Metadata-Version: 2.4
Name: autolens
Version: 2026.5.8.2
Summary: Open-Source Strong Lensing
Author-email: James Nightingale <James.Nightingale@newcastle.ac.uk>, Richard Hayes <richard@rghsoftware.co.uk>
License: MIT
Project-URL: Homepage, https://github.com/PyAutoLabs/PyAutoLens
Keywords: cli
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Natural Language :: English
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Classifier: Programming Language :: Python :: 3.11
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License-File: LICENSE
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# PyAutoLens-JAX: Open-Source Strong Lensing

[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/PyAutoLabs/autolens_workspace/blob/2026.5.8.1/start_here.ipynb)
[![Documentation Status](https://readthedocs.org/projects/pyautolens/badge/?version=latest)](https://pyautolens.readthedocs.io/en/latest/?badge=latest)
[![Tests](https://github.com/Jammy2211/PyAutoLens/actions/workflows/main.yml/badge.svg)](https://github.com/Jammy2211/PyAutoLens/actions)
[![Build](https://github.com/Jammy2211/PyAutoBuild/actions/workflows/release.yml/badge.svg)](https://github.com/Jammy2211/PyAutoBuild/actions)
[![Code Style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![JOSS](https://joss.theoj.org/papers/10.21105/joss.02825/status.svg)](https://doi.org/10.21105/joss.02825)
[![Zenodo DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4548697.svg)](https://doi.org/10.5281/zenodo.4548697)
[![arXiv](https://img.shields.io/badge/arXiv-1708.07377-blue)](https://arxiv.org/abs/1708.07377)
[![Project Status: Active](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
[![Python Versions](https://img.shields.io/pypi/pyversions/autolens)](https://pypi.org/project/autolens/)
[![PyPI Version](https://img.shields.io/pypi/v/autolens.svg)](https://pypi.org/project/autolens/)

[Installation Guide](https://pyautolens.readthedocs.io/en/latest/installation/overview.html) |
[readthedocs](https://pyautolens.readthedocs.io/en/latest/index.html) |
[Introduction on Colab](https://colab.research.google.com/github/PyAutoLabs/autolens_workspace/blob/2026.5.8.1/start_here.ipynb) |
[HowToLens](https://pyautolens.readthedocs.io/en/latest/howtolens/howtolens.html)

<img src="https://github.com/Jammy2211/PyAutoLogo/blob/main/gifs/pyautolens.gif?raw=true" width="900" />

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:

- [The PyAutoLens readthedocs](https://pyautolens.readthedocs.io/en/latest): which includes [an overview of PyAutoLens's core features](https://pyautolens.readthedocs.io/en/latest/overview/overview_1_start_here.html), [a new user starting guide](https://pyautolens.readthedocs.io/en/latest/overview/overview_2_new_user_guide.html) and [an installation guide](https://pyautolens.readthedocs.io/en/latest/installation/overview.html).
- [The introduction Jupyter Notebook on Google Colab](https://colab.research.google.com/github/PyAutoLabs/autolens_workspace/blob/2026.5.8.1/start_here.ipynb): try **PyAutoLens** in a web browser (without installation).
- [The autolens_workspace GitHub repository](https://github.com/PyAutoLabs/autolens_workspace): example scripts covering every **PyAutoLens** use case.
- [The HowToLens GitHub repository](https://github.com/PyAutoLabs/HowToLens): a Jupyter notebook lecture series teaching strong lensing and lens modeling from the ground up.

## 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](https://github.com/Jammy2211/PyAutoLens/issues).

## 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](https://pyautolens.readthedocs.io/en/latest/howtolens/howtolens.html), and the notebooks themselves live in the [PyAutoLabs/HowToLens](https://github.com/PyAutoLabs/HowToLens) repository.

## Citations

Information on how to cite **PyAutoLens** in publications can be found [on the citations page](https://github.com/Jammy2211/PyAutoLens/blob/main/CITATIONS.md).

## Contributing

Information on how to contribute to **PyAutoLens** can be found [on the contributing page](https://github.com/Jammy2211/PyAutoLens/blob/main/CONTRIBUTING.md).

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