Discussion

Definition of some track parameters

• All the definitions are cited from $ALICE_ROOT/TPC/doc/Definitions/Definitions.pdf

• # of TPC clusters N_cls: A charged particle traversing the TPC induces a signal on a given pad-row. If the charge exceeds threshold and fulfills all necessary quality criteria, it is called a cluster. Therefore the maximum number of clusters per track is 159 which corresponds to the total number of pad rows in a given TPC sector.

• # of TPC clusters in first iteration N_cls_iter1: the number of TPC clusters assigned during the first (inward) tracking iteration.

• # of missing clusters N_miss: Some TPC clusters along the track trajectory can be missing, because their charge is below threshold(e.g. due to baseline shifts etc.). These missing clusters can be identified;ed by looking into the neighboring pad-rows, e.g. if there is no reconstructed cluster on pad row i, but clusters are found on the pad rows i-1 and i+1 (or i-r and i+r in general).

• # of crossed rows N_eff: N_eff = N_cls + N_miss. This variable can be viewed proportional to the effectively sampled track length of a particle in the TPC. It is the relevant quantity for pt resolution of a track, because the pt resolution scales with 1/sqrt(N_cls) (statistics) and (N_eff)^2 (level arm) .

• Findable clusters N_find: The number of findable clusters is the number of geometrically possible clusters which can be assigned to a track.

• Remarks
  1. TPC clusters can be lost due to unknown reasons (e.g. dead zones, missing partitions and decays, etc) or because their charge is below threshold (caused by the front-end electronics; these clusters are called missing clusters). So the variable (N_cls)/(N_find) depends on the digital threshold, on multiplicity, energy loss, drift length and track angle. On the other hand (N_eff)/(N_find) is almost independent from energy loss, multiplicity and η. Supporting plots on 2010 PbPb data can be found in $ALICE_ROOT/TPC/doc/Definitions/Definitions.pdf
  2. 2012-01-05: Marco: The number nCrossedRows is based on the clustermap, which is a bitmap which has a flag for every padrow telling whether there was a hit found along the track trajectory or not. We then loop over this bitmap and count every hit and also counting neighboring empty rows, up to 2 away from a found hit. So, the number of crossed rows is at most (last row - first row) + a few. This measure is less sensitive to cluster finding efficiency than the number of clusters, because if you lose a cluster somewhere in the middle of the track; it is counted, as long as it has a found cluster in the neighboring row or the one next to it. The crucial point according to the TPC experts is that nCrossedRows 'fills in the gaps' if there is an occasional cluster missing and is therefore less sensitive to the details of the gas amplification and cluster finding efficiency. It does not extend the track beyond the first and last measured point (or at least not more than 2 points on each side). It does not 'correct' for large gaps in the track.
  3. 2012-01-19: Why would the ratio nCrossedRows/nFindableClusters be larger than 1? Marian: nFindableClusters can be under/overestimated by a large number of clusters for track near the sector boundaries. The ExB distortions are of the order of 2 mm at the inner radius of the TCP and 1 cm at the outer radius and are not fully treated in the calculation of nFindableClusters.

Track cuts

Definition

Hybrid tracks

• Use good global tracks when they are available, otherwise use global constrained tracks
• Cuts for good global tracks:
  • pT dependent cut on # of TPC clusters in the first iteration: if pt<20, N_max = 70 + 30/20 * pt. If pt>20, N_max = 100.
  • chi2 per TPC cluster in first iteration < 4
  • No kink daughters
  • Require TPC refit
  • Fraction of shared TPC clusters < 0.4
  • Require ITS refit
  • Chi2 per ITS cluster < 36
  • DCA_xy < 2.4cm
  • DCA_z < 3.2cm
  • At least one hit on SPD
  • Chi2 between TPC constrained and global < 36
• Cuts for global constrained tracks
  • Same cuts as for the good global tracks shown above except no ITS refit or SPD hits requirement
  • Constrained to primary vertex to improve pT resolution

• Good track pT resolution, uniform phi distribution, but track quality is mixed.

TPCOnly tracks

• TPCOnly track cuts + constrain to SPD vertex
  • # of clusters in TPC > 70
  • Chi2 per cluster in TPC < 4
  • No kink daughters
  • DCA_xy < 2.4cm
  • DCA_z < 3.2cm
  • Constrained to SPD vertex
• Uniform phi distribution, but bad pT resolution

Global/Gloden/Primary tracks

• Global/gloden/primary tracks are selected by using standard track cuts: AliESDtrackCuts::GetStandardITSTPCTrackCuts2010(kTRUE,1)
  • # of crossed rows in TPC > 70
  • Ratio of crossed rows over findable clusters in TPC > 0.8
  • Chi2 per cluster in TPC < 4
  • No kink daughters
  • Require TPC refit
  • Require ITS refit
  • At least one hit on SPD
  • pT dependent DCA in x-y plane
  • DCA < 2cm in z
• Good pT resolution, but non-uniform phi distribution

NTPCclsIter1 vs NCrossedRow

• In the hybrid track cuts, there are two ways to cut on track quality: NTPCclsIter1 (cut on # of TPC clusters in the first iteration) vs NCrossedRow (cut on # of crossed pad rows).

