IMPORTANT NOTICE: In order to distinguish between (official) plots done by the CKMfitter group and unoffical plots done with the package available above, it is asked to label "package" under the CKMfitter logo on the unoffical plots. Thanks.
This page intends to provide help in producing standard plots
with the package using the inputs |Vub|, |Vcb|, epsilonK, DeltaMd, DeltaMs and
sin2beta (as can be found
here ). Other plots can be produced modifying the default datacards provided
on this web page, and help can be obtained by contacting the
The minimal system configuration required to run the software is:
FORTRAN 77 and C++ compilers
HBOOK / PAW
[ Everything you wanted to know about PAW (Tutorial, FAQ, etc.):
(PAW is part of the CERNLIB package available
IMPORTANT: CERNLIB and RFIO problem
The default version of the "packlib" library since 2004 in the CERNLIB
is compiled with the "shift" library. It exists a version compiled without
the "shift" library: "packlib_noshift". If you encounter problems during compilation
of the CKMfitter package, this is certainly related to thisCERNLIB problem.
To solve it, edit the Makfile and change the line:
CERNLIBBAS = -lmathlib -lpacklib
CERNLIBBAS = -lmathlib -lpacklib_noshift
and then the usual "gmake".
[Each constraint in the (rho-eta) plane corresponds to a dedicated datacard. See the "datacard" directory.]
The script "runckm" calls the CKMfitter binary (CkmFitterApp). It is driven by
two types of datacards (located in the "datacards" directory): the first type
(like "ckm_all.data") contains the fit ingredients, and the second
type (like "ckm_flags.data") contains the fit options.
More details on the content of these datacards are given below.
Once the code stops running, you can plot the results in PAW by
typing in PAW the command (the file "ckmglobal.kumac" is in the "kumac" directory):
exec ckmglobal#plot_rhoeta ,
Change its content to your needs (especially the location of your hbook files)
The fit ingredients are specified in the datacard
ckm_all.data (containing all ingredients of the standard fit).
The name of the output HBOOK file is also specified in this datacard.
A standard (rho-eta) plot is composed by various constraints :
- the global fit using all constraints (obtained by "ckm_all.data")
- individual constraints obtained by the files "ckm_vub.data", "ckm_epsk.data",
Each ingredient is characterized by 4 quantities:
name = 'sin2beta' --> gives the name of the ingredient
value = 0.731, 0.056, 0.0 --> value +- Gaussian error +- flat error
TakeMeIn = T --> whether it should be used in the fit
Free = F --> whether it should be let floated in the fit
The measurement should have the values "TakeMeIn = T" and "Free = F", whereas
the theoretical parameters should have the values "TakeMeIn = T" and "Free = T".
There is one special setting to choose in this datacard, called
"UseOneNDof", which is used to specify the number of degree of freedom
of the fit. Two cases are possible:
- you use at least 2 ingredients both depending on (rho-eta): UseOneNDof=F
- you use only 1 ingredient depending on (rho-eta): UseOneNDof=T
The other setting in this datacard is called "$constrainMeasurements".
It is used when performing 1-D fits, or 2-D fit in other space than the
standard (rho-eta) space. Set the "constrUse" to 1 for the variables that
should be used in these non-standard fits, and to 0 for the other variables.
The default flag datacard, ckm_flags_all.data,
allows to realize a frequentist fit in the 2-D (rho-eta) plane, using a rough
binning of 50 x 50 (less CPU-consuming for a first test of the fit, but which should
be increased to 200 x 200 for final plots).
To realize most of the standard fits, only a few switches need to be modified, as specified below.
For more complicated fits (for example, related to charmless decays), other switches not mentioned
below should be modified. Please contact the
for more details.
The basic switches to know are the following:
UseImprove and UseMinos are used to improve the convergence of the fit.
They are CPU consuming (especially the second one), but allows to obtain completely converged
results (not-well converged results show irregularities).
FitLambda, FitA, FitRhoBar, FitEtaBar: to let the
Wolfenstein parameters floating or not.
ScanType2D: to choose between the four 2-D standard fits in the
(rho,eta), (sin2alpha, sin2beta), (sin2alpha, gamma), (sin2beta, gamma) planes.
Granularity: granularity of the scan (good quality is 200 x 200)
ScanDimensions: gives the minima and maxima of the 2D fits.
NumberOfFits: used when UseImprove=T: number of fits performed
at each point to improve the convergence. The default is 1, and you can go up
to 6 when the convergence is bad (3 is a good compromise).
DoTraceParameters: perform a 2-D frequentist standard fit
DoConstrainMeas1D: perform a 1-D frequentist fit
DoConstrainMeas2D: perform a 2-D frequentist non-standard fit
(other than the choices in ScanType2D)
DoTraceChi2Min: set to true to evaluate the CL of the fit