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No title. Vanya BELYAEV (Syracuse). 4 ways to make a physics analysis. “native” DaVinci explicit C++ , tools, explicit loops “ DaVinci for busy people” *.opts files no C++ LoKi C++ , which does not look like C++ Compact Bender Python Friendly Perfect for prototyping.

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  1. No title Vanya BELYAEV (Syracuse)

  2. 4 ways to make a physics analysis • “native”DaVinci • explicitC++ , tools, explicit loops • “DaVinci for busy people” • *.opts files • no C++ • LoKi • C++, which does not look like C++ • Compact • Bender • Python • Friendly • Perfect for prototyping There is no Vanya BELYAEV/Syracuse

  3. Take the best form all • Prototype your algorithm with • Bender/Python • run with signal data and relatively small amount of background • Estimate for acceptance, rec-efficiency, … • Mass/Lifetime resolutions • Few important variables for signal vs background discrimination • Prepare the selection algorithm • DaVinci/opts or LoKi/C++ • Run the stripping/skimming over *LARGE* data, reduce • Code “analysis” algorithm • Large reduction: Bender/Python • Small reduction: LoKi/C++ • Make “small” N-tuple, analyse with ROOT/PAW Iterate Vanya BELYAEV/Syracuse

  4. Bs→fg • Stripping/skimming (common with B→K*0g, Lb→Lg): • LoKi/C++ • Very loose cuts, almost no PID, no tight cuts on PT,IP • Reduce 3*107 events to O(40000) • 1 night or very long meeting, … • Final analysis step • LoKi/C++ • Final results • OpenOffice Vanya BELYAEV/Syracuse

  5. S/sqrt(S+B) Bs→fg Vanya BELYAEV/Syracuse

  6. S/sqrt(S+B) B→K*0g Vanya BELYAEV/Syracuse

  7. S/sqrt(S+B) B→K*0g Bs→fg Vanya BELYAEV/Syracuse

  8. S/sqrt(S+B) Bs→fg Vanya BELYAEV/Syracuse

  9. S/sqrt(S+B) B→K*0g Bs→fg Vanya BELYAEV/Syracuse

  10. S/sqrt(S+B) B→K*0g Bs→fg Vanya BELYAEV/Syracuse

  11. S/sqrt(S+B) B→K*0g Vanya BELYAEV/Syracuse

  12. Resolutions B→K*0g Bs→fg Vanya BELYAEV/Syracuse

  13. 13 minutes @ nominal conditions B→K*0g Vanya BELYAEV/Syracuse

  14. Bs→mm • Stripping/skimming: • DaVinci/opts • Very loose cuts, almost no PID, no tight cuts on PT,IP • Reduce 3*107 events to O(20000) • time to process 20k events O(1 hour): nice to run for the night or during lunch time, or meeting, … • Further (private) stripping: • LoKi/C++ • A bit more tights cuts: • Reduce to O(2000) • Time to process 2k events O(5’) ~ 1 coffee cup or 1 phone call • (Interactive) final analysis step • Bender/Python • Final results • PowerPoint Vanya BELYAEV/Syracuse

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