How Dark Energy Shapes What We Know About Galaxies

Overview

When astronomers measure the mass or star formation rate of a distant galaxy, the answer depends on the assumed cosmology. Distances in the universe are set by the cosmic expansion history, which in turn depends on the nature of dark energy. This project asks a simple but revealing question: if dark energy behaves differently from a cosmological constant, how do the measured properties of galaxies change?

In this project, you will derive the relevant cosmological equations by hand, predict analytically how galaxy stellar masses, star formation rates, and ages should shift when the dark energy equation of state is varied, and then test those predictions numerically using QUT's High Performance Computing (HPC). The project incorporates cosmology, extragalactic astronomy, mathematics, and scientific computing.

Research engagement

A short directed literature review on cosmological distance measures and spectral energy distribution (SED) fitting; analytic derivation and manipulation of equations from the Friedmann framework; development of a small numerical integration code in Python; configuration and execution of SED model fits; comparison of analytic predictions with numerical results; and a written summary of findings.

Research activities

You will work with Dr Michael Cowley within the QUT Astrophysics Research Group (QARG), with contact alongside the group's postgraduate students. Activities include weekly supervision meetings, guided exercises in the opening weeks, independent coding and HPC runs through the middle of the project, and preparation of summary plots and a short report in the final stretch.

Research skills

Practical experience translating theoretical cosmology into testable numerical predictions; scientific Python (numerical integration, astropy, matplotlib); use of a research-grade SED-fitting code; error analysis and model comparison; and scientific writing and presentation. These skills transfer directly to honours and postgraduate research in astrophysics.

Outcomes

The aim is to quantify how the dark energy equation of state propagates into SED-derived galaxy properties. Expected outcomes are: a validated set of analytic scaling predictions; a suite of SED runs across a grid of dark energy models; comparison plots showing where the analytic predictions hold and where they break down; and a short written report.

Skills and experience

Completion of PVB220 Cosmology (or equivalent exposure to the Friedmann equations) is highly 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 with astrophysics software pre-installed, worked notes from a previous related VRES project, and code templates for the numerical integration and plotting components. Supervision includes weekly one-on-one meetings and informal support from postgraduate group members.

Keywords

• cosmology
• dark energy
• galaxy evolution
• astrophysics
• Python

Contact

Michael Cowley

0731389197

michael.cowley@qut.edu.au