An unsupervised search of non-thermal diffuse emission in extended sources - Thwala, Siphiwe Anthony (University of the Witwatersrand, Johannesburg, 2022)
Low-surface brightness diffuse radio emission is a useful probe for studying the connection between non-thermal processes in radio sources and their environment, as well as gaining insights on galaxy formation. The presence of this emission in different astrophysical and cosmological signals is not well understood in the literature due to challenges in detection caused by the low-surface brightness of diffuse objects and their origins, particularly in relation to galaxy feedback and formation. We explored the utility of publicly available data to detect, characterise, and study diffuse emission in extended radio sources at the scales of radio galaxies and galaxy clusters. We performed multiple analyses on extended radio continuum sources found in large publicly available radio surveys. The analyses range from in-depth multi-frequency examinations of individual sources to novel approaches for grouping and classifying radio sources with unsupervised machine learning. The analysis of individual sources brought together a range of datasets and techniques to provide insight about their nature. To group and classify continuum radio sources at scale, a novel unsupervised machine learning approach was designed to combine self-organising maps with convolutional neural networks for automatically detecting and clustering similar sources in radio surveys. To the best of our knowledge, this is the first implementation of an architecture that allows for the training of a machine learning model using multi-frequency and multi-scale radio continuum data cubes, as input, to automatically detect and cluster similar sources in radio surveys. This comes at a time when radio astronomy is undergoing a transformation and data mining methods are critical for optimum scientific utilisation of data from telescopes like MeerKAT, JVLA, MWA, and LOFAR (as well as the upcoming SKA). The different works showcase the most interesting radio sources with diffuse emission observed in these investigations.
A thesis submitted in fulfillment of the requirements for the Degree of Doctor of Philosophy, to the Faculty of Science, School of Physics, University of the Witwatersrand, Johannesburg, 2022
Keywords: Computational Astrophysics; Radio Astronomy; Diffuse Emission; Physics; UCTD; SDG-9: Industry, innovation and infrastructure; SDG-13: Climate action