By Prof. Conny Aerts, KU Leuven, Belgium

During the MPA garden party, the Rudolf-Kippenhahn-Prize for the best scientific paper written in the past year by a student at the Max Planck Institute for Astrophysics was awarded to two students: Silvia Almada Monter for “Crossing walls and windows: the curious escape of Lyman-α photons through ionized channels” and Christian Partmann for “The importance of nuclear star clusters for massive black hole growth and nuclear star formation in simulated low-mass galaxies”. The prize is awarded to recognize originality, a large impact on science but also the quality of writing for a publication to which students themselves made substantial contributions.

In the first study of its kind, researchers at the RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS) in Japan, together with colleagues from the Max Planck Institute for Astrophysics (MPA) and the Flatiron Institute, used machine learning — a form of artificial intelligence — to significantly speed up the processing time to simulate the evolution of galaxies coupled with supernova explosions. This approach could help us to understand the origins of our own galaxy and, in particular, the elements essential for life in the Milky Way.

While concerned with massive objects such as neutron stars and black holes in her work, Martyna Chruslinska loves the lightweight feeling of figure skating in her spare time.