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Project area/S

  • The Local Universe
  • The Distant Universe

Project Details

Just how ‘normal’ is the Milky Way? Is it just a standard spiral galaxy, or is it special in any way? This project will seek to clarify these questions by comparing known attributes of the Milky Way galaxy to external galaxies. A sample of analogues to the Milky Way galaxy will first be selected based on Milky Way properties including stellar mass and other physical characteristics. Utilising resolved integral field spectroscopy from the SAMI galaxy survey, the student will then compare properties such as the age, metal content, degree of rotation, local environment, amount of star formation and structures within their Milky Way analogue sample to our own Galaxy. The result will be a comprehensive survey of how (if at all) the Milky Way differs from its extragalactic neighbours. The student will work with the Australia-wide SAMI galaxy survey team and learn about galaxy evolution through the use of optical spectroscopy and the analysis of integral field spectroscopic data cubes.

Student Attributes

Academic Background

Interest in observational astronomy (especially extragalactic astronomy) preferable.

Computing Skills
Some python experience (or similar programming language) desirable

Training Requirement
Python coding skills, LaTeX, how to perform a lit search for astronomy

Project Timeline

  • Week 1 Inductions and project introduction
  • Week 2 Initial presentation
  • Week 3 Familiarization with SAMI data set, auxiliary data, and literature. Learn what a data cube is, how to display using Python, and how to extract the required properties from SAMI maps files.
  • Week 4 Familiarization with SAMI data set, auxiliary data, and literature
  • Week 5 Select Milky Way analogues (MWA) in SAMI
  • Week 6 Characterize properties of MWA dataset
  • Week 7 Compare MWA properties to the Milky Way
  • Week 8 Make conclusions on the ‘uniqueness’ of the Milky Way compared to similar galaxies
  • Week 9 Final presentation
  • Week 10 Final report

Co-Supervisors

A/Prof Luca Cortese

ARC Future Fellow

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