gravitational-lensing

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.

Real-time black hole simulation in C++ and OpenGL, GPU ray marching with Schwarzschild geodesics, gravitational lensing, accretion disk with Doppler beaming, and interactive 2D/3D visualization.

A pipeline for versatile strong lens sample simulations

A User-Friendly Galaxy-Galaxy Lensing Python Package

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

PyAutoLens examples, tutorials, and datasets

Automated pipeline for lens modelling based on lenstronomy

Planck 2018 lensing pipeline

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

Standard for strong gravitational lensing analyses

Implementation of automatic differentiation in VBozza's BinaryLensing

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

microJAX: A GPU-accelerated differentiable microlensing modeling framework

Real-time black hole shader for Unity URP: geodesic lensing, accretion disk, procedural sky.

Dedicated to the brave men and women who gave their lives so we could begin again - Lazarus Missions.

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

Shear Mapping in Python (SMPy): A Python-based, accessible, and robust approach to constructing mass maps from weak lensing measurements.