posted on 2025-07-09, 04:55authored byJahang Prathap Puthan Kallayi
<p dir="ltr">A supermassive black hole resides in the centre of every galaxy. Some are active, resulting in observational features across the electromagnetic spectrum, and some are quiescent. Using the data from the Galaxy and Mass Assembly (GAMA) G23 region, the Evolutionary Map of the Universe (EMU) survey, and the Wide-field Infrared Survey Explorer (WISE) survey, this thesis proposes a new method for identifying active galactic nuclei (AGN) in low mass (M<sub>∗</sub> ≤ 10<sup>10</sup> M<sub>☉︎</sub>) galaxies. The technique is compared with a selection of different AGN diagnostics to explore the similarities and differences in AGN classification. While diagnostics based on optical and near-infrared criteria (the standard BPT diagram, the WISE colour criterion, and the mass-excitation, or MEx diagram) tend to favour the detection of AGN in high mass, high luminosity systems, the “ProSpect” SED fitting tool can identify AGN efficiently in low mass systems. An explanation for this result is investigated in the context of proportionally lower mass black holes in lower mass galaxies compared to higher mass galaxies and differing proportions of emission from AGN and star formation dominating the light at optical and infrared wavelengths as a function of galaxy stellar mass. Using the same sets of data, this thesis also measures the radio luminosity functions (LFs) of the G23 galaxies as a whole and for AGN and star formers separately. Redshifts and classifications are estimated using simple statistical techniques for those radio galaxies without spectroscopic data. The calculated LFs are compared with the existing studies, and the results suggest that the LFs match remarkably well for low redshift galaxies with an optical counterpart.</p>
1 Introduction -- 2 Spectral Energy Distribution Fitting: A Multiwavelength Search -- 3 EMU/GAMA: A Technique for Detecting Active Galactic Nuclei in Low Mass Systems -- 4 Radio Luminosity Functions -- 5 Conclusions and Future Prospects -- References
Awarding Institution
Macquarie University
Degree Type
Thesis MRes
Degree
Master of Research
Department, Centre or School
School of Mathematical and Physical Sciences
Year of Award
2024
Principal Supervisor
Andrew Hopkins
Additional Supervisor 1
Angel Rafael Lopez Sanchez
Additional Supervisor 2
Tayyaba Zafar
Rights
Copyright: The Author
Copyright disclaimer: https://www.mq.edu.au/copyright-disclaimer