic currentVeloTT algorithm. Tolerance window willimprove S/B, but still haveto cope with combinatorics S/B~0.4 S/B~4 S/B~0.6

  14. The backgrounds -- MinBias 2e33 P range (X range for S/B): P<5 GeV: (-50.0, 5.0) 5<P<20 GeV (-10.0, 2.0) P>20 GeV (-2.5, 0.5) S/B~9.3 S/B~44 S/B~3.8 S/B~1.6 S/B~1.4 S/B~0.15

  15. By Region – 2e33 Region 2 Region 3 Region 1 P<5 GeV 5<P<20 GeV P>20 GeV

  16. Looking by Occupancies – 2e33 • To translate to occupancy, • Divide by: • 100 events (n1=100) • 1 mm bin  0.198 mm strip • n2 = 5 All 4 planes grouped (n3=4) So, overall, divide by 2000. This is an event average. Clearly significant event-by-event variations, as the #intis Poisson distributed. Reasonably good agreementwith M. Needham’s talk atupgrade mtg, Jan 12, 2007. 10% Hits/mm Region 1 5% Hits/mm Region 2 3.5% Hits/mm Region 3

  17. BsDsK Signal – 2e32 P range (X range for S/B): P<5 GeV: (-50.0, 5.0) 5<P<20 GeV (-10.0, 2.0) P>20 GeV (-2.5, 0.5) Roughly S/B a factorof two worse than MinBias.(B events have~twice as manytracks/event) Low stats inbackground forp>5 GeV (DY<5 mm) S/B~22 S/B~136 S/B~9 S/B~0.8 S/B~2.6 S/B~0.3

  18. DY Distributions Using only TT Hits associated with track P<5 GeV 5<P<20 GeV P>20 GeV

  19. DX due to By and Multiple Scattering MS - back of envelope B deflection from observed deflectionsin MC. At 1 GeV: Field deflection ~ 23 mm s(DX)MS ~7 mm At 3 GeV: Field deflection ~ 7.5 mm s(DX)MS ~2.5 mm At 5 GeV: Field deflection ~ 4.5 mm s(DX)MS ~1.4 mm For MS, multiply by. From BOVExpected ~ 1.5 mm Both scale as ~1/p Scale MS expectation by 1/sqrt(2) for projection onto X or Y axis s(1/P)/(1/P) s(DX)/DX ~ 20% just from MS (maybe slightly overestimated)

  20. Improving pT Resolution via B∙dl Current LHCb Field (about ~0.7xField043) 0.2X 0.4X 0.6X 0.8X LHCb 2003-110, H. Dijkstra, et al 1X nominal B∙dl 1.2X 1.5X 2.0X 3.0X 5.0X Can gain in pT resolution with finer granularity as well

  21. Summary/Remarks • Increasing B∙dl sounds good, but will require a larger search window in X • Need to keep Y window “small” • Finer segmentation • Clearly, need better Y information ( strixel-TT ?) • Reducing pitch will improve p resolution, up to the point that MS in new TT starts to dominate. • E.g. 5 mm length x 100 um pitch ~2 million strixels/m2. (Current TT at ~1.5 m2) • Would need to look at what granularity is needed. • Should try to reduce material between VELO and TT if at all possible. • Can (upgraded) RICH1 help? • Toss low p tracks below threshold, confirmation… • Remove it – that’ll help also !

  22. Backup

  23. Previous Look from Matt

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