ISR/FSR Tomonobu Tomura (University of Tsukuba). 2 Introduction ISR/FSR is becoming one of the dominant sources of systematic uncertainties for in-situ.

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Presentation transcript:

ISR/FSR Tomonobu Tomura (University of Tsukuba)

2 Introduction ISR/FSR is becoming one of the dominant sources of systematic uncertainties for in-situ JES calibration method. CDF and DZero have been using different approach to estimate ISR/FSR uncertainty. Better to use consistent way for the top mass combination.

3 Previous CDF Scheme Use DY data (no FSR) for the extraction of reasonable range of Pythia parameters to describe ISR uncertainty. FSR syst. is based on the ISR study.

4 Previous DZero Scheme Use different mixture of Alpgen+Pythia ttbar+0p, 1p, 2p samples to describe the uncertainty. Systematic uncertainty: difference between tt0p and weighted sum of 0p, 1p, 2p

5 Merits and Demerits CDF Advantage Data driven. Separate treatment for ISR and FSR. Disadvantage Extrapolation to a higher Q 2 region based on the linear dependence on log(Q 2 ). Not all the diagrams. DZero Advantage Many diagrams. No extrapolation. Disadvantage No variation in soft radiation (below the threshold).

6 Comparison of Samples We compared some kinematical distributions of samples for the systematics. Pythia Nominal ttbar Alpgen+Pythia ttbar+0p(3.60 pb) and ttbar+≥1p(1.13 pb) Pythia ISR More/Less Pythia FSR More/Less

7 Jet Multiplicity Left plot: Njets distributions for various MC Right plot: difference from the Pythia nominal

8 Leading Jet (E T &  )

9 5th Jet (E T &  )

10  R between 5 th jet and b/q

11 Acceptance (≥4jets, ≥1b-tag) SampleAcceptance (%) Pythia Nominal2.88 Alpgen ttbar+0p/1p3.03 Pythia ISR More2.88 Pythia ISR Less2.82 Pythia FSR More2.78 Pythia FSR Less2.87

12 N(Nj>=5)/N(Nj>=4) SampleFraction Pythia Nominal0.251 Alpgen ttbar+0p/1p0.268 Pythia ISR More0.275 Pythia ISR Less0.247 Pythia FSR More0.256 Pythia FSR Less0.258

13 Plan / Proposal Use Alpgen+Pythia as the nominal sample. ISR/FSR Uncertainty  “ Signal Modeling Uncertainty ” Vary Alpgen parameters to cover the uncertainties in the prediction. Parameters to vary alpha_s, factorization scale, etc. Not 0p/1p sample fraction because it is determined by matching. How much to vary Control sample? Theoretical input? Or, reweighting the sample to construct + and – systematic samples. Alpgen Validation / Parameter Study are urgent issues.