Astro Seminar
Explainable deep learning models for cosmological structure formation
Speaker: Luisa Lucie-Smith (MPA Garching)
Date: Wednesday 13 March 2024
Time: 13:00
Venue: N1.32/Zoom
According to our standard cosmological model, the formation of cosmic structures in the Universe is driven by the gravitational collapse of small matter density fluctuations present in the early Universe. The non-linear nature of gravitational collapse makes it difficult to develop a physical understanding of how complex, late-time cosmic structures emerge from these linear initial conditions. In this talk, I will present an explainable deep learning framework for extracting knowledge about the underlying physics of cosmological structure formation. I will focus on applications to dark matter halos, which form the building blocks of the large-scale structure and wherein galaxy formation takes place. The goal is to use interpretable neural networks to model final emergent properties of dark matter halos, such as their density profiles, and connect them to the physics that determines those properties. The results illustrate the potential for machine-assisted scientific discovery in astrophysical datasets.