Hi Daniele,
On Mon, 20 May 2002, Daniele del Re wrote:
>
> more about genericmc-cocktailmc are in my last posting.
>
> The Breco normalization is done taking the number of reconstructed B's
> after the cut on the lepton.
OK, that what I thought - we are doing the same
thing. However, it is really strange that Henning
and I do not observe this sp3 feature. As you could see
from Hennings previous talks showing the Mx distribution
for different lepton cuts and missing mass cuts we observe
a reasonable agreement between sp3 cocktail and data. Also,
the difference between sp3 and sp4 seems to be not as large as
you are pointing out.
Well, anyway, your sp4 plots look now quite similar
to our plots.
Although it is a kind of sad that using sp4 only will
lead to a huge MC statistic error.
Oliver
>All the remaining plots are normalized to the
> same area.
>
> Cheers,
>
> Daniele
>
>
> > > 1) in general the agreement is better in the generic MC with respect to
> > > to Cocktail.
> > >
> >
> > I would rephrase this statement to:
> >
> > "in general the agreement between data and Monte Carlo is bad and
> > it is hard to tell which of the two types of MC performs worse."
> >
> > ... but thats just my personal point of view.
> >
> >
> >
> > > 2) the disagreement is the charged and neutral multiplicities. In
> > > particular the neutral multiplicity seems to be a bit worse in the
> > > high-energy case (160MeV<E<320MeV, E>320MeV). This affects mm2 and mx
> > > distributions.
> > >
> > > 3) if we normalize using the number of reconstructed B's we observe that
> > > cocktail and generic MC's go in different direction (don't look at the
> > > chi^2 in these plots since it is wrong). This effect is also
> > > reflected in the efficiency comparisons. We must study in detail
> > > this point.
> >
> >
> > I am not sure that I really understand what
> > "normalize using the number of reconstructed B's" means.
> > Looking at the plots for MXHAD (allcuts) it turns out
> > that "cocktail vs data" and "generic vs data" are quite similar.
> > I assume that for "allcuts" you normalize the histograms
> > to the same area (correct?). In case of the "allcuts(breconorm)"
> > the normalisation for the cocktail goes up whereas for generic
> > is goes down with respect to the "allcuts" scenario.
> > Thats the effect of "normalize using the number of reconstructed B's"
> > (I guess) ..... how do you get this significant different
> > normalization factors for generic and cocktail. I always thought
> > the normalisation is determined from data and hence the same for
> > cocktail and generic?!
> >
> > Regrads,
> >
> > Oliver
> >
> > >
> > > Daniele
> > >
> > >
> >
> >
>
>
|