Environments of Green Peas

Understanding how galaxies such as the Milky Way evolve is quintessential to understanding how the universe came to be and research on such subjects is often inaccessible and hidden behind jargon and mathematics.

With this project, we are examining if recently discovered galaxies reside in denser environments compared to the general galaxy population and we attempt to model its underlying dark matter structure. This project creates a pipeline for astrophysical data analysis that any student familiar with Python can carry out, as well as an immersive visualization app for our dataset.

We analyze the environments of these unique galaxies called the Green Peas, which are relevant because their properties resemble the first galaxies ever created, billions of years ago. Using statistical methods and inference techniques, we will attempt to write a theoretical dark matter halo model, which will yield a mathematical function that relates the denseness of the galaxy population to properties of the host galaxy sample.

Essential Functions

  • Read and manipulate large datasets
  • Perform and visualize calculations
  • Bayesian parameter estimation
  • Visualization and immersion on AR Headset


Student Mert Okyay
Faculty Nico Capelluti
College Department of Physics, X-Ray Astronomy Groups