1) Will follow-up offline on b-tagging calibration
2) Do you split V+jets SF’s across data-taking years as well? Do you observe significant differences? No, signal regions are inclusive in data-taking years, and so are our SFs, never looked at this
3) Have you checked VHcc signal extraction without the b-tag veto? No, the c-tagging WP was optimised considering the veto. For the combination with VH(bb) we checked the VH(cc) “contamination” in the VH(bb) categories and it is at most a few percent of the VH(cc) yield in the VH(cc) categories; in the combined fit there was no change in signal strength uncertainty, i.e. not losing much sensitivity using such a veto
4) How can you separate different background-enriched categories just using DRcc selection? There is one dRcc CR per c-tag SR and to control V+l there are also the 0 c-tag regions in 1/2L
5) sl 10: Is the relative fraction used as priors calculated wrt the alternative generators? Yes; it’s the quadrature sum of the various variations (alternative generator and internal weight variations)
6) sl 11: Expect these two shape uncertainties in SR and CR based on the cc mass to be quite correlated in the fit model as the nominal and alternative samples are the same and the main difference is the phase-space for the comparison. Is that the case? Can you comment on the correlation? Yes, this is correct, these shapes are usually quite slightly correlated. You can see that when deriving them, and also in the fit, where they usually show anti-correlations. It is worth noting though that the SR shape variations are usually small.
7) sl 13: What is the primary uncertainty of the top background component? The comparisons to of different generators (ME or PS variation) implemented as 2-point systematics
8) sl 20: Why do you expect such a difference in impact between Z+jets and W+jets modeling (7% vs 3.9%)? The Z+jets modelling enters both via the 2L and 0L channels and the 0L is driving the sensitivity.
9) sl 20: Why don’t you have constraints post-fit on ‘stat 0L SR’ which I assume it’s a bin-by-bin MC stats NP? Is it expected that the fit can constrain this parameter that much? We have one gamma NP for each bin, and in a high-stat region as this - it is in the 1 c-tag region the 0- lepton channel - we have a lot of data statistics
10) What accuracy is Sherpa V+jets? NLO-accurate ME for up to 2 jets, LO-accurate ME for up to 4 jets