Bs2JPsiGamma Workbook

Strategy Update - 16 Dec 2014

• Adjust preselection DIRA cut to 0.9999 (preselection now ~85% signal efficient). Previously it was 0.99999 (and around 68-70% efficient)
• With the new preselection applied run on the KstGamma MC and Data
• Fit the LL and DD Kstar MC component separately and freeze the parameters
• Then do data fit with exponential background component and LL, DD fraction in signal floating (this gives frac of LL = 0.47 +/- 0.17)
• Now look at just preselected Jpsi Gamma data and compare amount of data in signal window for the LL and DD
• This gives an estimate for the expected number of background events for LL and DD
• Using the fraction from KstarGamma above with the back of envelope theory prediction (for total 40 signal events). Summarise all the information as:

VALUES FOR OPTIMAL BDT CUT

===== SUMMARY ====
LL:
nSig = 12.2556
nBkg = 1668.12
DD:
nSig = 13.7444
nBkg = 5773
======================
fLL Sig: 0.47137
fll Bkg: 0.224176
======================

-- MatthewKenzie - 28 Jul 2014