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A Fast Level 2 Tracking Algorithm for the ATLAS Detector

A Fast Level 2 Tracking Algorithm for the ATLAS Detector. Mark Sutton University College London. 7 th October 2005. LHC pp colider, collision energy 14 TeV Bunch crossing every 25ns - 40MHz rate Data storage capability ~200Hz Reduction of ~200000 : 1 needed!

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A Fast Level 2 Tracking Algorithm for the ATLAS Detector

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  1. A Fast Level 2 Tracking Algorithm for the ATLAS Detector Mark Sutton University College London 7th October 2005

  2. LHC pp colider, collision energy 14 TeV Bunch crossing every 25ns - 40MHz rate Data storage capability ~200Hz Reduction of ~200000 : 1 needed! Peak luminosity: 2x1033 cm-2s-1 1034 cm-2s-1 Between ~5 and ~25 (soft) pp interactions per bunch crossing Interesting high pT interactions complicated by “pile-up” ATLAS will use a Three Level, Trigger… Pipelined, hardware LVL1 LVL2 and Event Filter farms Physics rates at the LHC M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  3. ATLAS Trigger-DAQ overview > Latency: 2.5ms (max) > Hardware based (FPGA, ASIC) > Calo/Muon (coarse granularity) LVL1 > Latency: ~10 ms (average) > Software (specialised algs) >All sub-dets, full granularity > Match different sub-det info > Work in Regions of Interest LVL2 > Latency: few sec (average) > Offline-type algorithms > Full calibration/alignment info > Access to full event possible EF M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  4. The ATLAS Detector Muon Detector Calorimeter InnerDetector M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  5. The ATLAS Inner Detector TRT SemiConductor Tracker Pixel Detector M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  6. Tracking in the ATLAS LVL2 Trigger • High-pT electron/muon identification - Match Inner Detector tracks to information from outer detector (calorimeter, muon detector) • B Physics (at low lumi) - Exclusive reconstruction of golden decays (e.g. B pp) • Inclusive b-jet tagging (e.g. in MSSM H  hh  bbbb) • LVL2 is the earliest stage where … • Data from tracking detectors is available, • it is possible to combine information from different sub-detectors • Precision tracking at ATLAS predominantly from the Inner Detector: • 3 layer Pixel Detector (3 layers in the end caps) • 4 Layer Semi-Conductor Tracker, SCT (9 layers in the end caps) • Transition Radiation Tracker (TRT) • Two approaches for the Silicon tracking … • Pixel only using Lookup tables - SiTrack, • Complete (all layer) silicon tracking - IdScan. M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  7. LVL2 processing in Regions of Interest (RoI’s) • Most LVL1 accepted events are still uninteresting for physics studies • Decision can be made by further processing only those sections of the detector that LVL1 found interesting • Minimise data transfer to LVL2 processors • Minimize processing time at LVL2 • Average RoI data size ~2% of total event • On average, ~1.6 RoI’s per LVL1 accepted event M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  8. H mmmm M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  9. One bunch crossing One pp interaction M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  10. Dealing witrh “Pileup” events • Exploit differences between interesting (high-pT) and uninteresting (low-pT) interactions • Each has a vertex at different z positions along the beamline. • The interesting pp collision should have more high-pT tracks, at least inside the RoI that generated the LVL1 RoI. • Ideally, we would want to • Find the z position of the interesting pp interaction before any track reconstruction • Select only groups of space points consistent with that z • Only then get into combinatorial tracking. M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  11. trackcandidate SpacePoints ZFinder Patternrecognition Track fitting Tracks z-coordinate trackcandidate trackcandidate LVL2 Tracking IdScan Algorithm overview • IdScan (Inner Detector Scan) Algorithm in four stages • Z Finder to find event vertex-histogramming algorithm • Hit Filter for hits compatible with this z -histogramming • Find hit combinations consistent with single tracks. • Track fitting with hits from previous stages -Kalman Filter Fitter, extrapolate to the TRT (See talk by Dmity Emelyanov) M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  12. ZFinder space point selection • Designed to be fast, without the need for detailed tracking • High pT tracks are (almost) linear in r–z. Use (r,z) from pairs of space points from a track for simple linear extrapolation to determine track z0 • Search for hits consistent with high pT tracks • Hits from high pT tracks will lie in a restricted region of f • bin hits in thin slices of f, (in bins of 0.2-0.3 degrees) • treat