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Any successful, predictive, theory of galaxy formation and evolution must account for the complex interplay of numerous, sometimes uncertain, physical processes, over a large range of spatial and temporal scales. For example, consider gas accreted from the cosmic web onto a galaxy, where it cools and condenses to form stars; subsequently, it is recycled via powerful winds and supernovae explosions and incorporated into the hot gaseous halo in which the galaxy is embedded, before finally accreting onto the galaxy’s central super-massive black hole. This illustrates concisely the range of physical processes (e.g. gravitational collapse and radiative cooling, star formation and stellar-driven injection of energy and momentum into the environment, black hole accretion) and scales (e.g. several orders of magnitude spanning accretion from the cosmic web down to star formation in giant molecular clouds) that must be tracked in any physically-motivated model of galaxy formation.

 

Large cosmological hydrodynamical simulations that track the formation of a galaxy population offer a compromise between the size of the galaxy sample and the accuracy with which detailed properties of individual galaxies can be recovered, assuming a given set of sub-grid prescriptions for e.g. star formation and black hole growth. This means that these kinds of simulations are suited ideally to exploring global statistics and trends within a given model, and are readily comparable to observational datasets. Hydrodynamical simulation of individual systems, which can be either cosmological or non-cosmological, provide a powerful and complementary approach. By focusing computational effort on an individual galaxy, group, or cluster, substantially higher spatial and temporal resolution can be achieved, while also making feasible the use of sub-grid models incorporating greater detail and/or variety. This means that these kinds of simulations are suited ideally to the development and exploration of physical prescriptions, as well as careful comparison with resolved observations.

Our work encompasses a number of key topics, including;

  • Studying the interactions between satellite galaxies and their environments, and consequences for the low surface brightness Universe;
  • Improving models of feedback from stars and black holes, and chemical enrichment of the inter-stellar and circum-galactic medium;
  • Using mock observations of simulated galaxies, groups, and clusters to interpret observational (e.g. stellar and gas integral field spectroscopy, cold gas emission and absorption, dust) datasets; and
  • Applying machine learning techniques to simulated datasets to enrich interpretation of theoretical and observational data.

The prospective student can get involved in various aspects of this broad research area,  including:

  1. Investigating what the spatial, kinematics, and chemical structure of galaxy stellar haloes might tell us about the assembly history of a galaxy like the Milky Way.
  2. Modelling radiative feedback from stars and black holes self-consistently in hydrodynamical simulations using radiative transfer.
  3. Developing an improved model of black hole growth and feedback for galaxy formation.
  4. Studying the co-evolution of black holes and star clusters and consequences for scaling relations between black holes and their host galaxies.
  5. The formation of galaxy disks and the interplay with the physics of the interstellar medium and stellar feedback.
  6. Environmental effects on galaxy evolution at multi-wavelengths.
A simulated galaxy is pictured, showing the main ingredients that make up a galaxy: the stars (blue), the gas from which the stars are born (red), and the dark matter halo that surrounds the galaxy (light grey). Credit:A. Benitez-Llambay & A. Ludlow.