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r1 - 11 Mar 2007 - 13:45:17 - CarlosEscobarYou are here: TWiki >  Atlas Web  >  SiliconForwardTracker > SiAlignment > GlobalChi2_CSC_Alignment

GlobalChi2 CSC Alignment

CSC Track Parameters:

  • Perigee and Beam Spot: CSC multimuons have been generated at (0,0,0) whith some spread, while the detector (PIX and SCT) has been shifted. All these conditions have an impact on the impact parameter and perigee of the reconstructed tracks. In the reconstruction the perigee is computed w.r.t. the origin (0,0,0) instead of w.r.t. the primary vertex.
  • Alignment Tests
  • Results comparing track parameters using the Full ID, Si Only and TRT Only hits on track [Tracking: newTracking (KalmanFitter)]:
    • Misalignment Unknown (Nominal Geometry):
      • Full ID (Pixel+SCT+TRT) (from the TrkValidation ntuple - Unbiased residuals): plots
      • Si Only (Pixel+SCT) (from the TrkValidation ntuple - Unbiased residuals): plots
      • Comparison plots (from the InDetAlignNt - Biased residuals):
        • track parameters: plots
        • Pixel and SCT biased residuals: plots

  • Results comparing the differences between the use of the Error Scaling in each case (using the TrkValidation ntuple - Unbiased residuals):
    • Misalignment Unknown (Nominal Geometry):
      • iPatRec - No Error Scaling - 50k events: plots
      • iPatRec - Error Scaling - 25k events: plots
    • Misalignment Known (Ideal Geometry):
      • iPatRec - No Error Scaling - 25k events: plots
      • iPatRec - Error Scaling - 50k events: plots
      • newTracking (GlobalChi2Fitter) - Error Scaling - 50k events: plots

Update on Global Chi2 CSC alignment

Results using the Double Cone Geometry (2328 barrel modules - 13968 DoFs). Using our own ntuple (Biased residuals):

Misalignment Known (Ideal Geometry)

Results using the Double Cone Geometry (2328 barrel modules - 13968 DoFs). Using our own ntuple (Biased residuals):

  • Using newTracking (GlobalChi2Fitter): in progress

Misalignment Unknown (Nominal Geometry)

Results using the Double Cone Geometry (2328 barrel modules - 13968 DoFs). Using our own ntuple (Biased residuals):
  • Using iPatRec:
    • Alignment Results (07/March/2007):
      • Iteration 0 (99150 events - 394995 tracks - 3728284 hits):
        • Summary plots: ps.gz pdf
        • Initial positions for Iter0 (before alignment): (root)
      • Iteration 1 (99150 events - 398967 tracks - 4316909 hits):
        • Summary plots: ps.gz pdf
        • Initial positions for Iter1 (before Iter0): (root)
      • Iteration 2(5000 events - 20160 tracks - 220937 hits):
        • Summary plots: ps.gz pdf
        • Initial positions for Iter2 (before Iter1): (root)
    • Comparison plots of Iterations 0, 1, 2. Only for tracks laying within the DoubleCone acceptance region. The ideal case is also included and serves as reference. So far, in all iterations, error scaling has been applied.
      • Track parameters: plots. In the reconstructed Pt, one may observe that the Q+Q- assymmetry decreases slihgtly after each iterarion. It does not clear, but the trend is a monotonical drecrease. Whilst in the equivalent plots extracted using newTracking (GlobalX2Fitter) it steadily grows.

  • Using newTracking (GlobalChi2Fitter):
    • Alignment Results (21/Feb/2007):
      • Iteration 0 (99150 events - 341604 tracks - 2952281 hits):
        • Summary plots: ps.gz pdf
        • Initial positions for Iter0 (before alignment): (root)
      • Iteration 1 (99150 events - 385028 tracks - 3910740 hits):
        • Summary plots: ps.gz pdf
        • Initial positions for Iter1 (after Iter0): (root)
      • Iteration 2 (99150 events - 394033 tracks - 4339267 hits):
        • Summary plots: ps.gz pdf
        • Initial positions for Iter2 (after Iter1): (root)
      • Iteration 3 (99100 events - 394606 tracks - 4353202 hits):
        • Summary plots: ps.gz pdf
        • Initial positions for Iter3 (after Iter2): (root)
      • Iteration 4 (1000 events - 4043 tracks - 44451 hits):
        • Summary plots: ps.gz pdf
        • Initial positions for Iter4 (after Iter3): (root)
    • Comparison plots of Iterations 0, 1, 2, 3 and 4. Only for tracks laying within the DoubleCone acceptance region. The ideal case is also included and serves as reference
      • Track parameters: plots More tracks are reconstructed after each iteration
      • Track params: Reco-Truth: plots
      • Hits associated to tracks: plots More hits are associated to the tracks. SCT is back to 8 and PIX to 3.
      • Pixel phi biased residuals: plots All residuals become more centered and narrower after each iteration
      • Pixel eta biased residuals: plots
      • SCT biased residuals: plots
      • SCT biased residuals (wider range): plots
      • Tranverse plane Impact parameter (d0) error and its phi0 dependence: plots
      • Accepted tracks per events (so tracks within double cone acceptance): plots
      • Q/p plots in various formats for systematic studies: plots

