DELVE Milky Way Satellite Selection Function and Empirical Model

This GitHub repository contains the data products and code associated with the observational selection function and empirical model from the DELVE Milky Way Census I paper (arXiv:2509.12313).

We include two simple, ready-to-use example Jupyter notebooks:

1. Notebook_1_Selection_Function_and_Survey_Footprint.ipynb
   Demonstrates how to use the XGBoost-based selection function derived in the paper.

2. Notebook_2_Empirical_Luminosity_Function.ipynb
   Shows how to generate a simulated satellite population based on the best-fit empirical Milky Way satellite model derived in the paper.

Installation and Requirements

To run the code locally, please use the provided Conda environment file. Python 3.10 or later is required.

Contact

If you plan to use these products or have any questions, please do not hesitate to reach out to:

• Chin Yi Tan (chinyi@uchicago.edu)
• Alex Drlica-Wagner (kadrlica@fnal.gov)