I am interested in computing the charge miss identification rates. These rates are derived from the data, based on the fraction of Z ->ee. The events in the m_ee region around the reconstructed Z-boson peak mZ are used.
For Nij electron pairs falling in the bin combination i,j the expected number of same-sign events is:
where ϵi and ϵj are the QMisID rates for each of the two electrons.
If all the same-sign events in the Z peak are produced by charge flip, then these numbers are described by a Poisson distribution:
Where observed events =>
and expected events =>
The probability for both electrons to produce a charge flip is:
Which is integrated into likelihood
that can be maximised (minimisation of -2lnL) to obtain the rates that best describe the data.
So for that, I have draw the distribution of Z->ee and apply the fit using the likelihood fit.
Hi,
In the fit above, which function did you use for fitting ? How did you code it ?
The parameters p0,…p4 are the parameters in teh order you have defined in your fit model function.
Then it is clear what the parameters p[] are. I guess your parameters can be derived by the number of expected Z->ee events. This can be obtained from the integral of your fitted function, assuming you don’t have a background component in your data.