Normal text - click to edit HLT tracking in TPC Off-line week 41 2007 Gaute Øvrebekk.

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Presentation transcript:

Normal text - click to edit HLT tracking in TPC Off-line week Gaute Øvrebekk

Normal text - click to edit Outline Overview ClusterFinder/Tracker. –Methods/Algorithms. –Results for Pb+Pb. Preparation for p+p run: –Reconstruction efficiency. –Benchmark on the HLT-Cluster.

Normal text - click to edit Multiplicities and occupancies What to expect? Extreme assumption: dN ch /dy=8000 Extrapolations from RHIC: dN ch /dy= TPC occupancy for different multiplicities

Normal text - click to edit TPC tracking methods Cluster finding Reconstruct space points from 2D clusters Track reconstruction Connect space points into tracks and fit them to a model (helix) Sequential tracking Alternative/Additional tools: ¤ Hough Transform ¤ Cluster deconvoluter and refitter

Normal text - click to edit Input: ADC-sequences above threshold Cluster Finding Cluster Finder - Simple sequence matching between neighboring pads - Centroids calculated as weighted mean of ADC-values Simple deconvolution scheme: Split clusters at local minima

Normal text - click to edit ClusterFinder Reading all data to memory Finding Cluster Candidates Finding Clusters A Cluster Candidate is defined to have signals in a minimum of two consecutive timebins on one pad. examples: data(timebin)=[-1,-1,-1,3,-1,-1,6,23,56,16,3,-1,-1,-1,3,-1] Calculates: Total Charge Time (Center of gravity) data(timebin)=[-1,-1,-1,3,-1,-1,6,23,56,16,14,24,76,19,3,-1,-1,3,-1] Deconvoluted when signal falls and rises again.

Normal text - click to edit A Cluster is defined to have Cluster Candidates in minimum two consecutive pads, where the absolute difference in time for the two Cluster Candidates is <=1. example: Pad 33 has Cluster Candidates with time: [ 70, 300, 390 ] Pad 34 has Cluster Candidates with time: [ 13, 245, 390 ] Pad 35 has Cluster Candidates with time: [ 12, 167, 391 ] Pad 36 has Cluster Candidates with time: [ 13, 168, 391, 440 ] After this initial step we look for single timebin signals(tails) in firstpad-1 and lastpad+1 Similar deconvolution scheme in pad direction.

Normal text - click to edit An On-Line tracker needs to: ¤ be robust ¤ be fast ¤ find primaries at high and intermediate pT ¤ …

Normal text - click to edit Track Finder - Conformal mapping Real space Conformal space - “Follow-your-nose” Build tracks from outer to inner TPC-radius Input: 3D space points Tracking Algorithm

Normal text - click to edit Performance for Pb+Pb events Efficiency = Found “good” tracks Generated “good” tracks dN ch /d  dN ch /d  Tracking efficiencies vs pt Tracking efficiency Has been tested on Pb-Pb. Published in 2004

Normal text - click to edit Sequential tracking - secondaries ¤ Efficiency of 80% for Kaons and Lambdas. ¤ Can be improved by a second tracking pass, taking input all unassigned clusters from the first pass. No vertex constrain is imposed on the track follower (conformal mapping done with respect to the first associated cluster on track)

Normal text - click to edit Sequential tracking – dataflow Cluster Finder Tracker Finder/Fitter Global Merging 36 Sectors ESD Writer

Normal text - click to edit Simulation of 1000 π GeV/c < p < 5 GeV/c 60 < theta < 120 Preparation for p+p run

Normal text - click to edit Primary π + KineHLT For HLT magnetic field was not set in ESD file. Momentum is correct, but wrong in drawing.

Normal text - click to edit HLT and Offline divided by simulated Overall Efficiency for primaries : ¤ HLT: 95% ¤ Offline: 94%

Normal text - click to edit How many clusters are associated to a track Total number of clusters on tracks: HLT: Offline:

Normal text - click to edit Pythia Events Used ConfigPPR.C kPythia6

Normal text - click to edit Number of pads in a Cluster HLTOff-LinePadRow Crossings Total Number of Clusters ???

Normal text - click to edit HLT divided by Offline. Efficiency.

Normal text - click to edit How many clusters are associated to a track. Off-Line HLT

Normal text - click to edit Benchmark on the HLT-Cluster Setup for one sector 6 ClusterFinders running in parallel on 6 CPUs 1 Tracker running on one CPU. Results (old decoder) ClusterFinder: 240 Hz Tracker:~200 Hz Stable run for 6 hours.

Normal text - click to edit ToDo Further study of performance. Comparison to MC and Offline. Some open questions -> Next slides.

Normal text - click to edit GeV Questions for the offline Tracker. Observation: Tracks pointing to the same MC track (Offline reconstruction in aliroot v4-06-Release, KinkIndex > 0 rejected) Explanation?

Normal text - click to edit Primary π +, p t >0.7GeV/c (TPCrefit, ITSrefit, HEAD ) trackTPC label# clustersp t (GeV/c)kink index (0)

Normal text - click to edit Technical questions What does each negative kink index mean? Which of 2 kink indices assigned to the same track do we keep? Why are MC primaries more than physical primaries? stack->GetNprimary() and stack->IsPhysicalPrimary(index)==kTRUE

Normal text - click to edit Transverse momentum of HLT, Off-line and Simulated

Normal text - click to edit Physics triggers Selecting events containing: - Jets - Open charm - J/  and   - Complete event selection/rejection - Region-of-interest readout

Normal text - click to edit TPC tracking methods Cluster finding Reconstruct space points from 2D clusters Track reconstruction Connect space points into tracks and fit them to a model (helix) Iterative tracking Sequential tracking Cluster finder Track finder Sequential tracking Space points Track seed finder Iterative tracking Sequential tracking Track fitter on tracks Track candidates / fitter Cluster shape is a function of track parameters Iterative tracking

Normal text - click to edit Sequential tracking – dataflow Front-End Processors: HLT-RORC (Readout Receiver Card) Sector processors Global/event processors Optical links ESD Writer

Normal text - click to edit Sequential tracking – computing requirements dN ch /d  CPU-time [s] #CPU CPU-time [s] #CPU Pentium III, 800 MHzPentium 4, 2800 MHz #CPU = Equivalent number of required 200 Hz processing rate CF Tr. Find.Tr. Fit. Tr. Merg. Gl. Tr. Merg.

Normal text - click to edit Hough Transform ?????

Normal text - click to edit Transverse momentum for HLT, Offline and Simulated

Normal text - click to edit compression techniques ???