The CDF Online S ilicon V ertex T racker

1. The CDF Online Silicon Vertex Tracker S. Donati University and INFN Pisa 9th Topical Seminar on Innovative Particle and Radiation Detectors, May 23-26 2004, Siena, Italy

2. Outline • Overview of the CDF-II detector and trigger • The Online Silicon Vertex Tracker : • - Physics motivation • - Working principle • - Architecture • - Track finding and fitting technique • SVT performance in the early phase of CDF Run II • SVT upgrades • Conclusions

3. The CDF-II Detector and Trigger detector elements Time Of Flight CAL COT MUON SVX CES MUON PRIM. XCES XFT XTRP L1 CAL L1 TRACK L1 MUON GLOBAL L1 SVT L2 CAL • 2-D COT tracks available@Level 1 (XFT) • Fast SVXII readout (105 channels) ~10s • SVT: 2D tracks in silicon (drops stereo info) • SVT: d = 35 mm (at 2 GeV/c) • Parallel design (12 slices in phi) reflects SVXII design GLOBAL LEVEL 2 TSI/CLK

4. Why do we need the Silicon Vertex Tracker ? Extract the huge Tevatron beauty/charm production (s= 50 mb) from the 1,000 larger QCD background (s = 50 mb)at trigger level bb pp In the pre-SVT age CDF was limited to leptonic modes (B  J/yX, B  lDX, suffering from low BR and acceptance) Secondary Vertex B Decay Length Lxy Displaced Track + Lepton (e, ) Pt(lepton) > 4 GeV (was 8 GeV) IP(trk) > 120 m Semileptonic modes: high statistics b-hadron lifetimes, b tagging, b mixing PT(B)  5 GeV Primary Vertex Lxy  450m d = impact parameter (~100 m) Two Track Trigger Pt(trk) > 2 GeV IP(trk) > 100 m Fully hadronic modes: 2-body charmless B decays, BS mixing, Charm.

5. SVT: Silicon Vertex Tracker(Chicago-Geneva-Pisa-Roma-Trieste) • SVT receives: • -COT tracks from Level 1 (,Pt) • -Digitized pulse height in SVX strips • and performs tracking in a • two-stage process: 1. Pattern recogniton: Search “candidate” tracks (ROADS) @low resolution. 2. Track fitting: Associate full resolution hits to roads and fit 2-D track parameters (d,,Pt ) using a linearized algorithm. • SVX II geometry: • 12 -slices (30°each) “wedges” • 6 modules in z (“semi-barrels”) • Reflected in SVT architecture

6. The SVT Algorithm (Step I)Fast Pattern Recognition Single Hit “XFT layer” Hardware Implemented by AM chip (full custom - INFN Pisa) : - Receives the list of hit coordinates - Compares each hit with all the Candidate Roads in memory in parallel - Selects Roads with at least 1 hit in each SuperStrip - Outputs the list of found roads FAST: pattern rec. complete as soon as the last hit of the event is read - 32.000 roads for each 30° slice - ~250 micron SuperStrips - > 95% coverage for Pt >2 GeV Si Layer 4 Si Layer 3 Road Si Layer 2 Si Layer 1 SuperStrip (bin)

7. The SVT Algorithm (Step II)Track Fitting When the track is confined to a road, fitting becomes easier • Linear expansion of parameters in hit positions Xi TRACK Pi = Fi Xi + Qi ( Pi = pt , f , d , c1 , c2 , c3) Road boundary P0i X5 • then refer them to the ROAD boundary X05 XFT layer P0i + dPi = Fi ( X0i + Xi ) + Qi X4 X04 SVX layer 4 P0i = Fi X0i + Qi X03 X3 SVX layer 3 X2 X02 • Fi and P0 i coefficients are calculated • in advance (using detector geometry) • and stored in a RAM SVX layer 2 X1 X01 SVX layer 1 • the task is to compute simple scalar products dPi = FiXi SuperStrip 250 mm

8. The SVT Boards AM Sequencer SuperStrip AM Board COT tracks from Level 1 Matching Patterns SVXII Data Roads Roads + Corresponding Hits Hit Finder Hit Buffer L2 CPU Tracks + Corresponding Hits Track Fitter

9. SVT Performance (I)d -  correlation 28 Aug 2001 data, 2<40 no Pt cut • Sinusoidal shape is the effect of beam displacement from origin of nominal coordinates SVX only d = X0·sin () - Y0·cos () track (X0,Y0) d  X0 = 0.0153 cm Y0 = 0.3872 cm • Can find the beam consistently in all wedges even using only SVX

