5may

Some globals results of the CuCu Data with the Silicon Strip Detector

The file used are :
* ITTF only TPT tracking, SVT hits, no tracking for SSD
/star/data13/reco/cu62productionMinBias/FullField/DEV_ssd.nosvt/2005/073
the files I used are : st_physics_6073006_raw_2020002.event.root
st_physics_6073006_raw_2020003.event.root
st_physics_6073006_raw_2020004.event.root
st_physics_6073006_raw_2020005.event.root
st_physics_6073006_raw_2020006.event.root

I'm sure in this case that no tracking is done with the svt and the ssd
So the 2 cases I rerun on are with (options in the bfc Chain):

tpcI -SvtIt -SsdIt : no SVT no SSD hits used in the tracking
tpcI -SvtIt SsdIt : only SSD hits used in the tracking

The tracking parameters are :

for the Z direction : sigma_z = 0.0049 (0.07*0.07)
for the r/phi direction : sigma_r/phi = 4e-6 (0.002*0.002)
min window = 1.
max window = 4.
Window Scale= 5.
Max chi2= 30.

There is no preliminary cut on the position of the primary vertex but only on the number of the hits in the TPC ( nTpc > 5 )
Some results

Global results

I look at the dca for the primaries tracks and compare when the tracking was done without ssd and when the tracking was done including the ssd AND for the primaries tracks including a ssd point
For all the plots about the DCA, there is here a cut on the number of the hits in TPC ( nTpc > 10 )

dca for pt < 0.5


Figure 1 : no eta cut	Figure 2 : fabs (eta)< 0.5

The DCA of the primary tracks decrease from 0.50 to 0.24 cm when the tracks include a point of the SSD.
The values are slightly the same ( MPV = 0.45 and MPV = 0.23 ) with a cut on the eta of the tracks.

dca for 0.1 < pt < 0.5

The idea is that the SSD must help for the tracking with the low pt particles, so the number of primary tracks for the low pt must increase when the ssd is in the tracking.
As Sti accept only tracks where pt>0.1 , pt=0.1 is the minimum value.

dca for differents pt ranges

dca vs tpcpoints

dca vs tpcpoints : 2-D plot

For this sample, I got ( NTpchits >10 && abs(eta) < 0.5 ) :

When the ssd is not in included :

global 189877

primary 178530

global	189877
primary	178530

When the ssd is in included :

tracks	with only tpc points	with tpc and ssd hit
global	173296	15960
primary	121227	56865

For this sample, I got the distribution of the tracks as the function of their pt:


Figure 1 : no ssd in the tracking	Figure 2 : ssd in the tracking

We can see :

Without the ssd, the number of global and primary is quiet the same ( 189877 global ; 178530 primary).
Distribution of these tracks as a function of pt : except the first range, it looks like the same, ie
The number of tracks (global + primary) is decreasing when we look for tracks including a ssd point


Figure 1 : Global tracks	Figure 2 : Primary tracks

Details of these plots :

The range in pt is 0.1 GeV/c.
The Y axis is the ratio between all the tracks which have a pt in this range over the total global or primary tracks.


Figure 1 : no eta cut	Figure 2 : fabs (eta) < 0.5

figure 1 :
1. top left : global tracks which are not included a ssd point
2. top right : primary tracks which are included a ssd point
3. bottom left : global tracks which are not included a ssd point
4. bottom right : primary tracks which are included a ssd point
The range in dca decrease from [0;0.8] to [0;0.5](green region) for the primary track in the NTpc hits range of [30;40];
figure 2 : the same but with the eta cut : this cut is not so effective on the dca for NTpc hits > 25.

For differents configurations :

left column : for the global tracks

right column : for the primary tracks

first row : no ssd in the tracking

second row : ssd in the tracking

third row : ssd in the tracking but the tracks have no ssd hits

fourth row : ssd in the tracking but the tracks have ssd hits

eta, phi, length, chi2 of the tracks


Figure 1 : For the Primary Tracks	Figure 2 : For the Global Tracks

Few comments :

the gap for -0.8 < phi < 0 is because ladder 7 and ladder 8 were not taking data during (almost) the run 5.
As you can see from next,
Identifier: 7000+wafer(from 1 to 16)*100+ladder (from 1 to 20);
Det Nber = 7107 cv:20.9546 ; -7.23984 ; -32.709 phi:-0.332661 r:22.17
Det Nber = 7108 cv:17.4917 ; -13.4285-32.647 phi:-0.654736 r:22.0519
(See the new SSD geometry : - here)

The length of primary tracks

Ratios

I look at the ratio between the number of primary tracks including a ssd hit with all the primaries : it could define some 'efficiency' for the ssd. With the previous tracking parameter where the chi2 cut for hit was set to 5 (default parameters in StiSsd), I then set it to chi2 = 30 according to $STAR/StarDb/Calibrations/tracker/KalmanTrackFitterParameters.20010312.000002.C.
Yon can see - here for the differences between
Then I get :

ratio(1)

ratio(2)

The top left figure shows the distribution of the tpc hits for all the primary (1)
The top right figure shows the distribution of the tpc hits for all the primary which are not including a ssd hit(2)
The bottom left figure shows the distribution of the tpc hits for all the primary which are including a ssd hit(3)
The bottom left figure shows (1) and (2) together (so it gives (1))


Figure 1 :	Figure 2 :

It is more understandable with the 2 next plots ( for 1 event ):
We have 33 primary tracks with :

18 are not including a ssd hit
15 are including a ssd hit

So it gives me a ratio between the number of primary tracks including a ssd hit and all the primary of 15/33 = 0.45


Figure 1 :	Figure 2 :	Figure 3 :

V0 candidates


Figure 1 : : K0 Short	Figure 2 : : Lambda

For both figures : plots in the same row from the left to the right:

column variable (from left to right) : DecayLength cut of the V0 candidates from 2 to 8
row variable( from top to bottom ) : daughters have no ssd hits, 1 of the 2 daughters has a ssd point, anf both daughters have a ssd point

The goal of this is to see if when the daughters tracks include one ssd point, we can release a geometrical cut, here the Decaylength.

For a decaylengthV0 > 2, I got :


Figure 1 : the tracks corresponding to the posive and negative daughters have no ssd points	Figure 2 : the positive OR the negative daughter has a ssd point	Figure 3 : Both positive and negative daughters include a ssd point

The background is fitted by an exponential : it is well reduce when one daughters includes a ssd point.
To do : I have to know if it is just becaase there is less tracks which have a ssd point so I simply got less entries or if this cut is really efficient.

V0 candidates : 19 may

Fit

The cuts applied are :

DecayLengthV0 > 2
daughters < 0.8
dcaParentoPrimVtx < 0.5
tpchits_neg>15 && tpchits_pos>15


Figure 1 : K0 candidates without the ssd	Figure 2 : K0 candidates which one daughter has a point in the ssd

The fit consists on a linear (background) + gaussian.
Again, there is not for now a huge difference between the 2 cases : the background is decreasing but the signal decreases too.
The K0 mass and the sigma on it don't change significantly.

Cuts


Figure 1 : K0 candidates without the ssd	Figure 2 : K0 candidates which one daughter has a point in the ssd


Figure 1 : Lambda candidates without the ssd	Figure 2 : Lambda which one daughter has a point in the ssd

Last modified: Fri May 5 10:57:26 EDT 2006