reggiebernardo/cosmo_learn
Python code for learning cosmology using different methods and mock data
This tool helps cosmologists and astrophysicists understand the universe's expansion and composition. It takes cosmological parameters as input, generates realistic mock observational data across various probes like supernovae and cosmic chronometers, and then uses statistical inference and machine learning to reconstruct cosmological models and constrain parameters. Researchers can use it to test different models against simulated observations and gain insights into dark energy and matter.
No commits in the last 6 months. Available on PyPI.
Use this if you are a cosmologist looking to simulate cosmological observations, test different models with machine learning, or perform statistical inference on cosmological parameters.
Not ideal if you are not working with cosmological datasets or are not comfortable with Python scripting for data analysis.
Stars
12
Forks
6
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Sep 20, 2025
Commits (30d)
0
Dependencies
14
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