Setup

The analysis is based on gammapy and uses .fits files containing the instrument responses (effective area, point spread function, energy smearing)

The package in km3net to produce irfs (and still under development) is: git@git.km3net.de:km3py/km3irf.git

The simulations used at that time have since evolved. To start, we can try to update the IRF fits files to newer / the latest Monte Carlo version of KM3NeT. The goal of this exercise is to obtain an update to Figs. 2 to 5 in the CTA-KM3NeT paper

There are already published csv tables for a newer Monte Carlo available here: https://github.com/KM3NeT/KM3NeT-ARCA-irf/tree/master/data. We want our instrument responses to agree with these.

Todo:

• Focus on effective areas for the start.
• Get the .csv tabulated effective areas. To get a feeling you can just plot the csv file contents.

For the acutal comparison it would be good to write a small converter to output a fits file from these .csvs. To that end:

• Install the km3irf package.

• Get familiar with the package and try to load/plot the files of the original analysis: https://github.com/KM3NeT/Analysis-galactic-sources-CTA-KM3NeT/tree/main/data/km3net/irfs **)

• Write a small converter, reading in .csv contents and putting the read-in data into a fits. You should be able to use the build_irf.WriteAeff function for that.

-> We want to focus on effective area for the time being, and extend to direction (PSF) and energy smearing later.

**) (to do this @shallmann personally likes to develop a streamlit-based tool. This lives in km3irf/viewer for the time being