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COSMIC

COSMIC (Cluster Optical Search using Machine Intelligence in Catalogs) is a galaxy cluster finding algorithm that utilizes machine learning techniques.

Toy Model

This project selects a 1 square degree region from the SDSS for testing the code.

Directory Structure

  • data/: Contains test data and background galaxy data.
  • model/: Contains the XGBoost model for BCG classification and the ResNet model for richness estimation.
  • output/: Stores program output data, including candidate BCGs in BCG_cand.fits, detected clusters in cluster.fits, and other necessary data.
  • source/: Contains the source code.

Dependencies

The project requires the following Python packages:

  • astropy==4.3.1
  • functions==0.7.0
  • h5py==3.7.0
  • matplotlib==3.5.3
  • numpy==1.21.6
  • pandas==1.2.0
  • scikit-learn==0.24.2
  • scipy==1.6.2
  • torch==1.7.1+cu110
  • torchvision==0.8.2+cu110
  • xgboost==1.4.2

Note: Ensure you are using a Python environment compatible with these package versions. You can install these dependencies using the provided requirements.txt file:

pip install -r requirements.txt

Running the Program

To execute the program, run:

cd source
python3 run.py

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COSMIC (Cluster Optical Search using Machine Intelligence in Catalogs): A Galaxy Cluster Finding Algorithm Using Machine Learning

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