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

2023 Project Description

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Connecting dense and diffuse gas flows in the giant molecular filament G214.5-1.8: why is this filament so bad at forming stars?
This project can be carried out remotely.

Keywords:
Data analysis
Interstellar medium
Radio astronomy
Star formation

Supervisors

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. Two commonly used tracers for this purpose are Carbon Monoxide (CO) and Ammonia (NH3), the former typically tracing more diffuse gas and the latter the dense gas.

In this project, the student will use observations of NH3 and CO emission lines taken using the 100m GBT and IRAM 30m telescope to study 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 using NH3 data to study how dense material flows along the filament to accumulate in cores where stars form, as well as quantify the degree of turbulence in this dense gas to see if it may significantly impact the star formation in G214.5-1.8. These results may then be compared to previous work using CO data to investigate how kinematics change between the diffuse and dense molecular gas.

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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