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Deep learning the physics of galaxy formation?

Marc Huertas-Company
Instituto de Astrofísica de Canarias, Spain

the availability of statistical samples of galaxies over the past decade has resulted in a global picture of galaxy formation which is successfully translated into modern cosmological simulations that reproduce realistic galaxies. However, most of the key physical processes that govern galaxy evolution are still largely unconstrained and, as such, are treated as subgrid physics in state of the art simulations. The data quality and complexity is progressing fast, which coupled with recent advances in AI, offers new opportunities to make progress in our understanding of the physics of galaxy formation.
Following a general introduction, in my talk, I will discuss recent results from our group aiming at connecting cosmological simulations and observations from deep surveys using a variety of modern deep learning methods.

2024 February 09, 13:30

Centro de Astrofísica da Universidade do Porto (Auditorium)
Rua das Estrelas, 4150-762 Porto

Faculdade de Ciências da Universidade de Lisboa Universidade do Porto Faculdade de Ciências e Tecnologia da Universidade de Coimbra
Fundação para a Ciência e a Tecnologia COMPETE 2020 PORTUGAL 2020 União Europeia