Physics applications of the ID alignment (as 01/Mar/07)

An example of physics analysis with our alignment constants obtained starting from the nominal setup and 4 iterations of the GlobalX2 with its builtin vertex constraint.

Test on Z-->mu+mu- events.

The alignment constats have been applied to reconstruct CSC Z-->mu+mu+ samples (5145) . Disclaimer as the alignment it only performed for the DoubleCone geometry then the two mouns candidates must lay within its acceptance (basically within |eta|<1.1).

The analysis is based on PIX+SCT only tracks. The selection of candidates is rather basic and at this stage of the analysis is not fine tunned at all. The following requirementes are applied:

  • A Z candidate is formed from two oposite signed tracks.
  • Each of the tracks must have a mimimum Pt of 10 GeV/c.
  • The collinearity of the tracks must be > 60 deg.
  • The Z candidate must have a Pt < 45 GeV/c

The distributions of these variables for the selected Z candidates and its muons is presented in here. Plots are normalized to 1 pb-1 of integrated luminosity. Other distributions are:

Test on MinBias events

Again the alignment constants have been applied on a sample of CSC MinBias events (5001). Below one may find some distributions of basic observables.

Figures for fun

  • Some schematic figures presenting the features of the misalignment
    • Impact parameter shift after a global shift of the detector: figure
    • Effect of the global shift in the reconstructed momentum: figure
    • A clocking effect (layer rotation proportional to radius) bends the trakcs of positive and negative charged particles in a different way. The result is a bias in the momentum. figure
    • Local X distributions after a global shift: figure

Comments about Nominal vs Ideal reconstruction (as 10/Mar/07)

Check these plots presented in a Valencia-Oxford coordination meeting: pdf file. In this file you may find a comparison of the track properties reconstructed using the nominal and ideal geometry (as they come no alignment yet), and using iPatRec and GlobalX2Fitter. What is presented is for all tracks delivered by the trackers. There is no further selection done by us. Besides, when the ideal geometry is used in the reconstruction then the error scaling is switched off. Whilst if the nominal geometry is used then the error scaling is switched on.

CSC: residuals hangover (as 08/Feb/2007)

Comment on tracking and silicon residuals.

During the last IDSW workshop we presented the residuals (PIX and SCT) obtained when running over the CSC multimuons sample (talk). It was observed that the residuals of the silicon (pixel and SCT) modules were different when using newTracking and iPatRec. This is now understood in terms of the biased vs unbiased residuals. In few words: while iPatRec residuals were biased, newTracking ones were unbiased.

We have processed 100K events of the CSC multimuons sample (7270) using the digits files. The exercise has been repeated 4 times with:

  • (1) iPatRec, using the ideal alignment and no error scaling
  • (2) newTracking with GlobalX2Fitter, ideal alignment and no error scaling
  • (3) iPatRec and using nominal positions for the modules and error scaling
  • (4) newTracking with GlobalX2Fitter, nominal positions and error scaling

Ideal means knowing the final positions of the modules while nominal means ignoring the real positions of the modules by placing them at their nominal location. So in a certain way ideal means perfectly aligned while nominal means misaligned. For obvious reasons no error scaling is needed for the ideal geometry, while it is needed in order to keep a decent track finding efficiency when using the nominal setup.

Tracks have been reconstructed with Pixels and SCT only (TRT excluded). It must also be said that we have used a minimum track quality cut by requiring the track to have associated at least 1 pixel hit and 4 SCT hits.

The job produces a TrkValidation.root file (with a FitterValidation/OutputTrack branch). We also produce the Richard Hawkings' ntuple (idaling). We have checked that: 1) both ntuples contain exactly the same number of tracks and 2) the residuals shape look the same. All the plots here presented are actually extracted from the idalign.root file. So in this way we had an easy acces to biased residuals for both tracking options.

