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Estimate of Sensitivity with a Bayesian approach G.Cavoto, F.Renga, G.Piredda, C.Voena

Estimate of Sensitivity with a Bayesian approach G.Cavoto, F.Renga, G.Piredda, C.Voena. Outline. Use temporary pdfs Estimate of number of bkg events from data Toy MC study and sensitivity study with Bayesian approach Fit Region : +- 6sigma : Eg=44 .2-61.4 MeV

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Estimate of Sensitivity with a Bayesian approach G.Cavoto, F.Renga, G.Piredda, C.Voena

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  1. Estimate of Sensitivity with a Bayesian approach G.Cavoto, F.Renga, G.Piredda, C.Voena

  2. Outline • Usetemporarypdfs • Estimate of number of bkgeventsfrom data • Toy MC study and sensitivitystudywithBayesianapproach • FitRegion: +-6sigma: • Eg=44.2-61.4MeV • Ep=48.-57.6 MeV • theg=170-180 degrees • Teg= 24.7-27.1 ns • (Assumedresolutions: • (Ep)=0.8MeV(Eg)=1.43MeV(Teg)=0.2ns, (theg)=30mrad)

  3. Temporary PDFs • SIGNAL • Eg: from full signal MC • Ep: 3-gaussianfromfrancesco’s fit on data • theg: fromtoy MC generation using MC angularresolution • Teg=gaussianwith 0.180 ns (from UL) • RADIATIVE • Ep,Eg,theg: toy MC thatsmear and weightkuno-okada • distributiontakinginto account resolution and acceptance • Teg: gaussianwithsameresolutionassignal • ACCIDENTAL • Eg: fromfittoTegsideband • Ep: fromfrancesco’s fit • theg:fromfittoTegsideband • Teg: flat

  4. Estimate of number of Accidental events • Strategy: • - Countevents in Tegleftsideband (othervariabiles in fitregion) and scale in Tegfitregionassumingflatbkgdistribution • NB=+- • Strategy2: • - FittoEgsidebandwithaccidental+radiativepdf, scale • toEgfitregionusingpdfshape • (thisgivesalso the number of radiativeevents) • NB= • NRD=

  5. Fit to Eg sideband Nacc=zzzz NRD=zzzz

  6. Toy MC results • Non Gaussian • errors with 0 • (low) number of • signal/radiative • events • Need to use • Likelihood to • estimate UL Fitted NS

  7. A Toy MC experiment with high statistics

  8. bayesian UL • On fitted data: • - build a posteriori pdf of BR byweighting the a-priori BR pdf • (flatfrom zero toBRmax) withweight w: • w = exp(-(LogL(NS)-MinLogL)) • where NS for a given BR iscomputedusing the normalization • factor (takinginto account its error) • Estimate of sensitivity • - perform the previousexcercisefor a set of toyswhere Nsgen=0 • We can usethistooltoperformsystematicstudies • Implementationongoing

  9. Estimate of UL on 2008 data Inputs

  10. Conclusion

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