Overcoming challenges in the evolution and nature of massive stars

Massive stars are the cornerstone of the dynamic and chemical evolution of the cosmos, enriching it as they evolve with chemically processed material that is blown away from their surface by energetic winds and eruption processes.

Despite their importance, their evolution from cradle to death as spectacular supernova explosions still poses many mysteries due to crucial knowledge gaps in the physical processes taking place in their interior and atmosphere and the mutual influence by close-by siblings.

Our ultimate goal is to elucidate the physical properties and evolution of massive stars impacted by companions, as well as their contribution to the generation of gravitational waves.

For this, we wish to establish a multidisciplinary, international network of researchers from Europe and America with expertise in various disciplines, and with background in both theory and observations.

We will exploit the avalanche of public data archives and develop machine learning algorithms to detect massive stars in binary and multiple systems, classify them, and create statistically meaningful samples for diverse evolutionary states.

We will develop progressive methods of signal processing for the analysis of the stellar properties, and cutting-edge numerical codes to unveil the impact of stellar interaction and mass ejection on the evolution of the stars and stellar systems. The acquired results will significantly enhance our knowledge and lead to major advancements in all related fields.

The bulk of exchanges will be undertaken by PhD students and Postdocs, whom we will educate and train in modern observing and data analysing techniques, machine learning algorithms, and in high-performance computing, equipping them with excellent skills for their future careers.

We will organise schools, workshops and educational activities to share knowledge as well as disseminate our results, which will be major breakthroughs and will expand Europe's leading role in basic research.