In what follows we present a comparison of the results obtained for both trackers: iPatrec and newTracking. The histograms settings (range and bins) are exactly the same. They were produced running over the same sample of 100K multimuons events. They are printed exactly in the same frame. If one of them seems to have less entries is simply because it has less entries (either due to less reconstructed tracks or due to less asociated hits).

Figures 1 and 2 present a comparison of the track properties when using alternatively both tracking methods (iPatRec and newTraking-GlobalX2Fitter). Figure1 shows the result for the ideal case, while figure 2 for the nominal case. So in the ideal case (figure 1), one can appreciate an almost perfect matching between both trackers. In the nominal case (figure 2) one can appreciate some differences. The main one is that iPatRec has more entries so a higher track efficiency (iPatRec 93%, newTracking 86%).

  • Figure 1: track properties when using the ideal geometry (perfectly aligned).

  • Figure 2: track properties when using the nominal geometry (misaligned).

The PIX phi residuals dsitribuitons in the ideal case presented in figure 3. Figure 4 presents the SCT ones. Again, one can see an almost perfect mathcing. So in conclusion one can say that both trackers perform equally well in the case of a perfect kwonledge of the geometry.

  • Figure 3: PIX phi residuals for the ideal.

  • Figure 4: SCT residuals for the ideal case.

Now figures 5 and 6 present the PIX phi and SCT resiudals in the case of the nominal setup. Obviously the distributions have become broader, reflecting the ignorance of the geometry. In general iPatRec residuals and newTracking look similar, but there are certain differences specially in the pixels. This fact is due to the less number of PIX hits that the newTracking founds associated to the track. It has been checked that the narrow peak at PIX phi residuals = 0 corresponds to the tracks wiht only 1 associated PIX hit.

  • Figure 5: PIX phi residuals for the nominal case.

  • Figure 6: SCT residuals for the nominal case.

It would be nice if other users of the CSC sample can confirm or deny this observations and the tracking experts could help us in understanding the hit association and the resiudal distributions.

Reconstruction of simulated Events

The CSC simulated events are created with Tag ATLAS-CSC-01-02-00 (misaligned and distorted material). To reconstruct the digits we have two options:

Option 1: Nominal Geometry - Misalignment Unknown

  # Detector Description
  DetDescrVersion = "ATLAS-CSC-01-00-00"
  IOVDbSvc = Service("IOVDbSvc")
  IOVDbSvc.GlobalTag="OFLCOND-CSC-00-00-00"
         

Option 2: Misaligned Geometry - Misalignment Known

  # Detector Description
  DetDescrVersion = "ATLAS-CSC-01-02-00"
  IOVDbSvc = Service("IOVDbSvc")
  IOVDbSvc.GlobalTag="OFLCOND-CSC-00-01-00"
        

There is no need to specify a GlobalTag in this case. The conditions database tag will be the same as use in the simulation regardless of which geometry tag is set.

See SettingGeometryVersion for more details

Releases Recipes

12.0.4

Required packages

Required packages to use tracks refitted with the vertex

jobOptions (examples)

Error Scaling

  1. set ErrorScaling parameters. Two working options are available:
    • Option 1: manually create the sql file
      • save the attached python script (available from Tracking/TrkTools/TrkRIO_OnTrackCreator/share) to the run directory of InDetRecExample and rename it as make_IndetTrkError.py
      • change dataset to:
                 dataset=[ ("PixPhi Barrel",1.0,0.035),
                           ("PixEta Barrel",0.89,0.025),
                           ("PixPhi Endcap",1.0,0.055),
                           ("PixEta Endcap",1.2,0.50),
                           ("SCT Barrel",0.79,0.70),
                           ("SCT Endcap",0.90,0.77),
                           ("TRT Barrel",0.91,0.230),
                           ("TRT Endcap",0.82,0.00)
                           ]
                 
      • change tag to something significative. Example:
                 tag="12.0.4_CSC"
                 
      • execute the script:
                 python make_IndetTrkError.py
                
      • this should produce a sql file called mycool.db.
    • Option 2: use the already attached sql file mycool.db
  2. add the the following lines at the end of InDetRecLoadTools.py:
             IOVDbSvc = Service ("IOVDbSvc")
             IOVDbSvc.Folders += ["<dbConnection>impl=cool;techno=sqlite;schema=mycool.db;X:OFLP130</dbConnection> /Indet/TrkErrorScaling <tag>12.0.4_CSC</tag> "]
             
  3. Move mycool.db to the run directory of InDetRecExample

Links

-- CarlosEscobar - 11 Mar 2007

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