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Friends-of-friends algorithm used to find galaxy clusters.

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Friends of Friends Algorithm

Disclaimer: WORK IN PROGRESS!!

This project uses the Friends-of-friends (FoF) algorithm to search for high redshift (0.5 < z < 2) galaxy clusters within the COSMOS survey.

This code base was developed for and used in my undergraduate thesis:

Detection and Analysis of High Redshift Galaxy Clusters

Completed: May 2021

About

Dependencies

  • Python 3.6 or later
  • Popular STEM libraries including: Numpy, Scipy
  • Data Processing libraries: Pandas, Matplotlib
  • Astropy
  • GrisPy

Usage

  1. Pull this repository with
git pull https://github.com/kennethcheo/FoF.git
  1. Obtain your dataset in your desired format (FITS, csv etc.)

    • This project mainly uses Pandas' dataframes to hold data.
    • Refer to data_processing.py for conversion of FITS to DF
  2. Ensure galaxy photometric or spectroscopic dataset with the relevant properties: RA, DEC, z, Absolute Magnitude, Galaxy ID

  3. Run pipeline with pipeline.py by commenting out relevant parts (or using it as a guide)

  4. Remember to change the default parameters in params.py

  5. Run dataset through the pipeline and save them to the appropriate location

    • Large datasets (> 1 million points) might take awhile.

Parameters

  • max_velocity: Maximum relative velocity of member galaxies to cluster center.
  • linking_length_factor: Constant of proportionality in determining linking length, default is 0.2 for dark matter halos.
  • virial_radius: Maximum separation of member galaxies from to cluster center.
  • richness, R: Minimum number of galaxies to form a cluster.
  • overdensity, D: Cluster density comparison with background density.

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