Notes on Tracking
Tracking performance study with Boris
Boris's tasks
Task 1
Task: Learn how to create a root tree with simple track variables.
Status: Complete
- Screenshot of myTrackVariables:
Task 2
Task: Learn how to plot the simple variables in the root tree using TBrowser and the mouse. Do simple histogram manipulations as fitting, re-binning and adding labels from the graphical interface.
Status: Complete
- Using TBrowser and graphical fit options:
Task 3
Task: Repeat Task 2 using a root macro
- Open your root file which contains the root tree.
- Access the root tree.
- Plot one simple variable (in this case z_{0}).
- Fit the histogram.
- Get the fit parameters back from the histogram object. You should be able to write these to a file if necessary.
Status: Complete
- Using a macro to plot and fit z_{0}:
- Exercise in root fitting.:
Task 4
Task: Add additional variables to the root tree related to the simTracks. Use the same variables as reco::track variable tree.
Status: Incomplete
Task 5
Task: Learn how to associate a reco::Track to a simTrack and vice versa. After you learn that, we can add to root tree some more interesting numbers like the residual of track parameters:
- deltaTIP: recotrack_transverseImpactParameter - simTrack_transverseImpactParamer
- ΔpT/pT
- Δφ
- Δη
- fraction of collected rechits with respect to the simulated ones.
- purity of the collected rechits
- track reconstruction effeciency and fate rate flag
- etc.
Status: Incomplete
Task 6
Task: Plot all the values stored in the tree at point 5 versus other simtrack and reco::track parameters
- efficiency vs η (you can compare with official plot)
- efficiency vs pT
- resolution of pT vs purity of the collected hits (another new plot)
- etc.
Status: Incomplete
Task 7
Task: After we have arranged all the previous machinery for a single track sample, we will move to a real multitrack sample to see what happens to track reconstruction inside a collimated jet or for a very energetic μ.
Status: Incomplete
Plot's for Prof. Sharma
For a sample of 50,000 Z→μμ events:
- d0 of Tracks with PT > 15 GeV and χ2/d.o.f. < 4:
- d0 of Tracks with PT > 15 GeV and χ2/d.o.f. ≥ 4:
- z0 of Tracks with PT > 15 GeV and χ2/d.o.f. < 4:
- z0 of Tracks with PT > 15 GeV and χ2/d.o.f. ≥ 4:
Plot for Boris
- This is from 50k Z→μμ events with PT > 15 GeV and χ2/d.o.f. < 4 and number of valid hits > 8:
Track Quality Study
Various kinematical variables of reconstructed tracks Tracks.
No Cuts (RecoTrack)
I loop over all reconstructed tracks in an event and plot the following kinematical variables and detector information: P
T, η, φ, d
0, z
0, and the number of valid hits in the tracker.
Matched vs Unmatched.
In each event I have two loops:
- The first loop is over the RecoTracks in each event. Next I define a match as a RecoTrack that has a corresponding SimTrack associated by hits using CMSSW_1_3_1 TrackAssociatorByHits that Boris showed me. Unmatched is defined as NOT Matched.
- The Second loop is over the SimTracks in each event. Next I define a match as a SimTrack that has a corresponding RecoTrack associated by hits again using CMSSW_1_3_1 TrackAssociatorByHits. Unmatched is defined as NOT Matched.
With Cuts
- The following cuts were applied:
- |η| < 2.5
- # valid hits > 7
- |d0| < 1 mm
- |z0| < 30 cm
- χ2/d.o.f. < 10
- RecoTracks that have an associated SimTrack.
- RecoTracks that do NOT have an associated SimTrack.
Δ = Reco - Sim.
- Calculated the difference between RecoTrack and SimTrack variables.
Pull = ΔVariable / VariableError. Note P
T error has not been implemented yet and I'm not sure that Δφ has been calculated correctly.
- Pull of Various Kinematical Variables:
--
RyanKelley - 01 Aug 2007