2026 Project Description

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Why Do Galaxies Stop Forming Stars? A Radial View of Star Formation in Cosmological Simulations

Keywords:

Cosmological Simulations

Galaxy Evolution

Theoretical Astrophysics

Supervisors

Angelo George
Find out more about supervisors on ASIAA website

Task Description and Goals

Galaxies can stop forming stars either because they lose their gas or because their remaining gas becomes inefficient at forming stars. Distinguishing between these possibilities is a key problem in galaxy evolution. In this project, the student will use the state-of-the-art IllustrisTNG cosmological simulations to study how star formation changes within galaxies. Rather than focusing only on global galaxy properties, the project examines radial trends by measuring how the specific star formation rate (sSFR) varies as a function of radius normalized by galaxy size (r/R_e).

The student will analyze a well-defined sample of simulated galaxies at low redshift and compare radial profiles for galaxies with relatively high and low sSFR. To interpret the results, the student will further examine how star formation efficiency (SFE) and gas fraction vary with radius, allowing them to assess whether reduced star formation is driven primarily by a lack of gas or by suppressed efficiency.

Main Goals:

Measure radial sSFR profiles as a function of r/R_e for simulated galaxies
Compare radial trends between high- and low-sSFR galaxy populations
Decompose sSFR into contributions from gas fraction and star formation efficiency
Assess whether star formation suppression occurs due to low SFE or low gas fraction at different regions in galaxies (centers vs. outskirts)

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 formation models. 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 star formation
Introductory experience with Python (preferred but not required)
Interest in data analysis and theoretical modelling

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