Implementation of binned observables in the Likelihood

[DegCo]

Hi all,

I have probably a simple question, but I have not found the answer in the previous issues. Hopefully it will be useful for other "rookies" like me.

When I try to implement in the likelihood binned observables just by their name, e.g. '(B0->K*mumu)', I get the error 'no measurements found'. Of course, I understand that one should also implement the binning, i.e. q2min and q2max, but I have not found a way of doing so. How do I pass in q2min and q2max information into the likelihood?

Thank you very much for your time and great work!

Example of code (that raises the error): FL = FastLikelihood(name='test', observables= [ '<FL>(B0->K*mumu)'], include_measurements=['LHCb B->K*mumu 2020 P 4-6'])

[peterstangl]

Observables that require additional arguments can be specified in three equivalent ways:

• using a tuple like e.g. ('<FL>(B0->K*mumu)', 4, 6)
• using a list like e.g. ['<FL>(B0->K*mumu)', 4, 6]
• using a dictionary like e.g. {'name: '<FL>(B0->K*mumu)', 'q2min': 4, 'q2max': 6}

[DegCo]

Thank you very much! I'll make good use of it.