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The CDF Online Silicon Vertex Tracker I. Fiori INFN & University of Padova 7th International Conference on Advanced Technologies and Particle Physics Villa.

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Presentation on theme: "The CDF Online Silicon Vertex Tracker I. Fiori INFN & University of Padova 7th International Conference on Advanced Technologies and Particle Physics Villa."— Presentation transcript:

1 The CDF Online Silicon Vertex Tracker I. Fiori INFN & University of Padova 7th International Conference on Advanced Technologies and Particle Physics Villa Olmo (Como) - October 15-19 2001

2 Tevatron and CDF upgrades for Run II The SiliconVertexTracker : - Physics motivation - Working principle - Architecture - Track finding and fitting technique SVT performance during summer 2001 Tevatron run - various items … Conclusions Outline

3        ns L = 1 - 2  10 32 cm -2 s -1 E CM = 2.0 TeV New Tracking System COT L00 +SVXII + ISL 3-D info Extended tracking to forward region New Trigger Time Of Flight The Tevatron and CDF Upgrades for Run II

4 CAL COT MUON SVXCES XFT XCES MUON PRIM. XTRP SVT L2 CAL L1 CAL GLOBAL L1 MUON L1 TRACK GLOBAL LEVEL 2 TSI/CLK detector elements New for CDF run II at Level 1: 2-D COT tracks available (XFT) Fast SVXII readout (10 5 channels) : ~ 2.5  s Track reconstruction with “offline” resolution at Level 2 SVT 2-D tracks (drop SVXII stereo info) Pt > 2 GeV/c parallelized design : 12  -slices (30°each) which reflects SVX II geometry Fast ! ~10  s (50 KHz L1 accept rate)  d = 35  m (at 2 GeV/c) d, Pt,  CDF Trigger in run II

5 Why do we need the Silicon Vertex Tracker ? The Tevatron produces a lot of B events   b ( ~ 10 events in Run II ) 11 bb But hidden in 1,000 more background   mb pp We need a Trigger “The Old Way” - Trigger on leptonic B decays - SVX tracks used Offline to reconstruct Secondary Vertices Problems - Low B.R. for leptonic modes - Detector acceptance limited (Nonetheless, many results from CDF) “The New way” - SVT: trigger on displaced tracks Improved B physics capabilities: fully hadronic B decays B Primary Vertex Secondary Vertex  100  m c  450  m B

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

7 Road The SVT Algorithm (Step I) Fast pattern Recognition Hardware Implemented via the Associative Memory 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 (found roads) –Outputs the list of found roads FAST! : pattern rec. is 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 Single Hit SuperStrip (bin) “XFT layer” Si Layer1 Si Layer2 Si Layer3 Si Layer4

8 The SVT Algorithm (Step II) Track Fitting When the track is confined to a road, fitting becomes easy ! : P i = F i * X i + Q i ( P i = p t, , d        ) P 0i +  P i = F i * ( X 0i +  X i ) + Q i P 0i = F i * X 0i + Q i  P i = F i *  X i … then refer them to the ROAD boundary : Road boundary TRACK P 0i X5X5 XFT layer X 05 SuperStrip 250  m the task reduces to compute the scalar products (FPGA) : F i and P 0 i coefficients are calculated in advance (using detector geometry) and stored in RAM Linear expansion of Parameters in the hit positions X i : SVX layer 4 X4X4 X 04 SVX layer 3 X3X3 X 03 SVX layer 2 X2X2 X 02 SVX layer 1 X1X1 X 01

9 The SVT Boards Hit Finder AM Sequencer AM Board Hit Buffer Track Fitter Detector Data Hits Super Strip Matching Patterns Roads Roads + Corresponding Hits L2 CPU Tracks + Corresponding Hits

10 SVT racks

11  Sinusoidal shape is the effect of beam displacement from origin of nominal coordinates d = X 0 ·sin (  ) - Y 0 ·cos (  ) SVX only (X 0,Y 0 ) d  28 Aug 2001 data,  2 <40 no Pt cut Can find the beam consistently in all wedges even using only SVX X 0 = 0.0153 cm Y 0 = 0.3872 cm track SVT Performance (I) d -  correlation

12 I.P. with respect to beam position (online) : Independent fit on each SVXII z -barrel (6) Can subtract beam offset online : Run 128449 - October 6 2001  d = 69  m Beam is tilt is : dX/dZ  840  rad dY/dZ  -500  rad Online fit of X-Y Beam position

13  d 2 =  B 2 +  res 2 Present (online)69 Correct relative wedge misalignment63 Correct for d and  non-linearity 57 Correct internal (detector layers) alignment55 Correct offline for beam z misalignment 48 GOAL : SVXII + COT offline tracks (1wedge)45 beam size i.p. resolution  d (  m ) Can be implemented soon Need to have beam aligned Understanding the width of d distribution

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

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

16  = 21  m  = 0.33 ·10 -4 cm   = 2 mrad  : SVT – COT Curvature : SVT - COT d : SVT - COT SVT Performance (II) correlation with offline tracks

17 =  B 2 · cos  Can extract  B from the correlation between impact parameters of track pairs If the beam spot is circular :  B = 40  m But at present the beam is tilt (beam spot is an ellipsis) :  short = 35  m  long = 42  m Intrinsic transverse beam width

18 L2 : N. SVT tracks > 2 | d | > 50  m  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 ! Cut Online on chi2, P t, d, N.tracks

19 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 Installation completed Autumn 2000 Thoroughly tested on real Tevatron data April – September 2001 Lots of tests and fine tuning done during the summer Many things understood, will be implemented after the October - November Tevatron shutdown Performance already close to design ! Conclusions


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