Hi all,

I think there is another issue to be addressed. Up to now, we have been 
worrying about fixing the signal/peaking background components in our 
mES fits, to deal with instabilities in bin of kinematic variables with 
low statistics. We implemented constraints on the signal/peaking 
background components for mES distributions as a function of the bins of 
the kinematical (mx, p+, q2) variables, but only for DATA.

However, our final mx, p+, mx/q2 fits need also distributions for 
Vcb+other MC and Vub(IN+OUT) signal MC. These MC components have been 
and are currently being determined by performing mES fits as usual, e.g. 
by leaving the signal, peaking and combinatorial backgrounds floating 
and without any constraint applied. There are plenty of mES fits on MC 
with low statistics. Recall also that every single bin in the kinematic 
variable under study results from an appropriate sum of mES fits 
performed separately on charged B, neutral B opposite flavor and same 
flavor to correct for BBbar mixing.  If you look  e.g. at Antonio's 
latest VVF fits in

you see that mES fits on data 
(charged B) 
(neutral B opposite flavor) 
(neutral B same flavor)

have the peaking/signal fixed (only signal S, combinatorial background B 
and argus shape ar are floating in the fits), whereas the peaking 
background component P is also floating in the MC mES fits:



The bottom line is: we need to constraint somehow the signal/peaking 
background components in the mES fits also for these MC samples. The 
question is: how?

One possible solution is to use the full (charged + neutral B) MC sample 
which has been used to correct for the  data, but Antonio showed in his 
previous posting that the fits are not stable for high mx values (signal 
and peaking background are swapped), and are not good for intermediate 
mx values. Grouping several high mx bins seems not to give more stable 

Another possibility (which can also be applied when constraining S/P = 
signal/peaking on data) is to determine separately S and P, by e.g. 
counting or fitting for S in events with truebrecomode==recobrecomode, 
and fitting ony P and the combinatorial background in events with 
truebrecomode!=recobrecomode. This latter solution should give more 
robust estimates.

In any case, any S/P constraint would be determined on the entire 
(charged+neutral B) sample, and it should be dependent perhaps only on 
the kinematical variables.

Any comments?
Ciao, Concezio.

Antonio Petrella wrote:
> Hi,
> we also computed a correction factor for the signal/peaking bkg using 
> the entire mx distribution, not a bin by bin.
> In this case the fit looks better, with respect to the bin by bin one:
> cheers,
>   Antonio