Astrophysics at the University of Nottingham 2020-2023

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The main focus of our research in Nottingham is to understand how galaxies form and how they evolve through time to produce the rich variety of structures we see today. We tackle these problems with a number of complementary approaches. One approach is to study relatively nearby galaxies, which we can observe in greater detail. In Nottingham we are involved in a large international project (MaNGA), designed to dissect thousands of local galaxies and extract far more information than was previously possible. At the other extreme, we also specialise in studying very distant galaxies, observing them in the act of formation and transformation many billions of years ago. Due to the finite speed of light, when we observe very distant galaxies we are also looking far back in time, allowing us to observe galaxy evolution at different stages throughout the history of the Universe. Another aim of our research is to understand the roles of "nature" versus "nurture" in shaping galaxy evolution, and in particular how they are influenced by the environments in which they reside. We tackle these varied and challenging problems using a combination of observational techniques, using some of the largest telescopes in the world and in space, combined with theoretical studies and computer simulations. With the latest supercomputers we can create models to simulate the formation of galaxies and the growth of cosmic structures. Many of the most interesting discoveries occur when we confront our models with the latest data, to directly test our understanding of the key processes shaping the Universe. We also use gravitational lensing, a novel technique that exploits the warping of space time by massive objects, which allows us to map the distribution of matter and structure in the Universe to great precision. Finally, we are also developing new "machine learning" tools to help the astronomical community analyse the vast amounts of data that are now routinely produced by astronomical observations and simulations.