The Magellanic Stream is a fascinating region of the galaxy characterized by low gas density. This intriguing project aims to investigate the properties and distribution of the HI gas within the Magellanic Stream.

Leveraging the unprecedented resolution of the Galactic ASKAP survey (30 arcseconds), we will apply the decomposition techniques to analyze the emission and absorption data. This will enable us to directly derive essential parameters such as temperatures, optical depths, column densities, and cold gas fractions along the lines of sight towards the background continuum sources. 

In addition to traditional analysis methods, we will incorporate Machine Learning techniques to estimate the cold HI gas and explore the significance of cold, opaque HI gas within the Magellanic Stream.

By conducting this comprehensive study, we will gain valuable insights into the distinctive properties of the HI gas in the Magellanic Stream. This will allow us to compare the properties of HI gas in the Magellanic Stream with those in the Magellanic Clouds and the Milky Way, shedding light on the differences between these regions.

Python programming skills are preferred for this project.