Tracking at the ATLAS LVL2 Trigger Athens – HEP2003 Nikos Konstantinidis University College London

2Nikos KonstantinidisTracking at the ATLAS LVL2 Trigger Outline Introduction Introduction ATLAS Trigger StrategyATLAS Trigger Strategy Tracking at LVL2Tracking at LVL2 The IDScan tracking package The IDScan tracking package The algorithmsThe algorithms PerformancePerformance Conclusions – Outlook Conclusions – Outlook

3Nikos KonstantinidisTracking at the ATLAS LVL2 Trigger Triggering at the LHC Challenge 1: Challenge 1: Bunch crossing every 25ns => rate: 40MHzBunch crossing every 25ns => rate: 40MHz Data storage capability ~100HzData storage capability ~100Hz Must select online a couple events in a million!!! Online background rejection of ~6 orders of magnitude! Challenge 2: Challenge 2: Peak luminosity: 2x10 33 (low) (high)Peak luminosity: 2x10 33 (low) (high) ~5 ~25 pp interactions per bunch crossing ~5 ~25 pp interactions per bunch crossing Luminosity falls by a factor ~2 over a fill (~10hours) Luminosity falls by a factor ~2 over a fill (~10hours) Interesting (high p T ) pp interaction complicated by pile-up Very annoying for tracking (increases combinatorics)

4Nikos KonstantinidisTracking at the ATLAS LVL2 Trigger ATLAS Trigger Strategy

5Nikos KonstantinidisTracking at the ATLAS LVL2 Trigger ATLAS Trigger – Overview LVL1 LVL1 Uses Calorimeters & Muon Trigger Stations (coarse granularity) LVL2 LVL2 Uses LVL1 Regions of Interest (RoI), so only a small fraction of the event data is accessed InDet tracking avail. Combines sub-dets Full granularity Event filter Event filter Refined, offline-type reconstruction, with access to calibration & alignment data

6Nikos KonstantinidisTracking at the ATLAS LVL2 Trigger Region of Interest x-y view -z view

7Nikos KonstantinidisTracking at the ATLAS LVL2 Trigger LVL2 Tracking is needed for Tracking is needed for Single, high-p T electron/muon identificationSingle, high-p T electron/muon identification Match tracks to info from outer detectors Match tracks to info from outer detectors B Physics (at low lumi? budget permitting?)B Physics (at low lumi? budget permitting?) Exclusive reconstruction of golden decays (e.g. B–>) Exclusive reconstruction of golden decays (e.g. B–>) b-jet tagging (e.g. in MSSM H –>hh –> bbbb)b-jet tagging (e.g. in MSSM H –>hh –> bbbb) All must be done in ~10ms All must be done in ~10ms Must deal with combinatoricsMust deal with combinatorics At high luminosity: ~20K space points in the Si TrackersAt high luminosity: ~20K space points in the Si Trackers

8Nikos KonstantinidisTracking at the ATLAS LVL2 Trigger The Si Trackers of ATLAS

9Nikos KonstantinidisTracking at the ATLAS LVL2 Trigger The IDScan algorithms A sequence of four algorithms for pattern recognition & track reconstruction using 3D space points. A sequence of four algorithms for pattern recognition & track reconstruction using 3D space points. Basic idea: Basic idea: Find z-position of the interesting (high-p T ) pp interaction before any track reconstructionFind z-position of the interesting (high-p T ) pp interaction before any track reconstruction Select only groups of space points consistent with the above zSelect only groups of space points consistent with the above z

10Nikos KonstantinidisTracking at the ATLAS LVL2 Trigger ZFinder Relies on: Relies on: Tracks are straight lines in –z. Using the (,z) from a pair of space points of a track, you can determine its z 0 by simple linear extrapolationTracks are straight lines in –z. Using the (,z) from a pair of space points of a track, you can determine its z 0 by simple linear extrapolation High-p T tracks are almost straight lines in –.High-p T tracks are almost straight lines in –. Steps: Steps: Make very thin slices in  ( degrees)Make very thin slices in  ( degrees) In each slice, make all pairs of space points from different layers, calculate z 0 by linear extrapolation and fill a 1D histogram with thisIn each slice, make all pairs of space points from different layers, calculate z 0 by linear extrapolation and fill a 1D histogram with this The bin with the max. number of entries corresponds to the z 0 you are looking forThe bin with the max. number of entries corresponds to the z 0 you are looking for

