Code for Anisotropies in the Microwave Background

Multi-purpose lens modeling software package

PyAutoLens: Open Source Strong Gravitational Lensing

A gravitational lensing simulator for the machine learning era.

A pipeline for versatile strong lens sample simulations

Inference of substructure properties in strong lensing systems with machine learning. Code repository associated with https://arxiv.org/abs/1909.02005.

A Galaxy-Galaxy Lensing Python Package

Planck 2018 lensing pipeline

Automated pipeline for lens modelling based on lenstronomy

Standard for strong gravitational lensing analyses

JAX port of lenstronomy, for parallelized, GPU accelerated, and differentiable gravitational lensing and image simulations.

The fastest gravitational (quasar) microlensing code on the planet. A parallel Barnes-Hut tree code optimized for GPUs, written in OpenCL

Gradient Informed, GPU Accelerated Lens modelling (GIGALens) -- a package for fast Bayesian inference on strong gravitational lenses.

Implementation of automatic differentiation in VBozza's BinaryLensing

An interactive simulation of gravitational lensing effects using WebGL

Analysis pipeline capable of searching for dark compact objects in the Milky Way through astrometric lensing in real or mock Gaia DR4 data.

From Shear to Map: A Python-based approach to constructing mass maps from lensing measurements.

Code for making lensed CMB maps

An interactive-slider-demo for a simple gravitational lens.

The goal of this project is to create an all-encompassing collection of Jupyter notebooks—your trusty companions for engaging exercises related to microlensing. Through these notebooks, the insights and experiences of microlensing elders can light your path as you embark on your journey of discovery and exploration through scientific research.