Galaxy clusters are the largest structures in the Universe held together by gravity, containing hundreds or even thousands of galaxies. As galaxies interact, merge, and fall into these massive systems, some of their stars can become detached from their parent galaxies and drift freely within the cluster. These stars are bound not to individual galaxies but to the cluster's overall gravitational potential, which is dominated by dark matter (invisible but dominant matter in the Universe). Over time, they create a very faint and diffuse glow between galaxies known as intra-cluster light (ICL).

The talk is about using astronomical images and cosmological simulations to study this elusive component of galaxy clusters. This faint glow is so dim that it is extremely difficult to detect, making it one of the most challenging features to study in astronomical images. Python plays a central role in this work: from image processing and object detection to measuring galaxy properties, mapping the distribution of diffuse light, and investigating the connections between visible matter and dark matter in galaxy clusters. In this talk, I will present how Python-based tools and scientific libraries enable the analysis of some of the faintest structures ever observed in the Universe and help us uncover the history of galaxy clusters.