The low-surface-brightness Universe: a new frontier in the study of galaxy evolution

New astronomical surveys that are both deep and wide - from revolutionary instruments like the Hyper Suprime-Cam (HSC) and the Large Synoptic Survey Telescope (LSST) - are poised to transform our understanding of galaxy evolution. Previous work has been dominated by bright/massive galaxies that lie above the surface-brightness limit of past surveys (e.g. the SDSS). However, 'low-surface-brightness' (LSB) galaxies, i.e. ones that are too faint to be undetectable in past surveys, actually dominate the galaxy number density. Furthermore, key LSB components, such as tidal features induced by galaxy mergers, strongly constrain our structure-formation paradigm. A complete comprehension of how the Universe evolves therefore demands a detailed understanding of the LSB Universe - without it our understanding of galaxy evolution is likely to be highly incomplete!

This project will combine state-of-the-art data from HSC and LSST, with in-house cosmological simulations (Horizon-AGN) and advanced machine-learning techniques (Martin et al. 2019), to perform the first statistical studies of the LSB Universe. It will open up the vast discovery space in this regime by mapping the properties of LSB galaxies in unprecedented detail, quantify the role of galaxy mergers in driving star-formation, black-hole growth and morphological transformation over cosmic time and study the poorly-understood role of black-hole feedback in LSB/dwarf galaxies over at least half the lifetime of the Universe.

The student will collaborate closely (through visits and conference trips) with colleagues in Paris, Oxford and a worldwide network of scientists within the LSST project (in which our team has a leadership role). The project will give the student a broad skillset in astronomical observation, theory and machine-learning that is well-aligned with this new era of Big Data astronomy.