autolens 2026.1.21.3
Open-Source Strong Lensing
License: MIT
Requires Python: >=3.9
Keywords: cli

PyAutoLens-JAX: Open-Source Strong Lensing
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`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/Jammy2211/autolens_workspace/blob/release/start_here.ipynb>`_ |
`HowToLens <https://pyautolens.readthedocs.io/en/latest/howtolens/howtolens.html>`_

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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 Binder <https://mybinder.org/v2/gh/Jammy2211/autolens_workspace/release?filepath=start_here.ipynb>`_: try **PyAutoLens** in a web browser (without installation).

- `The autolens_workspace GitHub repository <https://github.com/Jammy2211/autolens_workspace>`_: example scripts and the HowToLens Jupyter notebook lectures.

Support
-------

Support for installation issues, help with lens modeling and using **PyAutoLens** is available by
`raising an issue on the GitHub issues page <https://github.com/Jammy2211/PyAutoLens/issues>`_.

We also offer support on the **PyAutoLens** `Slack channel <https://pyautolens.slack.com/>`_, where we also provide the
latest updates on **PyAutoLens**. Slack is invitation-only, so if you'd like to join send
an `email <https://github.com/Jammy2211>`_ requesting an invite.

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>`_