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Project area/S

  • The Distant Universe

Project Details

Cosmic web is the filamentary structure of dark matter, gas and galaxies connecting everything in our Uni-verse. Being the luminous object out of the three, galaxies are used to illuminate the nodes (consisting of 1000s of galaxies), filaments (long channels connect-ing galaxies and gas), and holes (maybe a single or no galaxies) in the cosmic web. Cosmological models make very specific predictions about the growth of the cosmic web over time. The lack of large spectroscopic datasets limits our understanding of the cosmic web at high redshifts. The data from the new Australia-led MAGPI survey on the 8-meter Very Large Telescope in Chile could revolutionize this field detecting 100s of galaxy associations beyond the local Universe. The aim of this project is to develop routines to identify galaxy-galaxy associations in the MAGPI observations. We will use the detected galaxy-galaxy associations to constrain the number density and size of structures in the cosmic web at high redshifts. The student will use the reduced data products and red-shift catalogs created by the MAGPI team from one of the best integral field spectrograph in the world, MUSE. This project will have huge scientific impact on future programs with large telescopes.

Student Attributes

Academic Background

Basic knowledge of astronomy and large-scale structures in the Universe.

Computing Skills
Experience with Linux and Python would be desirable, but any programming experience would be fine.

Training Requirement
Basic visualization and emission-line analysis technique from spectroscopic datasets. Statistical analysis of structure in large datasets. Plotting with matplotlib and python.

Project Timeline

  • Week 1 Inductions and project introduction
  • Week 2 Initial Presentation
  • Week 3 Training on visualization software and data catalogs
  • Week 4 Develop code to identify galaxy-galaxy associations in red-shift catalogs in one datacube
  • Week 5 Use the full datacube to check the fidelity of identified associations
  • Week 6 Run the code on all observed field in MAGPI
  • Week 7 Literature search to cross match the newly identified sources
  • Week 8 Tabulate the results and compare conclusion with other surveys in the literature
  • Week 9 Final Presentation
  • Week 10 Final Report

Co-Supervisors

Dr Kate Harborne

Astro3D Research Associate

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