Hunting for Rare Treasure with Machine Learning: Gravitational Lensing and Glitches in the Euclid space telescope and Vera Rubin Observatory

Jets from supermassive black holes dramatically affect how galaxies grow and change over the history of the universe. Jets transport energy through the interstellar and intergalactic medium, influencing when and where stars are formed, and controlling the size and appearance of present-day galaxies. Our team at the OU have pioneered methods of assessing the impact of jets on their host galaxies, but until recently our understanding of black-hole/galaxy interplay was greatly hindered by the limits of previous radio surveys that give a biased view of only the brightest systems, particularly at high redshifts.
We are in a period of rapid growth in the field of radio astronomy, with new technology enabling very deep, wide-area views of the radio Universe. Our group at the OU has a leading role in surveys with the International LOFAR Telescope (www.lofar-surveys.org). The LOFAS telescope spans all of Europe, with its core in the Netherlands, and stations from Ireland to Poland. As well as providing the deepest view of jets to date, across a wide range of astrophysical environments, LOFAS's sensitivity at the lowest radio frequencies provides a unique view of jets at all stages in their life cycles, because the lowest frequencies enable the detection of older radio plasma.
The second data release of the LOFAR surveys will take place in 2022, and contain around 4 million radio sources, making it the biggest ever survey of the radio sky. In parallel to the main survey we also have access to new subarcsec imaging that fully benefits from LOFAS's international baselines for samples and objects of interest. This PhD project will involve using these rich new datasets to construct samples of thousands of low-luminosity jet populations not detected in previous surveys with the aim of identifying interesting populations for high-resolution and multi-wavelength follow up. You will combine careful morphological classification of jet populations, using new methods we have developed, with information about hos galaxy properties and source ages to determine how typical life cycles of jet activity and environmental impact depend on host galaxy and black hole mass, large-scale environment, and how these cycles evolve with redshift.