.. |logo| image:: https://raw.githubusercontent.com/ajshajib/dolphin/efb2673646edd6c2d98963e9f4d08a9104d293c3/logo.png :width: 70

|logo| dolphin

.. image:: https://readthedocs.org/projects/dolphin-docs/badge/?version=latest :target: https://dolphin-docs.readthedocs.io/latest/ .. image:: https://github.com/ajshajib/dolphin/actions/workflows/ci.yaml/badge.svg?branch=main :target: https://github.com/ajshajib/dolphin/actions/workflows/ci.yaml .. image:: https://codecov.io/gh/ajshajib/dolphin/branch/main/graph/badge.svg?token=WZVXZS9GF1 :target: https://app.codecov.io/gh/ajshajib/dolphin/tree/main :alt: Codecov .. image:: https://img.shields.io/badge/License-BSD_3--Clause-blue.svg :target: https://github.com/ajshajib/dolphin/blob/main/LICENSE :alt: License BSD 3-Clause Badge .. image:: https://img.shields.io/badge/ApJ-%20992%2040-D22630 :target: https://iopscience.iop.org/article/10.3847/1538-4357/adf95c :alt: Shajib et al. 2025, ApJ, 992, 40 .. image:: https://img.shields.io/badge/arXiv-2503.22657-b31b1b?logo=arxiv&logoColor=white :target: https://arxiv.org/abs/2503.22657 .. image:: https://img.shields.io/badge/DOI-10.5281%2Fzenodo.16587211-blue :target: https://doi.org/10.5281/zenodo.16587211 :alt: Zenodo DOI 10.5281/zenodo.16587211 .. image:: https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=brightyellow :target: https://pre-commit.com/ .. image:: https://img.shields.io/badge/code%20style-black-000000.svg :target: https://github.com/psf/black .. image:: https://img.shields.io/badge/%20formatter-docformatter-fedcba.svg :target: https://github.com/PyCQA/docformatter .. image:: https://img.shields.io/badge/%20style-sphinx-0a507a.svg :target: https://www.sphinx-doc.org/en/master/usage/index.html

Welcome to dolphin, an AI-powered automated pipeline for strong gravitational lens modeling!

dolphin leverages lenstronomy <https://github.com/lenstronomy/lenstronomy>_ as its core modeling engine, providing an accessible and scalable framework for studying galaxy-scale lenses.

What is Dolphin?

Strong gravitational lens modeling traditionally requires significant manual effort. dolphin changes this by providing an AI-driven approach to forward modeling, enabling researchers to process large samples of strong lenses with ease. Whether you want a fully hands-off automated pipeline or a semi-automated workflow where you can fine-tune the AI-generated configurations, dolphin gives you the flexibility and power you need.

Features

• 🤖 AI-Automated Modeling: Streamline forward modeling for large datasets of galaxy-scale lenses.
• 🎛️ Flexible Workflows: Choose between fully automated runs or semi-automated modes with manual overrides.
• 🌈 Multi-Band Support: Easily configure and model across multiple observing bands simultaneously.
• 🌌 Versatile Sources: Built-in support for both galaxy–galaxy and galaxy–quasar lens systems.
• 💻 HPC Ready: Seamlessly sync your setup between local machines and High-Performance Computing Clusters (HPCC).
• ✅ Tested & Reliable: Comprehensively tested with |Codecov|.

.. |Codecov| image:: https://codecov.io/gh/ajshajib/dolphin/branch/main/graph/badge.svg?token=WZVXZS9GF1 :target: https://app.codecov.io/gh/ajshajib/dolphin/tree/main

Installation

.. image:: https://img.shields.io/pypi/v/space-dolphin.svg :alt: PyPI - Version :target: https://pypi.org/project/space-dolphin/

Installing dolphin is simple. You can install the latest stable release via pip:

.. code-block:: bash

pip install space-dolphin

Alternatively, to install the latest development version directly from GitHub:

.. code-block:: bash

git clone https://github.com/ajshajib/dolphin.git
cd dolphin
pip install .

For instructions on setting up your workspace and running your first model, please check out our Quickstart guide <QUICKSTART.rst>_.

Citation

If you use dolphin in your research, please cite the main dolphin paper:

• Shajib et al. (2025) <https://arxiv.org/abs/2503.22657>_

Depending on the fitting recipe used, please additionally cite the following papers for the underlying modeling methodology:

• Galaxy-Quasar Recipe: Shajib et al. (2019) <https://ui.adsabs.harvard.edu/abs/2019MNRAS.483.5649S/abstract>_
• Galaxy-Galaxy Recipe: Shajib et al. (2021) <https://ui.adsabs.harvard.edu/abs/2021MNRAS.503.2380S/abstract>_