How Spectral Energy Distribution Models Shape Active Galactic Nucleus Identification

Overview

When astronomers classify a galaxy as harbouring an active galactic nucleus (AGN), that classification often rests entirely on the output of a spectral energy distribution (SED) fitting code. But SED-fitting codes require the user to choose an AGN model, and different models encode different physical assumptions about the geometry, dust distribution, and emission properties of the nucleus. This project asks a deceptively simple question: how much does that choice matter? Working with a radio-selected galaxy sample drawn from the ASKAP-based Evolutionary Map of the Universe (EMU) survey, you will configure and run the SED-fitting cod under a range of AGN model assumptions on QUT's HPC, compare the recovered AGN indicators across configurations, and assess where and why the results diverge. The project sits at the intersection of observational astrophysics, galaxy evolution, and scientific computing.

Research engagement

A concise directed literature review on AGN physics, AGN classification schemes, and SED-fitting methodology; familiarisation with our SED software and its AGN characterisation modules; configuration and execution of SED fits across a controlled sample of EMU radio-selected galaxies; systematic variation of AGN model assumptions and quantitative comparison of recovered AGN indicators; diagnostic visualisation of model-dependent variations; and a written summary of findings.

Research activities

You will work with the QUT Astrophysics Research Group (QARG), under the joint supervision of Dr Michael Cowley and Vanessa Porchet. Activities include weekly supervision meetings, guided orientation to our software in the opening weeks, independent SED configuration and run management through the middle of the project, and preparation of diagnostic figures and a short written report in the final stretch.

Research skills

Practical experience configuring and interpreting outputs from a research-grade SED-fitting code; scientific Python for data handling and visualisation; systematic model comparison and error analysis; and scientific writing and presentation. These skills transfer directly to honours and postgraduate research in observational astrophysics and galaxy evolution.

Outcomes

The aim is to evaluate the sensitivity of SED-derived AGN indicators to AGN model assumptions. Expected outcomes include a suite of SED runs across a grid of model configurations; quantitative comparisons of recovered AGN fractions, luminosities, and related indicators; diagnostic plots illustrating where model choices produce consistent or divergent results; and a short written report.

Skills and experience

Some prior exposure to astrophysics at second-year level or above is recommended. Working knowledge of Python is required.

Start date

2 November, 2026

End date

19 February, 2027

Location

QUT Gardens Point campus, with flexibility for remote work once the computing environment is established.

Additional information

You will be provided access to group computing resources and associated software, a curated sample of EMU radio galaxies, and example configuration files. Supervision includes weekly one-on-one meetings and ongoing support from postgraduate group members.

Keywords

• galaxies
• cosmology
• astrophysics
• scientific computing

Contact

Michael Cowley

07 3138 9197

michael.cowley@qut.edu.au