1D pdf with additional variables from dataset, but not normalize over the additional variable

Dear RooFit experts,
I am trying to implement a pdf which describe the relativistic Breit-Wigner shape. It needs three variables to evaluate the line shep: the mass m of mother particle, the mass m1 and m2 of two daughter particles, and the mass m of mother particle is the observable/variable to be investigated
and to be fitted. While when the two daughters are stable particles such as pion and kaon, I can use the PDG value in the evaluation, but for non-stable particles, e.g., omega\phi\rho, I think it is better if I can use the detected mass m1 and m2 in the evaluation. This means for each event in a dataset, I need the ‘m’, and also ‘m1’ and ‘m2’, while ‘m’ will be the one the variable of the BW pdf, the ‘m1’ and ‘m2’ should also be in the dataset but not any ‘variable/observable’. I did not find any information related on this topic. So I am wondering if it is possible? If so, how should I implement it and if not, can this feature be in the furture RooFit version?
In summary, what I want/need can be shown as below example:
A dataset contains three RooRealVar, m, m1, m2. A pdf which has some parameters (p1,p2,…), and take the ‘m’ as variable, and it also needs m1, and m2 when do the detailed evaluation of pdf value: mypdf(m, p1, p2, …, m1, m2). The m1, and m2 are used to evaluate pdf value, but not as the fit variable (fit variable is m) and also not parameters (parameters are p1, p2, …, and are same for all events in the dataset). Therefore this is not 3d pdf.

Best Regards,

Welcome to the ROOT forum

May be @jonas can help

Hi @zjq,

these kind of additional observables to normalize over are called ConditionalObservables() in RooFit. They are quite common, and you can find some tutorials that make use of it:

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