Difference: CMSSusyAnalysisResultsTest (26 vs. 27)

In |DPhi|>2.7, the signal pollution is one order of magnitude smaller! A': 0.1% B': 9% C~: 0.6%

A'/C' ratio is very similar to the A/C ratio, we can substitute that instead. The B/B' background ratio could be taken from MC and use it to scale the number of events in B' to have an order of magnitude less polluted estimate for B and then D).

D is then: D = (B/B')_MC * B' * C' / A' = (9.45/12.24) * 13.36 * 1273.35 / 5801.51 = 2.26

c.f: 2.10 with no signal contamination. The error then is around the signal pollution level of B' which can also be substracted maybe, but it's definitaley lower than ABCD only prediction. i.e: Polluted A/B/C would cause: D_poll = B_poll * C_poll / A_poll = 4.67 --> This would be much larger and therefore it is a legitimate question

This method I think looks good! Is this the logic you described, Petar?

4) Try other TTbar samples as a comparison

Warning: NLO event weights are not correct (negative gen-weights aren't subtracted), but the obs/predicted ratio is still useful - Overall number of ttbar events are around ~1+-0.4, prediction to observed ratio: ~1.4+-0.3 - In all cases, the overall event number prediction stays very close to the observed number of events: ratio: 0.97 +-0.09, pulls are low too

5) Why TT+W/Z not similar to ttbar? Plot DeltaPhi shape for TTV

Plots attached. For some reason the Dphi distribution looks very similar regardless the Ntop/Dphi bin. These are NLO samples, so I will need to correct for the negative weights.

6) When backgrounds are combined scaling might not work: --> Try mixing together different ratios of bacgrounds to check how robust the method is

If I scale ttbar by 2 times the cross section, the pull gets larger, the ratio is sligthly lower, but still within statistical error. - Should we apply a ~3% correction to account for this? - If I blow up ttbar to x5 xsec, the ratio is still 0.85 --> Should we simply add a systematic error?

The method seems to be very robust.

7) Try to find a way to describe why the method works from first principles Plot correlation of Razor variables for all regions of the ABCD methods in TTbar (and other) samples, eg: a) DeltaPhi vs MR/MTR for Ntop==2 and Ntop<2

The MTR vs DPhi plots show no correlation, that's great. MR vs DPhi shows some correlation, but I have an idea: MR for the top-pair is uncorrelated to DPhi, this is potentially useful. But I have to update my top-pair definition to the latest recipe and rerun the code.

I am planning to do a full AK4/AK8/TT - R comparison to settle this issue (I already did for Phys14, but I only checked signal efficiency, which was very similar).

Hopefully TT-R is uncorrelated to DPhi and then the explanation why the method works might be finally there.

b) MR/MTR vs Ntop for DeltaPhi <2.7 and DeltaPhi >2.7

I missed these plots, sorry. They are on my to-do list.