MC Routines

To generate synthetic data, we adopt the fiducial model that the diffuse gamma ray background is isotropic.

Ferrer's MC Python routines

Here are Ferrer's MC routines in Python:

The script Media:mc.py generates 10000 synthetic samples with the same number of events in the real data. The events are uniformly distributed in the spherical caps and do not fall close to a Fermi source. The samples are saved to disk in numpy array format. Their statistics (average and standard deviation) is computed using this script Media:qstat.py. For b>80deg we obtain the following MC samples Media:mc80.tar.gz.

Tashiro's MC routines in Fortran90

Tashiro's MC routines in F90 are included in File:Gamma codes.tar.

"MC_code" contains the code for Monte Carlo simulations. There is a parameter "north_south" which is for choice of north and south. After the code, "generate_SQT.nb" generates the file for plotting the MC result. In the file, we can find R degree, average Q and the standard deviation.