Pass2

• This data set suffers from the bug of bookkeeping the TPC cluster map. So all the tracks with more # of TPC clusters than # of crossed pad rows are removed.

Before cut

• All the following plots are produced with base cuts: meaning standard hybrid track cuts without cut on NTPCclsIter1

• Correlation of NTPCclsIter1 and NCrossedRow in different track pt bins
  

Distribution

• Distribution of NTPCclsIter1 in different track pt bins. Official cut is: if pt<20, N_max = 70 + 30/20 * pt. If pt>20, N_max = 100.
  

• Distribution of NCrossedRow in different track pt bins. Official cut is: N_max = 70.
  

• Distribution of NCrossedRow/NFindableClusters in different track pt bins. Official cut is ratio > 0.8
  

Correlate with track phi

• Correlation of NTPCclsIter1 with track phi in different track pt bins
  

• Correlation of NCrossedRow with track phi in different track pt bins
  

Correlate with track momentum resolution

• Correlation of NTPCclsIter1 with track momentum resolution in different track pt bins. Compared to the plots below, it looks like the NTPCclsIter1 cut cuts away more track with bad resolution.
  

• Correlation of NCrossedRow with track momentum resolution in different track pt bins
  

Effects of the two different cuts

• The official cuts:
  • Cut on NTPCclsIter1: if pt<20, N_max = 70 + 30/20 * pt. If pt>20, N_max = 100
  • Cut on NCrossedRow: N_max = 70; ratio of crossed rows over findable clusters > 0.8

• Effects on track pt distribution: within statistical uncertainties, the difference is < 5% and cut on NCrossedRow includes more tracks.
  

• Effects on track momentum resolution: cut on NCrossedRow clearly selects more tracks with bad resolution
  

• Effects on raw jet yield: within statistical uncertainties, the difference is within a few percentage.
  

Summary

• Given the fact that NCrossedRow cut includes more tracks with bad resolution, I think it is better to use the cut on NTPCclsIter1.

Hybrid vs TPCOnly

Pass2

• Track pT resolution
  • Left: hybrid track: three band shows up. From the best to worst:
    • Global tracks with ITSrefit and a hit in one of the two or both SPD layers
    • Global tracks with ITSrefit but no hits in the 2 SPD layers
    • Global tracks without ITSrefit (note that these tracks can have a hits in the SPD layers but it is not required)

• Track pT distribution in full phase space
  

TPCOnly vs global tracks

• Track pT:
  • Reconstructed track pT: from AliESDs.root
  • Constrained track pT: after updated by constraining to SPD vertex
  • Delta pT = reconstructed track pT - constrained track pT

MC

• Delta pT vs reconstructed track pT
  

• Compare to MC truth
  

• Delta pT vs DCA_xy: the peak of DCA distribution at 0 is not artificial, meaning these tracks do have very small DCA
  

• Delta pT vs DCA_z
  

• Delta pT vs # of TPC clusters:
  

• Delta pT vs track eta
  

Pass2

• MB: Constrained pT vs reconstructed pT
  

• EMC-trigger: Constrained pT vs reconstructed pT
  

Pass1

• Number of tracks per event in triggered and MB events.
  

• pT distribution of tracks in triggered and MB events.
  

• Phi distribution of tracks in triggered and MB events.
  

• Eta distribution of tracks in triggered and MB events.
  
• To have a closer look into the bump at eta=0, I show eta distribution of TPCOnly tracks in MB events with pT>0,1,2 [GeV/c]. As shown in the plot, this bump exists for higher pT tracks
  

Pass2

Hybrid tracks

• Track pT distribution
  

• Track phi and eta distribution
  

TPCOnly tracks

Track pT distribution

• pT distribution of all the tracks in both HT and MB events.
  

• pT distribution of tracks in EMCal acceptance both in HT and MB events (left) and their ratio (right).
  

Track phi-eta distribution

• Track phi-eta distribution
  • Top row -> HT events; bottom row -> MB events
  • From left to right: different pT cuts -> 0, 0.2, 1, 5 GeV/c

Pass3

TPCOnly tracks

Ratio of pos to neg

• Ration of positive tracks to negative ones:
  

Pass1

Global tracks

pT distribution

• pT distribution of tracks:
  

phi-eta distribution

• This plot shows the phi-eta distribution of global tracks pointing to EMCal in triggered and MB events with different pT cut.
  • Upper: triggered event, pT>0, 0.2, 1, 5
  • Lower: MB event, pT>0, 0.2, 1, 5
  • More activity shows up in area corresponds to EMCal SM 5

MC study

TPCOnly tracks

Tracking efficiency

• Cut on |eta| < 0.9 both for generated and reconstructed tracks
• Use primary charged pion sample
• Pure tracking efficiency with (left) and without (right) upper kinematic cut, namely 40GeV/c, on the reconstructed tracks.
  

Track pT resolution

• This plot is created by matching reconstructed tracks to the generated primary tracks.