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Open-Source Strong Lensing

Project description

PyAutoLens-JAX: Open-Source Strong Lensing

Colab Documentation Status Tests Build Code Style: black JOSS Zenodo DOI arXiv Project Status: Active Python Versions PyPI Version

Installation Guide | readthedocs | Introduction on Colab | HowToLens

When two or more galaxies are aligned perfectly down our line-of-sight, the background galaxy appears multiple times.

This is called strong gravitational lensing and PyAutoLens makes it simple to model strong gravitational lenses, using JAX to accelerate lens modeling on GPUs.

Getting Started

The following links are useful for new starters:

Community & Support

Support for PyAutoLens is available via our Slack workspace, where the community shares updates, discusses gravitational lensing analysis, and helps troubleshoot problems.

Slack is invitation-only. If you'd like to join, please send an email requesting an invite.

For installation issues, bug reports, or feature requests, please raise an issue on the GitHub issues page.

HowToLens

For users less familiar with gravitational lensing, Bayesian inference and scientific analysis you may wish to read through the HowToLens lectures. These teach you the basic principles of gravitational lensing and Bayesian inference, with the content pitched at undergraduate level and above.

A complete overview of the lectures is provided on the HowToLens readthedocs page, and the notebooks themselves live in the PyAutoLabs/HowToLens repository.

Citations

Information on how to cite PyAutoLens in publications can be found on the citations page.

Contributing

Information on how to contribute to PyAutoLens can be found on the contributing page.

Hands on support for contributions is available via our Slack workspace, again please email to request an invite.

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