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Flavor Tagging

Flavor Tagging. Joseph Kroll University of Pennsylvania 1 st CDF B Mixing Workshop 9 June 2004. Reminder: Fundamental Quantities. We quantify performance with efficiency  and dilution D.  = fraction of signal with flavor tag. D = 2P – 1, P = probability that tag is correct.

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Flavor Tagging

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  1. Flavor Tagging Joseph Kroll University of Pennsylvania 1st CDF B Mixing Workshop 9 June 2004

  2. Reminder: Fundamental Quantities We quantify performance with efficiency and dilution D = fraction of signal with flavor tag D = 2P – 1, P = probability that tag is correct Statistical error A on asymmetry A (N is number of signal) statistical error scales with D2 J. Kroll University of Pennsylvania

  3. Two Types of Flavor Tags Opposite side Produce bb pairs: find 2nd b, determine flavor, infer flavor of 1st b + Applicable to both B0 and B0s −other b not always in the acceptance Same side Based on fragmentation tracks or B** + better acceptance for frag. tracks than opp. side b −Results for B+ and B0not applicable to B0s Reminder: for limit on ms must know D J. Kroll University of Pennsylvania

  4. Opposite Side Tags Have evaluated performance of opposite side tags using lepton + SVT triggered data sample Results for pure b extracted using subtraction technique based on signed impact parameter of SVT track – see CDFNOTE 6480 Lifetime problem in l + SVT sample points to background that has not been taken into account Is this background an issue for determination of D? J. Kroll University of Pennsylvania

  5. Run II Results on Opposite Side Tags Soft muon tag (CDFNOTE 6483) blessed have D vs. pTrel Jet charge tag (CDFNOTE 6951) blessed have D vs. Qjet with and without SECVTX have seen talks on soft electron tag and kaon tag not blessed Need blessed results on these soon Significant effort has been spent on optimizing J. Kroll University of Pennsylvania

  6. Performance of OST’s is Poor – Why? Part of the problem is acceptance of opposite side b Generator Level study by K. Lannon – see CDFNOTE 6254 Need high statistics MC Sample with all processes J. Kroll University of Pennsylvania

  7. Poor Performance of OST’s cont. We need to understand our opposite side tag D2 Begin by taking out opposite side acceptance: Tag opposite side b with lifetime (SECVTX, SVT…) Can we understand the dilution of these opposite side b’s? • We should be able to understand lepton tags: • understand semileptonic b decay • can measure detection efficiency • can measure fake background An example – see D. Usynin, 27 Jan. 2004 at Semileptonic meeting If we master lepton tags – move on to JQT, OSKT Invest more effort here before spending more time optimizing J. Kroll University of Pennsylvania

  8. Summary of Opposite Side Tags • get soft electron tag blessed (ICHEP) • continue work on kaon tag – when do we show something? • invest effort to understand OSTs – continue with muons • Desirable to have MC with all processes – important for SST too • may find a way to improve tags – or find they are already optimal • this could be ready for ICHEP if somebody works on it • Extend coverage in  – 5.3 helps here (forward tracking) • BMU already in SLT() – can be improved (use 5.3 data) ICHEP • What about electrons or jet charge? • Develop new OST’s e.g., D* tag • Understand OST before investing effort improving them J. Kroll University of Pennsylvania

  9. Summary of Opposite Side Tags (cont.) • Sample composition of lepton + SVT sample understood? • main use of this sample • optimization • dilution as a function of parameters (pTrel, Qjet, etc.) • Probably okay here – need to settle this issue (ICHEP) • Need to apply OSTs to B0 mixing analysis (ICHEP) • includes using multiple tags – see Franco’s presentation J. Kroll University of Pennsylvania

  10. Same Side Flavor Tags Based on correlation between charge of fragmentation particle and flavor of b in B meson Decay of P-wave mesons (B** also contributes to B0, B+ (not B0s) Expected correlations different for B+, B0, B0s J. Kroll University of Pennsylvania

  11. Run II Results on SST with B0, B+ Blessed results on SST – see CDFNOTE 6964 based on exclusive K and D modes Results confirmed with semileptonic modes – see CDFNOTE 7011 Blessing imminent J. Kroll University of Pennsylvania

  12. Run I: Understood SST Well MC explained D+ vs. D0 F. Abe et al., PRD 58, 032001 (1999) Data vs. Tuned MC Excellent Agreement We need to do the same thing in Run II J. Kroll University of Pennsylvania

  13. Agreement Between Data and MC Crucial If we do not observe B0s mixing need MC to predict SSKT D Tuning MC to agree with Data is TOP PRIORITY (Aside: part of this is measuring B** production in data) At the same time: need to study particle id around B mesons Do we see a difference in K//p around B+, B0, B0s in data? Opposite side tags may be limited by opposite b acceptance SS(K)T may be our only path to sensitivity to ms We must prepare a credible case that we understand SS(K)T J. Kroll University of Pennsylvania

  14. Summary of Same Side Tags • Tune MC to match data • examine various quantities like multiplicity, pTrel, pLrel, etc. • measure B** production as part of this comparison • Measure K//p around B+, B0, B0s mesons • does MC reproduce observed particle content? • measurement in data a good goal for ICHEP • Use tuned MC to investigate optimal algorithms • so far have just blessed pTrel alg. of Run I • This is a long physics program • we need a lot more concentrated organized effort here • there will be publications as part of this work (particle content) J. Kroll University of Pennsylvania

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