Update 'FCNC Fitter'
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06cecf4a15
@ -110,4 +110,38 @@ Currently, the file structure is as follows. All the `.cc` source files also hav
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## Running
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python script
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For the detailed explanation of possible parameters, [[click here|Running-the-FCNC-fitter]].
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For quickly running everything, run the following commands
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```
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python run.py -convert -all -Run 1
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python run.py -dontCompile -convert -all -Run 2
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python run.py -dontCompile -MC -angCorr -Run 1 -scan
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python run.py -dontCompile -MC -angCorr -Run 2 -scan
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python run.py -dontCompile -MC -angCorr -Run 1
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python run.py -dontCompile -MC -angCorr -Run 2
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python run.py -dontCompile -MC -angRes -Run 1
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python run.py -dontCompile -MC -angRes -Run 2
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python run.py -dontCompile -MC -Run 12 -fit -Ref -nBins 1
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python run.py -dontCompile -MC -Run 12 -fit -nBins 5
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python run.py -dontCompile -Run 12 -v 2 -fit -Ref -nBins 1 -genMC -Ref
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python run.py -dontCompile -Run 12 -v 2 -fit -nBins 5 -genMC
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python run.py -dontCompile -Data -Run 12 -fit -Ref -nBins 1 -massDim
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python run.py -dontCompile -Data -Run 12 -fit -nBins 5 -massDim
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python run.py -dontCompile -Data -Run 12 -fit -Ref -nBins 1 -bkgOnly -upper
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python run.py -dontCompile -Data -Run 12 -fit -nBins 5 -onlyBkg -upper
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python run.py -dontCompile -Run 12 -v 2 -fit -Ref -nBins 1
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```
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**TODO** Create PHSP weights
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* First, it compiles the code and prepares the tuples with Run 1.
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* Then, since we already compiled the code, we use the -dontCompile option for running the next commands.
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* We prepare the tuples for Run2. Then, it scans the order of polynomial used for the PHSP angular description.
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* Next step is to create the angular acceptance weights using the optimal polynomial.
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* Then, the signal Monte Carlo sample is fitted: first fit the reference channel, then the signal channel.
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* After this step is done, it fits the generator level Mont sample in the J/psi Q2 bin and rare channel in 5 Q2 bins.
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* The next step is to fit the data in the B+ and K*+ masses: first, fit the J/psi channel, then the rare channel in the 5 bins.
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* Then, fit the angular background distributions (upper B+ mass sideband) using a chebyschev polynomial.
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* The last step is to fit the data, J/psi channel in 4 dimensions (B+ mass, cos(thetal), cos(thetak), phi)
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