Super-K Code: Making a Monte Carlo Tuning Sample
Super-K Code Exercise: Making a Monte Carlo Tuning Sample
This exercise will allow you to employ skills learned from
the previous tutorials, and in fact is a task similar to
the kind of thing one often needs to do in reality. The idea is to
create a sample of MC events that one can compare to data. You will
take a file of stopping muon data events, fit (reconstruct) them,
and create kinematics files using the fit results in order to
simulate a matched MC sample.
Monte Carlo Tuning
Detector simulation code usually has a number of parameters that can
be tweaked in order to change the nature of the simulation. Some
examples are: sizes or densities of detector elements, optical
properties of detector materials, properties of the electronics.
Sometimes these parameters are quantities that can be known precisely,
either from the way the detector is constructed or else independently
measured: for instance, in Super-K the sizes of the PMTs are well
known, as is the density of the water. Other parameters may not be so
well known, either because it's hard to measure them directly or they
might change with time. For instance, transparency of the water in
Super-K can vary with its cleanliness. For the case when the
parameters aren't well known, one can "tune" them: i.e. determine
parameter values in order that simulated events match real data events
as well as possible.
A typical way of tuning the MC is to obtain a data sample,
and simulate a MC sample which in principle should match it. Then,
one looks at various key distributions for data and Monte Carlo
(the nature of which depends on what parameters you're looking at)
and tweaks the parameters until the distributions match are well
A Stopping Muon Example
For this example, you will take a sample of selected stopping muons
in Super-K (real data events). You will then fit them using
a simple fitter called muboy. The fitter outputs
vertex and direction for each muon. You will use this information
to create a kinematics file that corresponds to the stopping muon
sample, i.e. each real data event will have a corresponding
event in the kinematics file for simulation. Then, run skdetsim to
simulate the events. Finally, you will create plots for
your data and MC distributions for comparison. The point of
the example is to create a sample that can be used for tuning;
we'll stop short of the actual tuning step (although some
of you will be doing this later).
I am not providing complete canned code for each of these steps: your
challenge is to fill in the blanks to complete the task. Most
of the examples we've done so far should give you guidance.
Files for this example
Copy the following files
into your working directory:
- muboy_fit.F: contains sample source code
for fitting muons.
- The shell script for running the program, muboy_fit.sh.
contains primarily stopping muon data events (superscan them to have a look).
You need not copy this file into your working directory. This is a data file from Super-K II.
- sk2_odtune.card contains parameters for skdetsim appropriate to Super-K II.
- First, examine muboy_fit.F. You will see it is similar
to the previous examples, but has some extra variable declarations
for muboy fit variables. For each event, it calls the muboy fitting
All but the first of these arguments are the
fitting results returned to you. Of these, variables you will need are:
- muboy_class: this is the type of event. Class=1 means a through-going
muon, and class=2 means a stopper. The events in this
example's file will be overwhelmingly class 2.
- muboy_entry: this is the entry point of the muon on the ID.
- muboy_dir: the fit direction vector of the muon.
- muboy_tracklength: the tracklength of the muon in the detector.
- Compile and run the fitting program on the stopping muon
file, and check the output written to the screen.
- Now, modify muboy_fit.F to open a kinematics file and
write an entry for each data event, where the vertex and direction of
the event correspond to the vertex and direction resulting from the
muboy fit. As a first pass, you can use the muboy entry point (in
the ID) as the vertex.
For the energy, take the pathlength provided by muboy and
multiply by the energy loss of a muon in water, which is approximately
2 MeV/cm. You will probably need to consult a Fortran
manual or tutorial to figure out how to write
output in the proper format (alternatively, you can write to a
simple unformatted text file, and use Perl or another language to
write the properly formatted output, if you are more comfortable with
- Once you have your kinematics file, simulate the events
You can check with superscan that the data and MC events correspond
to each other.
- Finally, write a program (I am not providing one-- use
the examples so far as a guide) to read the data file, read the MC
file, and output the number of hits in the ID, nqisk,
for comparison between data and MC.
- Make a plot of the distribution of number of ID hits for data,
with a plot of MC superimposed, using PAW.
Since the entry point given by muboy is on the ID cylinder, if
you make the vertex the same as the muboy entry point, the muon will
not be properly tracked in the OD (check this yourself with
superscan). To simulate events with appropriate
OD light, you will need to extrapolate the muboy track back to where
it intersects the OD outer wall, and make the vertex the entry
point in the OD.
Try this next, and make a plot of the distribution of
OD hits for data and MC. Here are some tools that will help:
- The routine crstnksk (standard SK software)
finds the intersection of a line and a cylinder. You can find
this in $SKOFL_ROOT/src/sklib/crstnksk.F: the documentation
at the top of this source file tells you how to use it.
- The include file geotnk.h has parameters which give
the size of the SK tank ID and OD. You can find this in