11Nikos KonstantinidisTracking at the ATLAS LVL2 Trigger ZFinder – Example Jet RoI from WH(120GeV)

12Nikos KonstantinidisTracking at the ATLAS LVL2 Trigger HitFilter Given this z 0, all space points of a track originating from z 0 will have the same  Given this z 0, all space points of a track originating from z 0 will have the same  Steps: Steps: Put all space points in a 2D histogram in (,)Put all space points in a 2D histogram in (,) Accept all space points in a bin if this bin contains space points in at least 5 (out of 7) different layersAccept all space points in a bin if this bin contains space points in at least 5 (out of 7) different layers Reject all other space pointsReject all other space points No combinatorics => linear time behaviour No combinatorics => linear time behaviour Returns groups of hits Returns groups of hits

13Nikos KonstantinidisTracking at the ATLAS LVL2 Trigger HitFilter – Example -z view x-y view view  histogram

14Nikos KonstantinidisTracking at the ATLAS LVL2 Trigger Performance (I) Single e (p T =40GeV) RoI at high L ( x  = 0.2 x 0.2) Single e (p T =40GeV) RoI at high L ( x  = 0.2 x 0.2) ~ 250 ~ 250 ~1ms* ~1ms* ZFinder resolution ~ 180mZFinder resolution ~ 180m Efficiency ~98%Efficiency ~98% B physics (low L ) full Si Trackers reconstruction B physics (low L ) full Si Trackers reconstruction ~20ms* ~20ms* Execution Time (ms) # of space-points in Event Linear scaling with occupancy 0 *projected to CPU speed of 4GHz

15Nikos KonstantinidisTracking at the ATLAS LVL2 Trigger Performance (II) Using 2 rather than 3 pixel barrel layers Using 2 rather than 3 pixel barrel layers Only necessary to change the min. number of space points required to make a track, from 5 (out of ~7) to 4(out of 6)Only necessary to change the min. number of space points required to make a track, from 5 (out of ~7) to 4(out of 6) Algorithms conceptually simple => Flexible => Robust

16Nikos KonstantinidisTracking at the ATLAS LVL2 Trigger Example – Electron RoI   

17Nikos KonstantinidisTracking at the ATLAS LVL2 Trigger IDScan – Virtues Modular –> flexible –> robust Modular –> flexible –> robust Fast and linear: t ~ (# of space points) Fast and linear: t ~ (# of space points) Suitable for all tracking needs of LVL2 Suitable for all tracking needs of LVL2 No DetDescr dependence: only space points No DetDescr dependence: only space points Uniform treatment of barrel/endcaps Uniform treatment of barrel/endcaps Uniform treatment of pixel/SCT Uniform treatment of pixel/SCT

18Nikos KonstantinidisTracking at the ATLAS LVL2 Trigger Summary – Outlook Triggering has a central role at the LHC; the physics reach of ATLAS (and CMS) depends on it critically Triggering has a central role at the LHC; the physics reach of ATLAS (and CMS) depends on it critically Tracking at LVL2 is a real challenge, especially at high luminosity Tracking at LVL2 is a real challenge, especially at high luminosity Determining the z-position of the interesting pp interaction prior to any track reconstruction and then rejecting all space points that cannot be due to tracks from that z seems to work best Determining the z-position of the interesting pp interaction prior to any track reconstruction and then rejecting all space points that cannot be due to tracks from that z seems to work best Still space for novel ideas to improve the ATLAS physics potential and exploit the physics at the LHC optimally Still space for novel ideas to improve the ATLAS physics potential and exploit the physics at the LHC optimally