Recent Improvements in Track Reconstruction

Transcription

1 Recent Improvements in Track Reconstruction Boris Mangano (University of California, San Diego) on behalf of the tracking group (Tracker Project)

2 Outline one slide description of track reconstruction in CMS improvements in tracking - description - effects on tracking performance - effects on physics evolution of timing performance over past CMSSW releases

3 Tracking modules Trajectory seeding Trajectory building Trajectory fitting Initial estimate of trajectory parameters from a small subset of tracker measurements (hits on seeding layers). An iterative process which collects all the measurements associated to the same charged particle. Estimate of final track parameters from the fit of the full set of measurements associated to the same charged particle. Track collection filtering new Removal of ghost tracks (fakes) + quality filter.

4 Porting of code from ORCA ORCA performance global efficiency - - single muon, pt = 1 GeV - - single muon, pt = 10 GeV - - single muon, pt = 100 GeV CMSSW_1_3_X performance ORCA tracking performance ~ re-obtained with CMSSW_1_3_X release (beginning of 2007) Actually some new features were already introduced: e.g. mixed seeding gave better tracking efficiency in the high eta region.

5 New Feature: Tracking with overlaps Original trajectory builder was able to collect only one measurement per layer per track. Nevertheless the tracker has overlapping sensors: sometimes there is more than one measurement produced by the same charged particle on the same tracker layer

6 New Feature: Tracking with overlaps New trajectory builder is able to collect hits on all the overlapping sensors of the CMS tracker hit collection efficiency: from ~88% to 98% hit collection efficiency building with overlap new trajectory builder standard building old trajectory builder Thanks to: - W.Adam (Wien) - P.Lenzi (INFN Florence) fully integrated and used by default in CMSSW_1_7_X

7 New Feature: Handling of Magnetic Field In-Homogeneities During Track Fit average (p t reco - p t sim )/p t error - - single muon, pt = 1 GeV - - single muon, pt = 10 GeV - - single muon, pt = 100 GeV approximate handling of magnetic field inhomogeneities produces a bias in the reconstructed value of transverse momentum Effect is apparent in high eta region of the tracker

8 New Feature: Handling of Magnetic Field In-Homogeneities During Track Fit average (p t reco - p t sim )/p t error Track parameters propagator based on Runge-Kutta method allows to properly take into account the magnetic field inhomogeneities during the final fit - - single muon, pt = 1 GeV - - single muon, pt = 10 GeV - - single muon, pt = 100 GeV Thanks to: - T.Todorov (now in ATLAS) - M.Mulders (CERN) fully integrated and used by default in CMSSW_1_8_X

9 New Feature: Handling of Magnetic Field In-Homogeneities During Track Fit J/ψ reconstructed mass mean = GeV plot by M.Cepeda (CIEMAT) Bias in the reconstructed J/ψ mass is completely removed thanks to the Runge-Kutta propagator

10 Additional New Features: Impact on Quality of Reconstructed Track average χ 2 /ndf CMSSW_1_7_X QCD sample 7 independent new features of track reconstruction have exceptionally improved the χ 2 of reconstructed tracks CMSSW_1_7_0 + 7 fixes/improvements Individual contributions are shown in the following slides

11 Additional New Features: Impact on Quality of Reconstructed Track average χ 2 /ndf default tracking in CMSSW_1_7_X QCD sample + updated material budget parameterization for track fitting Thanks to: - A.Bocci (SNS Pisa) - W.Adam (Wien)

12 Additional New Features: Impact on Quality of Reconstructed Track average χ 2 /ndf default tracking in CMSSW_1_7_X QCD sample + better track angle hypothesis during clusters re-fitting Thanks to: -G.Cerati (INFN Milano) -C.Genta (INFN Florence)

13 Additional New Features: Impact on Quality of Reconstructed Track average χ 2 /ndf default tracking in CMSSW_1_7_X QCD sample + splitting of matched hits before final fit of the track Thanks to: -G.Cerati (INFN Milano) -C.Genta (INFN Florence)

14 Additional New Features: Impact on Quality of Reconstructed Track average χ 2 /ndf default tracking in CMSSW_1_7_X QCD sample + Runge-Kutta propagator during final fit of the track Thanks to: - T.Todorov (now in ATLAS) - M.Mulders (CERN)

