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

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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 2C. Diez Pardos

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Samples and Muon Selection Samples: 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, 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 p T > 100 GeV. 3C. Diez Pardos

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Cocktail choice for data and MC In general, TPFMS preferred, for data Picky in the Barrel until pt 200 4C. Diez Pardos 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%

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Cocktail choice for data MORE TPFMS ACORDING TO joRDAN

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-LnProb(chi2) difference TPFMS- PICKY Negative mean! W W W' W' Mass 1500 GeV BARREL ENDCAP 6C. Diez Pardos

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Ratio chi2 MC W over Data pt>100 GeV In this region most of the BG is W, distributions are normalised to area o 7C. Diez Pardos

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Ratio ln chi2 tail prob MC W over Data pt>100 In this region most of the BG is W, distributions are normalised to area TPFMS 8C. Diez Pardos PICKY

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Pt distributions ANIADIR RATIO, PT for pt<100 W 9C. Diez Pardos

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Resolution residuals for the chosen algo 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 Fit for each algorithm the resolution, for the whole region and the BARREL ONLY?? PUT a plot 10C. Diez Pardos

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Resolution residuals for the chosen algo 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 Fit for each algorithm the resolution, for the whole region and the BARREL ONLY?? PUT a plot 11C. Diez Pardos

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Resolution residuals for the chosen algo 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 Results separated by selected or rejected for Picky and TPFMS PONER % de picky y TPFMS Por ver que mejor no cogerlo nunca?? ==> Hacer el del cocktail total 12C. Diez Pardos

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Resolution residuals as a function of pt for W' MC Tracker not shown, too little stat 13C. Diez Pardos

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Resolution residuals as a function of pt for W (allpt!) MC 14C. Diez Pardos

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Pulls as a function of pt for W MC 15C. Diez Pardos

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Pulls as a function of pt for W' MC 16C. Diez Pardos

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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 17C. Diez Pardos

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Back-up 18C. Diez Pardos

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Chi2 between data/MC (all BG) (Plots by G. Abendi, A. fanfani) 19C. Diez Pardos

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Barrel Choice for MC and data

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Data: all eta regions

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