ASIAA Summer Students Program
ASIAA Summer Student Program 2022
July 1 - August 31

2022 Project Description

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Can multi-scale gas flows explain why the giant molecular filament G214.5-1.8 is so bad at forming stars?
This project can be carried out remotely.

Giant molecular filaments
Radio Astronomy
Star formation


Seamus Clarke
Find out more about supervisors on ASIAA website

Task Description and Goals

Filamentary structures play a key role in the star formation process; however, their formation and how they channel material to newly formed stars is not well understood. While molecular clouds/filaments are predominantly made up of H2, due to its lack of a permanent dipole moment it is difficult to directly observe at low gas temperatures. Thus, other molecular tracers must be used. Furthermore, using the Doppler shift in the frequency of such molecular line tracers, the kinematics and gas flows can be studied. A commonly used tracer for this purpose is Carbon Monoxide (CO) as it is the second most abundant molecule in the interstellar medium.

In this project, the student will use observations of CO emission lines taken using the IRAM 30m telescope to study multi-scale gas flows in the giant star-forming filament G214.5-1.8. This giant filament is unique amongst the ~100 known giant filaments due to how little star formation is occurring despite its massive size and narrowness. An explanation for this uniqueness is not currently known, and is the main aim for the work in this project. This will be done by studying the flow of material onto the filament to help determine how the filament formed, how material flows along the filament to accumulate in cores where stars form, and to quantify the degree of turbulence in the gas to see if it may significantly impact the star formation in G214.5-1.8.

The student will learn the basics of radio astronomy, 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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