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A Python framework for applying simulation-based inference to cosmological survey data.

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ltu-ili

The Simons Collaboration on Learning the Universe Implicit Likelihood Inference (LtU-ILI) pipeline is a framework for applying simulation-based inference methods to constrain posteriors on cosmological parameters using astronomical survey data. The code is currently built to analyze spectroscopic surveys of the universe's Large-Scale Structure (LSS), such as SDSS-BOSS.

Documentation

The documentation for this project can be found at this link

Installing

Follow the instructions detailed in INSTALL.md.

Contributing

Before contributing, please familiarize yourself with the contribution workflow described in CONTRIBUTING.md.

Contact

If you have comments, questions, or feedback, please write us an issue. The current leads of the LtU ILI working group are Benjamin Wandelt (benwandelt@gmail.com) and Matthew Ho (matthew.annam.ho@gmail.com)

Contributors

Below is a list of contributors to this repository. (Please add your name here!)

Acknowledgements

This work was supported by the Simons Collaboration on "Learning the Universe".

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A Python framework for applying simulation-based inference to cosmological survey data.

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