15 Additional New Features: Impact on Quality of Reconstructed Track average χ 2 /ndf default tracking in CMSSW_1_7_X QCD sample Thanks to: -M.Swartz, D.Fehling, G.Giurgiu, P.Maksimovic (JHU) - V.Chiochia (University Zurich) + new pixel parameters estimator based on templates review of the several benefits for tracking due to new pixel CPE are shown in CMS NOTE

16 Additional New Features: Impact on Quality of Reconstructed Track average χ 2 /ndf default tracking in CMSSW_1_7_X QCD sample Thanks to: G.Cerati (INFN Milano) + tool for rejection of outlier hits Impact of outlier rejection on tracking efficiency, fake rate and estimation of parameters at vertex will be described in a note, currently in preparation

17 Additional New Features: Impact on Quality of Reconstructed Track average χ 2 /ndf default tracking in CMSSW_1_7_X QCD sample + finer description of material budget for final fit of tracks Thanks to: A.Bocci (SNS Pisa)

18 new features: track collection filter based on vertex compatibility CMSSW_16X old standard tracking QCD sample efficiency and fake for pt > 0.9 GeV old standard tracking old standard tracking + new track collection filter old standard tracking + new track collection filter selection is based on d0 and dz (and significances) respect to reconstructed primary vertex Thanks to: -P.Azzurri (SNS Pisa) -M.Pioppi, P.Janot (CERN) -F.Ambroglini (INFN Perugia) Fake rate is almost completely removed without spoiling the track reconstruction efficiency

19 New Pixel CPE and New Track Filter: effects on b-tagging mis-tag QCD sample track counting, 2nd track (w/o new CPE) track counting, 2nd track (new pixel CPE) track counting, 3rd track (w/o pixel CPE) track counting, 3rd track (new pixel CPE) Tests on b-tagging by M.Swartz, D.Fehling, G.Giurgiu, P.Maksimovic (JHU) and T.Boccali (INFN Pisa) Impact on btagging performance are impressive for both track counting configurations. The btagging algorithms have not been changed b-tagging efficiency

20 new features: track collection filter based on vertex compatibility cut-based loose electrons: isolation performance studies and plot by M.Lebourgeios (UCSD) Lowering the tracking fake rate, the electron isolation performance improves (without any changes in the isolation algorithm itself!)

21 new features: seeder based on triplets and vertex-constrained hit pairs QCD sample Thanks to: -M.Konecki (Warsaw) old standard tracking new tracking configuration -G.Boudoul, T.Legrand (IPNL Lyon) -G.Petrucciani (SNS Pisa) normalized distributions New seed generator is based on triplets of hits + hit pairs constrained by the primary vertex. Both high efficiency and high seed collection purity are achieved pt spectrum of reconstructed tracks can extended toward lower values: up to +65% reconstructed track increasing only slightly the algorithm timing

22 average time/event (secs) Evolution of Timing Performance Almost factor 3 reduction in timing: SMatrix migration and C++ code optimization (V.Innocente, G.Petrucciani) Almost same timing, despite +65% reconstructed tracks (thanks to new seed generator): minimum Pt from 0.9 GeV to 0.3 GeV all tests done with: - BJets_Pt_ sample w/o PU GHz E5335 intel processor - gcc345 compiler

23 Evolution of Timing Performance mode old code (before June 2007) global unpacking regional unpacking unpacking on-demand SiStrip clusters unpacking time (ms) sample: single tau - time is per event. Averaged on events which pass L2.5 Thanks to: - M.Wingham, N.Cripps, R.Bainbridge (Imperial college) - D.Giordano (INFN Bari) More than a factor 100X in reducing the timing of tracker clusters unpacking. Clear impact on HLT performance - J-R. Vlimant (UCSB)

24 Conclusion Last 12 months have been rich of activities related to track reconstruction The current status of the tracking software is well beyond what was available after the porting from ORCA: - almost no fake tracks (from 20% to few percent) - low pt tracking (from 0.9 GeV to 0.3 GeV) - faster reconstruction (factor 2 in speed, despite the more sophisticated algorithms) Many additional ideas are under investigation and development. Current studies are more real tracker conditions oriented.

25 Conclusion performance for 10pb-1 conditions are expected to be under control: -resolutions of parameters at vertex are necessarily degraded - efficiency and fake rate are almost exactly the same tracking for ideal conditions tracking for alignment conditions after 10pb-1 Higgs -> GammaGamma sample