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

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS2 Physics rates at the LHC l LHC pp colider, collision energy 14 TeV l Bunch crossing every 25ns - 40MHz rate l Data storage capability ~200Hz Reduction of ~ : 1 needed! l Peak luminosity: 2x10 33 cm -2 s cm -2 s -1 l Between ~5 and ~25 (soft) pp interactions per bunch crossing Interesting high p T interactions complicated by “pile-up” l ATLAS will use a Three Level, Trigger… l Pipelined, hardware LVL1 l LVL2 and Event Filter farms

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS3 LVL1 LVL2 EF > Latency: 2.5  s (max) > Hardware based (FPGA, ASIC) > Calo/Muon (coarse granularity) > Latency: ~10 ms (average) > Software (specialised algs) > All sub-dets, full granularity > Match different sub-det info > Work in Regions of Interest > Latency: few sec (average) > Offline-type algorithms > Full calibration/alignment info > Access to full event possible ATLAS Trigger-DAQ overview

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS4 The ATLAS Detector Calorimeter Muon Detector Inner Detector

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS5 The ATLAS Inner Detector TRT Pixel Detector SemiConductor Tracker

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS6 Tracking in the ATLAS LVL2 Trigger l 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   ) l Inclusive b-jet tagging (e.g. in MSSM H  hh  bbbb) l LVL2 is the earliest stage where … l Data from tracking detectors is available, l it is possible to combine information from different sub-detectors l Precision tracking at ATLAS predominantly from the Inner Detector: l 3 layer Pixel Detector (3 layers in the end caps) l 4 Layer Semi-Conductor Tracker, SCT (9 layers in the end caps) l Transition Radiation Tracker (TRT) l Two approaches for the Silicon tracking … l Pixel only using Lookup tables - SiTrack, l Complete (all layer) silicon tracking - IdScan.

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS7 LVL2 processing in Regions of Interest (RoI’s) l Most LVL1 accepted events are still uninteresting for physics studies l Decision can be made by further processing only those sections of the detector that LVL1 found interesting l Minimise data transfer to LVL2 processors l Minimize processing time at LVL2 l Average RoI data size ~2% of total event l On average, ~1.6 RoI’s per LVL1 accepted event

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS8 H  

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS9 One bunch crossing One pp interaction

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS10 Dealing witrh “Pileup” events l Exploit differences between interesting (high-p T ) and uninteresting (low-p T ) interactions l Each has a vertex at different z positions along the beamline. l The interesting pp collision should have more high-p T tracks, at least inside the RoI that generated the LVL1 RoI. l Ideally, we would want to l Find the z position of the interesting pp interaction before any track reconstruction l Select only groups of space points consistent with that z l Only then get into combinatorial tracking.

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS11 LVL2 Tracking IdScan Algorithm overview l IdScan (Inner Detector Scan) Algorithm in four stages l Z Finder to find event vertex - histogramming algorithm l Hit Filter for hits compatible with this z - histogramming l Find hit combinations consistent with single tracks. l Track fitting with hits from previous stages - Kalman Filter Fitter, extrapolate to the TRT (See talk by Dmity Emelyanov) ZFinder Space Points Pattern recognition track candidate Tracks Track fitting track candidate z-coordinate

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS12 ZFinder space point selection l Designed to be fast, without the need for detailed tracking High p T tracks are (almost) linear in  –z. Use ( ,z) from pairs of space points from a track for simple linear extrapolation to determine track z 0 l Search for hits consistent with high p T tracks Hits from high p T tracks will lie in a restricted region of  bin hits in thin slices of , (in bins of degrees) l treat each slice (almost) independently l Take all pairs of hits and histogram their extrapolated intersection with beam line. l Fast - reduces hit combinations from lower momentum tracks

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS13 Use narrow phi slices ( degrees)  improves selection of high p T tracks and significantly reduces combinatorial multiplicity. p T ~ p T ~ 20 GeV  ~ 0.3 degrees p T ~ 1 GeV  ~ 5 degrees Curvature in the transverse plane

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS14    From total ~200 hits, only ~7 good electron hits Single electron RoI (0.2x0.2)

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS15 ZFinder – Jet RoI Jet RoI fromWH event

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS16 Zfinder Performance - Single electrons l Resolution for single 25 GeV electron events (with no pile-up) ~200  m, varies with  l Efficiency approaches 100% l In low luminosity events (with pile up) efficiency approaches 95-97%

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS17 The HitFilter All Space Points on a track originating from a given z 0 have the same  when calculated with respect to z 0 … Put all hits in a 2D histogram in ( ,  ) - (currently use 0.005, 2.4 degrees) l Accept hits in a bin if it contains hits in at least 4 (out of 7) layers l Reject all other hits (at high lumi, ~95% of hits are rejected!) l Limits number of combinations l Latency behaviour, approximately linear with number of hits.

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS18   - z view x-y view  -  histogram  z   Pattern Recognition in Pile-up events l If correct vertex is found, track finding efficiency approaches 100%.

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS19 Group Cleaner l 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 (p T,  0 ) information to select final track candidates Similar to Hit Filter: make a 2d-histogram in 1/p T and  0 Select triplets of Space Points, calculate (1/p T,  0 ), fill the 2d-histogram l Track candidates consist of bins with Space Points in at least 4 (out of 7) layers l If two track candidates share a significant number of Space Points, keep only the longest candidate (“clone” removal) (d 0 =0, z V, 1/p T,  0 ) are good starting parameters for the Kalman fitter l Fitter also performs some outlier removal and can extrapolate tracks into the TRT.

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS20 Performance l Single p T = 40 GeV electron RoI at high Luminosity l Mean number of space points ~ 200 l Mean execution time ~ 1ms 1 ZFinder resolution ~ 200  m l Efficiency ~95% l B physics (low Luminosity), full Silicon Tracker reconstruction l Mean execution time ~10ms 1 CPU speed of 1GHz Execution Time (ms) Number of space-points Linear scaling with occupancy 0

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS21 Performance - Monte Carlo data l 25 GeV electrons, design (high) luminosity with pileup. l Vertex residual for u- and b-jet events.

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS22 Resonance reconstruction Fully reconstructed mesons from the D s   channel.

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS23 ATLAS Combined Test Beam Transition Radiation Tracker First Muon Chambers Hadronic Calorimeter Electromagnetic Calorimeter Beam Line

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS24

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS25 Test beam performance l 40 GeV muons in magnetic field, 100A solenoid current. l Vertex residual with respect to offline kalman filter algorithm. l Full alignment proceedure still in development stage, l resolution around 200 microns l Efficiencies approaching 100%

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS26 Summary and Outlook l Tracking in the ATLAS Trigger is essential to achieve the physics goals of the LHC, yet must function in a very demanding environment. l Reconstructing the primary interaction coordinate in z to aid subsequent pattern recognition works well … l Latency performance seems acceptable, l Performance in high luminosity, high occupancy data seems acceptable. l Level 2 tracking algorithms successfully operational in test beam l First look at online tracking performance with real data very encouraging. l Work is always ongoing to improve the Level 2 Tracking. l ATLAS will see its first collisions in in 2007 … l Detector and Trigger well on target for readiness within this challenging schedule.

TIME th October, Zurich M.Sutton - A Fast Level 2 Tracking Algorithm for ATLAS27 And finally … l A big THANK YOU to the organising committee for the excellent choice of venue for the conference dinner.