ASIAA Summer Students Program
ASIAA Summer Student Program 2023
July 3 - August 31

2023 Project Description

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How do supernova remnants impact molecular clouds and star formation? Using the unique CTB 109 remnant as a case study.
This project can be carried out remotely.

Data analysis
Interstellar medium
Molecular clouds
Radio astronomy
Supernova remnants


Seamus Clarke
Find out more about supervisors on ASIAA website

Task Description and Goals

Supernovae play an integral part in the dynamics of the interstellar medium, and by extension star formation. The ejecta of these highly energetic explosions sweep up surrounding gas to form supernova remnants, thus imparting energy and momentum into the interstellar medium, driving turbulence and compressing gas. As the high-mass stars which result in supernovae are short-lived, the first in the clusters to explode do so surrounded by their natal molecular cloud which is still forming stars. Unfortunately due to the short timescales involved it is rare to see these interactions between supernova remnants and dense molecular clouds.

In this project, the student will use observations of multiple molecular tracers taken using the IRAM 30m telescope to study gas properties of a molecular cloud currently being impacted by the supernova remnant CTB 109. Due to the unique configuration of the molecular cloud and the supernova remnant, CTB 109 allows one to study the direct impact of the remnant's shock on the dense gas as well as the indirect effect which the remnant's high energy X-rays has on the cloud chemistry and thermodynamics. This will be done by using line brightnesses and the radiative transfer RADEX to investigate the volume density and temperature structure of the molecular cloud over a wide region, as well as quantifying the level of turbulence driven by the shock so that it may be compared to turbulence in non-shocked regions.

The student will learn the basics of radio astronomy, supernova remnants, star formation and the interstellar medium, as well as gain experience in data analysis and visualisation using Python.

Required Background

Required knowledge includes: English proficiency, a Physics/Astrophysics background, experience using Python.

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