run 7 : K0s inv mass signal-to-noise and significance vs. St cut

The idea is to look at the cut St = dca /σ (track significance) but for all possibilities (silicon hits = 0 to silicon hits =4)

This cut may be different since σDCA(Pt) is different from silicon hit =0 (TPC only) to silicon hits =4 (SSD+SVT), as shown in Fig. 1

Fig. 1 : σDCA distribution of pions candidate

TPC only (yellow) has a <σDCA> of 0.25 cm whereas tracks with SSD+SVT (red for silicon hits =4) have a <σDCA> of 0.025 cm 

Then the next step is to fit the distribution dca / σDCA vs Pt ; the idea is that tracks from secondary vertex should have larger dca, then selecting tracks with St > g(Pt) [where g(Pt) is the fit function] might remove combinatorial background

Note: this is equivalent to the "usual" cut for V0 decay , |dca to PV| > .8 cm

Fig. 2 : s.t.d of dca / σDCA vs Pt ; lines are pol3 to pol4 fit ; the parameters of each fit are then used in the analysis ;

from left to right, top to bottom : tracks with silicon hits = 0, 1, 2, 3, 4

 

In the analysis, I only used the fit parameters if Pt < 2.5 .

K0s candidates are only kept if pion tracks satisfied the condition St > g(Pt), depending on their silicon hits number
 

  •  St > 1*g(Pt)

  •  St > 2*g(Pt)
  •  
  •  St > 3*g(Pt)

 

Summary :

s/b and significance vs. St cut
St > 1 2 3
signal-to-noise 0.06 0.59 2.09
significance 14.87 26.23 26.60

 

  1. St > 1 helps to have an K0s peak but with low s/b [put the inv. mass plot w/o any cuts on St to show the combinatorial background]
  2. going from St>2 to St>3 does not improve much the significance but considerably (x4) increase the s/b 
Mean mass and width values
St > 1 2 3
<mass> 0.4974 0.4917 0.4966
σ 0.009 0.007 0.008

 

  •  invariant mass vs. # silicon hits of daughters

 

Fig. 3 : invariant mass of K0s vs. the # of silicon hits for daughters : each opposite combination (1 && 2, 2 && 1) is also included

Labels of histograms are wrong , one should read "SiPion(daughter1) && SiPion(daughter2)

  1. for #si(daughter1) = 0 && #si(daughter2) = 0

  1. for #si(daughter1) = 1 && #si(daughter2) = 1

  1. for #si(daughter1) = 2 && #si(daughter2) = 2

  1. for #si(daughter1) = 3 && #si(daughter2) = 3

  1. for #si(daughter1) = 3 && #si(daughter2) = 4

 

 summary : 

si hits for daughters 0-0 * 1-1 2-2 3-3 3-4
mass  0.4984  0.4971 0.4956 0.4955 0.4956
width  0.0015  0.001 0.006 0.005 0.003

 * : the fit is not working well, it seems there is a double speak

➥ so we see that daughters having 2 or more silicon hits have an improved width