In few problems can the integrals that appear in the evaluation of
cross sections be done analytically. Most of the time we have to
revert to numerical methods to evaluate the integrals. There are many
ways to do evaluate the integrals numerically. A good library is the
CUBA
package. It can be linked either with
C/C++ or with Fortran programs. It has several methods with
the same calling structure, so that one can substitute one method for
another and check for accuracy. The manual comes with the package.
I have done a gaussian integration
subroutine gauss.f
that uses the
same calling conventions, and therefore can also be tested in the same
way. To illustrate its use I have done an example in Fortran
with a simple
problem, the
in QED (that is, only
the photon graph) that we studied before
as an example of the use of the mathematica packages. In this
case the integrations can be done analytically, but the integral
diverges if we integrate in
. So we have to
apply a cut, say
. This is the well-known
collinear divergence that appears because the photon is massless. In
terms of center of mass variables, we have (we do not neglect the
fermion masses)
and we see that it diverges for
.
A Fortran program that calculates this is
muemue.f. To use it you also need
an header file with the physical parameters of the Standard Model
smpc.h
and the Cuba package
compiled as library (we assume it in
/usr/local/lib/Cuba/libcuba.a). It is useful to use a
Makefile
to compile the
program. You can get a tar gzipped file
Integrals.tar.gz
with all the needed files. You should experiment with the
integration methods and
compare with the exact integration that is also included in the
program.
Note added 22.04.2014: The current version is compatible with
Cuba-3.3. We remind the reader that the calling of the routines was
modified from previous versions.
The results are summarized in the following figure:
where we have applied a cut
and
GeV. We have calculated in four different
ways: a) Using the exact analytical results (black line) b) Using
gaussian integration (red dots) c) Using Vegas integration (blue
crosses) d) Using CalcHEP (green diamonds). We see that the results
are in excellent agreement.
Jorge Romao
2023-09-01