Galactic diffuse emission with INTEGRAL/IBIS

This repository provides the code of the IBIS/ISGRI background model used in the paper "The properties of the Galactic Hard X-Ray and soft gamma-ray Background based on 20 years of INTEGRAL/IBIS observations" by Krivonos et al., (2024) arXiv:2409.20058.

In addition to the code, the package contains preprocessed data in data directory. In particular, it contains ISGRI detector count rate cleaned from the contribution of X-ray point sources, for each INTEGRAL observation (so-called "science window", ScW) in the range of the INTEGRAL orbits 70-2740 and in different energy bands. This data set and code can be used to calibrate the ISGRI background model and measure the X-ray intensity of the Galactic background in different parts of the Milky Way.

The preprocessed data will be continuously updated until INTEGRAL stops registering photons.

INSTALL

Step 1. Creation of Python virtual environment

mkdir ~/work; cd ~/work
python3 -m venv venv
source ./venv/bin/activate 

or activate already installed environment, e.g. conda:

conda activate ciao-4.15

Step 2. Clone a repository into a new directory

Go to working directory: cd ~/work.

Then git clone git@heagit.cosmos.ru:integral/ridge.git or git clone http://heagit.cosmos.ru/integral/ridge.git

Step 3. Install code in your Python virtual environment

cd ~/work/ridge
pip install --editable ridge/

Pay attention to the --editable parameter, it allows you to edit the source code of this package and execute it immediately. If you do not plan to modify the local copy of the code, you can remove this option.

Install required packages: pip install -r requirements.txt

After work, you can delete the project:

pip uninstall ridge

Work with pre-processed data

Actual work with the data takes place in the scripts directory, where processing scripts must be run sequentially. This directory contains a detailed description of all actions.

Acknowledgements

Dedicated to Mikhail Revnivtsev (1974-2016). This work is based on observations with INTEGRAL, an ESA project with instruments and the science data centre funded by ESA member states (especially the PI countries: Denmark, France, Germany, Italy, Switzerland, Spain), and Poland, and with the participation of Russia and the USA. The authors are grateful to E. M. Churazov, who developed the INTEGRAL/IBIS data analysis methods and provided the software.

This work was financially supported by grant 24-22-00212 from the Russian Science Foundation.