each slice (almost) independently • Take all pairs of hits and histogram their extrapolated intersection with beam line. • Fast - reduces hit combinations from lower momentum tracks M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  13. Curvature in the transverse plane • Use narrow phi slices (0.2-0.3 degrees) - improves selection of high pT tracks and significantly reduces combinatorial multiplicity. pT ~ 20 GeV Df~ 0.3 degrees pT ~ 1 GeV Df~ 5 degrees M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  14. Single electron RoI (0.2x0.2) From total ~200 hits, only ~7 good electron hits M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  15. ZFinder – Jet RoI Jet RoI fromWH event M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  16. Resolution for single 25 GeV electron events (with no pile-up) ~200 mm, varies with h Efficiency approaches 100% In low luminosity events (with pile up) efficiency approaches 95-97% Zfinder Performance - Single electrons M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  17. The HitFilter • All Space Points on a track originating from a given z0 have the same h when calculated with respect to z0 … • Put all hits in a 2D histogram in (h,f) - (currently use 0.005, 2.4 degrees) • Accept hits in a bin if it contains hits in at least 4 (out of 7) layers • Reject all other hits (at high lumi, ~95% of hits are rejected!) • Limits number of combinations • Latency behaviour, approximately linear with number of hits. M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  18. Pattern Recognition in Pile-up events • If correct vertex is found, track finding efficiency approaches 100%. r x-y view r-zview z f f-hhistogram h M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  19. Group Cleaner • A group from the Hit Filter may contain hits from more than one track, and maybe some random hits • In Group Cleaner, we exploit the (pT,f0) information to select final track candidates • Similar to Hit Filter: make a 2d-histogram in 1/pT and f0 • Select triplets of Space Points, calculate (1/pT,f0), fill the 2d-histogram • Track candidates consist of bins with Space Points in at least 4 (out of 7) layers • If two track candidates share a significant number of Space Points, keep only the longest candidate (“clone” removal) • (d0=0, zV, 1/pT, h, f0) are good starting parameters for the Kalman fitter • Fitter also performs some outlier removal and can extrapolate tracks into the TRT. M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  20. Performance • Single pT = 40 GeV electron RoI at high Luminosity • Mean number of space points ~ 200 • Mean execution time ~ 1ms1 • ZFinder resolution ~ 200mm • Efficiency ~95% • B physics (low Luminosity), full Silicon Tracker reconstruction • Mean execution time ~10ms 30 Execution Time (ms) 20 10 Linear scaling with occupancy 0 0 2000 4000 6000 8000 10000 Numberof space-points 1 CPU speed of 1GHz M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  21. Performance - Monte Carlo data • 25 GeV electrons, design (high) luminosity with pileup. • Vertex residual for u- and b-jet events. M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  22. Resonance reconstruction • Fully reconstructed mesons from the Dsf p channel. M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  23. First Muon Chambers Electromagnetic Calorimeter Hadronic Calorimeter Beam Line Transition Radiation Tracker ATLAS Combined Test Beam M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  24. M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  25. Test beam performance • 40 GeV muons in magnetic field, 100A solenoid current. • Vertex residual with respect to offline kalman filter algorithm. • Full alignment proceedure still in development stage, • resolution around 200 microns • Efficiencies approaching 100% M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  26. Summary and Outlook • Tracking in the ATLAS Trigger is essential to achieve the physics goals of the LHC, yet must function in a very demanding environment. • Reconstructing the primary interaction coordinate in z to aid subsequent pattern recognition works well … • Latency performance seems acceptable, • Performance in high luminosity, high occupancy data seems acceptable. • Level 2 tracking algorithms successfully operational in test beam • First look at online tracking performance with real data very encouraging. • Work is always ongoing to improve the Level 2 Tracking. • ATLAS will see its first collisions in in 2007 … • Detector and Trigger well on target for readiness within this challenging schedule. M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

  27. And finally … • A big THANK YOU to the organising committee for the excellent choice of venue for the conference dinner. M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS

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