2026 Project Description

How Do Galaxies Grow? Tracking Size Evolution in Simulated Galaxies

Supervisors

Angelo George
Find out more about supervisors on ASIAA website

Task Description and Goals

Galaxy sizes depend on stellar mass, star formation activity, and the wavelength at which they are observed. Different physical processes—such as star formation in disks, bulge growth, mergers, or stellar mass loss—can change galaxy sizes over time in ways that depend on galaxy type and wavelength. Understanding which processes drive size evolution is a central problem in galaxy formation.

In this project, the student will use the state-of-the-art IllustrisTNG cosmological simulations with realistic mock images to measure galaxy sizes at two rest-frame wavelengths (~3000 Å and ~5000 Å). Rather than studying population averages, the project will track individual galaxies through time to identify episodes of size growth and associate them with physical processes such as smooth star formation, mergers, or passive evolution. By comparing size changes in the UV and optical, the student will learn how different processes leave distinct observable signatures and how wavelength-dependent size measurements can reveal the underlying physics of galaxy growth.

• Measure galaxy sizes at two rest-frame wavelengths (~3000 Å and ~5000 Å) from pre-selected simulated images using GALFIT
• Analyze how various physical mechanisms affect galaxies in the size-mass plane
• Produce plots and statistical summaries of UV–optical size offsets for the provided samples

This project is designed to be completed within 8 weeks and introduces the student to research-level data analysis, cosmological simulations, and the physical interpretation of galaxy evolution. It provides strong preparation for students considering a Master’s program in astrophysics or a related field.

Required Background

This project is suitable for undergraduate students in astronomy, physics, or related disciplines. Helpful background includes:

• Basic knowledge of galaxies and stellar populations
• Introductory experience with Python and basic command-line/Shell usage (preferred but not required)
• Interest in data analysis and theoretical modeling

No prior experience with numerical simulations is required. Close supervision and a clearly structured analysis plan will be provided.