1. Cocktail algorithm studies
MB Workshop
Cocktail algorithm studies
Carmen Diez Pardos
Silvia Goy López
CIEMAT Madrid
Muon POG
07/04/2011
C. Diez Pardos 1
C. Diez Pardos (CIEMAT) 1

2. Introduction: cocktail algorithm
Study in detail chi2, resolution and pulls for the data and MC used in the W' analysis
Not many high pt muons
Also: compare with cosmics (next step)
There are several tunes, the used one is “TuneP”
Algorithm logic: selection based on -lnProbchi2
Picky is taken as default, if it doesnt exit -> Take TPFMS -> tracker - >global
If -lnProbchi2 (Picky-Tracker) >30, chosen tracker
If -lnProbchi2 (TPFMS-chosen) >0 : takes TPFMS
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3. Samples and Muon Selection
Data: 2010RunB Nov4ReReco
MC: Fall10 W samples, W’ (1500GeV)
Selection on the criteria for the analysis
Must be Global and Tracker Muons
Combined isolation: < 0.15 in a cone R < 0.3
Quality cuts related to the track: d0<0.2 cm, number of valid muon and pixel hits >0, number of valid tracker hits >10, number of matching segments >1, valid muon hits >0
Muon matched to a L3 muon: HLT_Mu9, _Mu11, _Mu15
Note: For this selection W MC is not enough to describe data (should include other BG), but it should be fine for pT > 100 GeV.
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4. Cocktail choice for data and MC
At low pT data and MC differ in Barrel and EC:
Low pt W: more TPFMS
Data: more Picky (changes tendency at high pT, see next slide)
TkOnly contibrutes ~1%
C. Diez Pardos 4
In general, TPFMS preferred, for data Picky in the Barrel until pt 200 4

5. Cocktail choice for data
MORE TPFMS
ACORDING TO joRDAN

6. -LnProb(chi2) difference
TPFMS- PICKY
Negative mean!
BARREL W W' W
ENDCAP
W' Mass 1500 GeV
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7. Ratio chi2 MC W over Data pt>100 GeV
In this region most of the BG is W, distributions are normalised to area
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8. Ratio ln chi2 tail prob MC W over Data pt>100
PICKY
TPFMS
In this region most of the BG is W, distributions are normalised to area
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9. Pt distributions
ANIADIR RATIO, PT for pt<100 W
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10. Resolution residuals for the chosen algo
Fit for each algorithm the resolution, for the whole region and the BARREL ONLY??
PUT a plot
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Left tail: reconstructed momentum higher than generated
Interested: See tails in low pt distributions and resolution core in high pt
MEAN: Similar?
SIGMA: Quite similar within algorithm, better for the chosen one

11. Resolution residuals for the chosen algo
Fit for each algorithm the resolution, for the whole region and the BARREL ONLY??
PUT a plot
C. Diez Pardos 11 11
Left tail: reconstructed momentum higher than generated
Interested: See tails in low pt distributions and resolution core in high pt
MEAN: Similar?
SIGMA: Quite similar within algorithm, better for the chosen one

12. Resolution residuals for the chosen algo
PONER % de picky y TPFMS
Por ver que mejor no cogerlo nunca??
==> Hacer el del cocktail total
Results separated by selected or rejected for Picky and TPFMS
Left tail: reconstructed momentum higher than generated
Interested: See tails in low pt distributions and resolution core in high pt
MEAN: Similar?
SIGMA: Quite similar within algorithm, better for the chosen one
C. Diez Pardos 12 12

13. Resolution residuals as a function of pt for W' MC
Tracker not shown, too little stat
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14. Resolution residuals as a function of pt for W (allpt!) MC
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15. Pulls as a function of pt for W MC
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16. Pulls as a function of pt for W' MC
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17. Conclusions
- How valid a tune with data/MC is applicable to the other samples: Different behaviour in eta regions and pt
Datos: falta una contribucion para pt bajo de MC
- Is it the optimal cocktail? (It seems that it works fine...)
- Check with cosmics (Jordan?)
Many, many thanks to Jordan for all the help and pacience 
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18. Back-up
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19. Chi2 between data/MC (all BG) (Plots by G. Abendi, A. fanfani)
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20. Barrel Choice for MC and data

21. Data: all eta regions