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High Level Trigger of M uon Spectrometer

High Level Trigger of M uon Spectrometer. Indranil Das Saha Institute of Nuclear Physics. Description of the problem. Signal. Background. y. L0 Trigger by Muon Trigger. J/ Ψ  μ + μ - Y  μ + μ - B  μ + / μ - + X D  μ + / μ - + X. Muons from π and K. Z.

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High Level Trigger of M uon Spectrometer

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  1. High Level Trigger of Muon Spectrometer Indranil Das Saha Institute of Nuclear Physics

  2. Description of the problem Signal Background y L0 Trigger by Muon Trigger J/Ψ μ+ μ- Y  μ+ μ- B  μ+/μ- + X D  μ+/μ- + X Muons from π and K Z (for hadronic background) Continue hardware and software trigger….. P2 = (P1 + P2)2

  3. Description of the problem • For ALICE Muon Spectrometer L0 (hardware trigger) == Hits in trigger station. + Track pointing to origin + Option for transverse momentum (pT) selection. • Muons coming from Pions and Kaons decay have low pT . • Thus to reduce the background two pTcuts of 1 GeV or 2 GeV has been planned to clean invariant mass spectrum of J/Ψ and Y. pz p py pT px Software cut improves the result, so why not online software cut ?

  4. Description of the problem HLT : Thus, on top of the hardware trigger a software trigger is applied, which is called High Level Trigger (HLT). The HLT is an online system that provides the common facilities (i.e. Input/Output Link, PC farm for analysis) and executes the triggering algorithms (full reconstruction) developed for different detectors. Main motivation of Dimuon HLT: In case of Muon Spectrometer, HLT algorithms are supposed to improve the pTcuts (1 GeV or 2 GeV at most, depending on beam luminosity) as defined by Muon Trigger Station (L0 Trigger), which are important remove the combinatorial background of low momentum particles to clear the J/Ψ and Y signals. A typical processing rate of 1 kHz is the design requirement of muon HLT for heavy ion Pb-Pb collisions. How do we deal online data in reality ?

  5. ALICE data flow in online mode DAQ Rawdata (GRID) HLTESD Detector HLT Offline Clusters HLTESD Tracks Clusters Physics Trigger {Level 0 [L0]} Tracks Event Display ESD But then it is very straight forward right ?

  6. Description of the problem • One simulated Pb-Pb event needs few seconds for offline reconstruction (official physics analysis software) and therefore this can not be used for online analysis. • Thus, a new algorithm has been developed which will perform online analysis of data and satisfies, • A online processing component has to be robust (24x7) • It is to be fault tolerant against input data stream • It has to provide results of appreciable quality • It has to be fast enough so that the rest of experimental component does not wait for HLT If any of above conditions are violated dimuon part of HLT is excluded from the experimental run. Data rate of 500 MB/s for 1 kHz trigger rate with hit multiplicity ~ 300 Accuracy as good as offline reconstruction within the time limit of 1 ms

  7. Outline • Development of the Algorithm • Hit Reconstruction (Thesis work) • Trigger Reconstruction (UCT + Cagliary) • Track Finding (Thesis work) • Cellular Automata • Kalman Filtering • Validation with the simulated data (Thesis work) • Implementation in HLT PC-Cluster and validation with cosmic data (Thesis work) • Online display of LHC p-p data (Thesis work) • Ongoing Analysis of p-p data (Thesis work) At first the Hit Reconstruction algorithm…..

  8. A fast Algorithm • The charges are found to spread over 2 or 3 pads along a direction in most of the cases => one cluster. • Each cluster is characterized by one Central Pad (Pad with maximum charge for the given cluster). • Thus, to generate reconstructed hits, it is not essential to make clusters but only identification of Central Pad is sufficient. • Once the central pad is found the reconstructed Y hits in bending plane is calculated using centre of gravity method over three pads around the central pad. • Above method is repeated for non bending plane to find out reconstructed X . • Finally the bending and non bending hits are merged to form reconstructed X and Y. Comparison with offline…

  9. Comparison of Simulation Results Fine !!! What about tracking ?

  10. Charged particle track y Z MCS and E.Loss Correction Cellular Automata St. line track Kalmanχ2 match Trigger Seed

  11. Full Tracker Scheme Linear Extrapolation in St4/5 A trigger tracklet can be formed with the trigger seed, which is extrapolated to find the ROI in St4/5. the hits inside those ROI are checked for the alignment with the trigger tracks and added to extrapolate the tracks. Trigger Seed The Trigger chamber issues a Trigger when at least three out of four planes are fired along linear direction Kalman Chi2Test The tracksegs in the St4/5 are extrapolated through the magnetic field using Kalman filter to meet the trackseg In St1/2. CA in St1 and St2 At First the small tracklets between the two chambers of a given station are formed. Then the tracklets from different stations are collected to make a track segment in the forward half of the Spectrometer. Extrapolate The tracks are then extrapolated to vertex to incorporate energy loss and MCS (multiple Coulomb Scattering) in the Muon absorber . What is Cellular Automata ?

  12. Cellular Automaton Cell Creation Cell is a small tracklet between the two chambers of a given station. The tracklet object contains three pointers, one corresponds to its rank in the track and the rest two points towards each other Connect Tracks The cells from different stations are collected into a track from the Muon Trigger stations towards station1 with certain strict boundary condition. How does Kalman Filter Works ?

  13. Kalman Filtering Process Initial Estimate Measurement Kalman Gain Project to k+1 Update Estimate Update Covariance Projected Estimate Result on simulated data….

  14. Transverse Momentum Reconstruction at a given PT For other delta PT values…..

  15. Comparison of Different Tracking Approach How does it fit to the PTefficiency plot ?

  16. PT Cut Efficiency Pause and discuss…. Offline testing is not same as online implementation….

  17. First Track in Muon Spectrometer of ALICE was detected by SINP group Run 24841 March 3, 2008 And many more…..

  18. Event Snapshots of ALICE Control Room ALICE Control Room (ACR) First online snapshot of muon track in 7 TeV(highest energy) pp collision beam at record luminosity (~ 6 × 1028 cm-2 s-1), processing at a rate of 700 Hz Run 119842

  19. Not Only Display, but Quality Assurance(QA) as well………. Cluster Dist. Attached to the tracks PT Distribution Bingo!! Real Time Vertexing !!!!!! Online Inv. Mass Distribution

  20. Analysis of the quality of the events….. Total ADC Charge per Data Link Number of Clusters per Data Link Trigger Type as declared by Trigger Chamber Charge Ratio in the Two Planes of the Detectors

  21. Monitoring even deeper….. Cluster size distribution Cluster Charge Distribution Offline Comparison

  22. Ongoing Analysis of p-p data The performance plots are shown for the Full-Tracker on data from 54 runs from LHC10d: 126097 12608 126087 126081 126078 126073 126008 126007 126004 125855 125848 125847 125844 125843 125842 125632 125630 125628 125296 125292 125186 125156 125139 125134 125131 125101 125100 125097 125085 125083 124608 124607 124606 124605 124604124603 124600 124388 124380 124378 124374 124371 124367124364 124362 124360 124359 124358 124355 124187 124186 124183 122375 122374 Preliminary Preliminary How does L0, Offline, HLT triggered mass spectrum look like …. ?

  23. Any track passes 1.0 GeV cut

  24. Summary and Future Plan Successful development, simulation testing, onlineimplementation, real-time execution and validation by physics analysis of the Hit Reconstruction and Track Reconstruction algorithms Histogram incorporation to QA for global run characteristics. Continue Validation test with p-p and Pb-Pb collision.

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