10. Online fit of X-Y Beam position Run 128449 - October 6 2001 Can subtract beam offset online : I.P. with respect to beam position (online) : Independent fit on each SVXII z -barrel (6) s ~ 45 mm

11. Highlights of B physics (hadronic channels) B0sD-s p+ Bh+h'- Bh+h'- crucial to understand CP violation in the B sector (CDF-II competitive and complementary to B factories) B0s  D-s p+ golden channel to resolve B0s fast oscillations

12. Highlights of B physics (semileptonic channels) 1400 Bs  lDsl[] B+gl+D0X High statistics semileptonic B samples are excellent for calibration, B+/B0and Bs/B0lifetime measurements,tagging and B0and Bs mixing (for moderate xs)

13. Why is the SVT upgrade important ? 4/4 – 4/5 4/4 – 4/5 27 msec Time (ms) Empty SS • looser matching criteria • Ghost roads • 5 layers  larger Patterns 5/5 4/5 • 4 LVL2 buffers  • dead time depends on: • total LVL2 latency • fluctuations This road share all hits with the 5/5. It’s a ghost. More memory for thinner patterns

14. First step: new Associative Memory System Use standard cell chips to perform AM chip function Increase from 128 pattern/chip  4k pattern/chip (thinner roads, less fits, faster system, can cope with increasing Tevatron luminosity, increase coverage to forward region, lower pt threshold)

15. Conclusions • SVT performs fast and accurate 2-D track reconstruction • (is part of L2 trigger of CDF-II). Tracking is performed in • two stages: • - pattern recognition • - high precision track fitting • Taking good data since the beginning of CDF Run II, many • analyses in the field of beauty/charm physics only possible • thanks to this device • Upgrade of the system in progress to cope with increasing • Tevatron luminosity

16. CDF Trigger in run II • New for CDF run II at Level 1: • 2-D COT tracks available (XFT) • Fast SVXII readout (105 channels) : ~ 2.5 s detector elements CAL COT MUON SVX CES MUON PRIM. XCES XFT Track reconstruction with “offline” resolution at Level 2 XTRP SVT L1 CAL L1 TRACK L1 MUON d , Pt ,f d = 35 mm (at 2 GeV/c) GLOBAL L1 Fast !~10 ms (50 KHz L1 accept rate) SVT L2 CAL • 2-D tracks (drop SVXII stereo info) • Pt > 2 GeV/c • parallelized design : 12 -slices (30°each) • which reflects SVX II geometry GLOBAL LEVEL 2 TSI/CLK

17. Accurate deadtime model (ModSim) 4/5 simulation Ini_lum=10*1030 M. Schmidt 4/5 sept. 2003 Ini_lum=44*1030 7% 4/4  4/5+SVTupgrade+L2upgr Simulation: Ini_lum ~ 20*1030 Low lum, Run IIa L2, no COT prob. To be done again.

18. Understanding the width of d distribution d2 = B2 + res2 beam size i.p. resolution d ( mm ) • Present (online) 69 • Correct relative wedge misalignment 63 • Correct for d and  non-linearity 57 • Correct internal (detector layers) alignment 55 • Correct offline for beam z misalignment 48 • GOAL : SVXII + COT offline tracks (1wedge) 45 Can be implemented soon Need to have beam aligned

19. Effect of non-linearity : • Because of the linear approximation done by Track Fitters, SVT measures : • dSVT d /cos (f) • fSVT  tan (f) • Becomes important for large beam offset • Can correct it making the online beam position routine fit a straight line on each wedge

20. Expected SVT performance From SVT TDR (’96) : SVT simulation using RunI data Commissioning Run - Nov. 2000 : SVT simulation with SVX hits + COT Offline s ~ 45 mm s ~ 45 mm

21. SVT Performance (II)correlation with offline tracks : SVT – COT Curvature : SVT - COT  = 2 mrad d : SVT - COT  = 0.33 ·10-4 cm-1  = 21mm

22. Intrinsic transverse beam width Can extract B from the correlation between impact parameters of track pairs • If the beam spot is circular : <d1· d2> = B2· cos  B = 40 mm • But at present the beam is tilt (beam spot is an ellipsis) : short = 35 mm long = 42 mm

23. Cut Online on chi2, Pt, d, N.tracks • L2 : • N. SVT tracks > 2 • | d | > 50 mm • 2< 25 • Pt > 2 GeV/c • L1 prerequisite : • 2 XFT tracks • Trigger selection successfully implemented ! • About 200 nb-1 of data collected with this trigger where we can start looking for B’s !

24. SVT racks