Overview

I am currently a Research Assistant working with Dr Paddy Leahy and Prof. Anna Scaife following on from my PhD, which was titled "Magnetic fields around Radio Galaxies". Primarily, I work on POSSUM, the Polarisation Sky Survey of the Universe's Magnetism. POSSUM is one of the Science Surveys currently being carried out by ASKAP, the Australian Square Kilometre Array Pathfinder telescope. Another ASKAP project I have contributed to is and EMU, the Evolutionary Map of the Universe. I have also recently focused on applications of Machine Learning for Radio Astronomy, specifically for image analysis.

Left: an example of a radio galaxy in the POSSUM Pilot survey.

Below: image of an ASKAP dish (source).

Above: diagram of Faraday rotation. The amount the polarised radio wave rotates is proportional to the magnetic field B and the thermal electron density n_e.

Magnetic fields

POSSUM makes use of a physical phenomenon called Faraday Rotation. Radio waves can be polarised; this means that the waves only oscillate (or "wiggle") in a particular direction. If a polarised radio wave passes through a magneteoionised medium (i.e. a part of space with free electrons and magnetic fields), its polarisation angle changes. By measuring how this polarisation angle changes with radio frequency, we can study the Universe's magentic fields.

I am also involved in another astrophysical magnetism study, QUOCKA. QUOCKA uses the Australia Telescope Compact Array to make complimentary observations to POSSUM.

Radio galaxies

My research focuses on radio galaxies in particular. They're pretty much exactly what they say on the tin: galaxies which are bright in the radio part of the light spectrum. All of the galaxies that I study have an Active Galactic Nucleus, or AGN. AGN occur when black holes at the centre of galaxies convert the mass that they consume into energy, which they release as powerful jets. These jets can stretch out to distances much larger than the galaxies themselves, and are bright when seen in radio waves, especially when these beams spread out into more diffuse 'lobes' as they encounter material in the space between galaxies.

Multiwavlength view of radio galaxy Hercules A. (Source, Credit: NASA, ESA, S. Baum and C. O'Dea (RIT), R. Perley and W. Cotton (NRAO/AUI/NSF), and the Hubble Heritage Team (STScI/AURA)

Above: EMU Zoo logo.

Machine Learning for Radio Astronomy

We are entering the era of Big Data. As radio telescopes become increasingly more advanced, the data volumes they produce grow exponentially. Soon, the days where an astronomer can manually check, or "eyeball", their data will be gone. With ASKAP, thousands of sources can be seen with observations than span the course of only a few hours. My work, funded in-part by the Alan Turing Institute, aims to process radio astronomy data such that it can be better processed by machine learning methods and citizen science.