Accelerated modelling of the entire observable Universe
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The latest space based telescopes, such as the James Webb Space Telescope and Euclid, are now regularly probing the earliest galaxy populations, formed less than a billion years after the Universe formed. Numerical simulations are a key tool in the astrophysicists toolbox that allow us to understand the complex processes occurring in these distant galaxies. But how do we compare our theoretical models to actual observations? And what can we learn about both galaxies and cosmology from these sophisticated models?
In this talk I'll review how we model galaxies using numerical simulations, with a particular focus on how we model the light they emit across the whole electromagnetic spectrum. I'll also talk about some of the exciting new methods from statistics and machine learning that are helping to accelerate our models, and provide new insights into both astrophysics and cosmology.
About our speaker:
Dr. Christopher Lovell is a Dennis Sciama Fellow at the University of Portsmouth. His research focuses on numerical simulations of galaxy evolution, in particular how to model the electromagnetic emission from galaxies, whilst also leveraging the latest statistical and machine learning methods. He received a Phd in Astronomy from the University of Sussex in 2019, supervised by Prof. Peter Thomas and Dr. Stephen Wilkins. He has held postdoctoral roles at the University of Hertfordshire and the University of Tokyo. Recently he was awarded the 2024 Winton Award from the Royal Astronomical Society for his work on forward modelling extreme star forming galaxies. He is a member of the Euclid, Learning the Universe, CAMELS and FLARES international collaborations.
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