Code for Anisotropies in the Microwave Background
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Updated
Aug 27, 2024 - Fortran
Code for Anisotropies in the Microwave Background
Multi-purpose lens modeling software package
PyAutoLens: Open Source Strong Gravitational Lensing
Inference of substructure properties in strong lensing systems with machine learning. Code repository associated with https://arxiv.org/abs/1909.02005.
A gravitational lensing simulator for the machine learning era.
A pipeline for versatile strong lens sample simulations
A Galaxy-Galaxy Lensing Python Package
Planck 2018 lensing pipeline
Standard for strong gravitational lensing analyses
JAX port of lenstronomy, for parallelized, GPU accelerated, and differentiable gravitational lensing and image simulations.
Gradient Informed, GPU Accelerated Lens modelling (GIGALens) -- a package for fast Bayesian inference on strong gravitational lenses.
The fastest gravitational (quasar) microlensing code on the planet. A parallel Barnes-Hut tree code optimized for GPUs, written in OpenCL
Analysis pipeline capable of searching for dark compact objects in the Milky Way through astrometric lensing in real or mock Gaia DR4 data.
An interactive simulation of gravitational lensing effects using WebGL
Code for making lensed CMB maps
An interactive-slider-demo for a simple gravitational lens.
Modeling and inversion of gravitational lenses through a Python interface
From Shear to Map: A Python-based approach to constructing mass maps from lensing measurements.
SNTD is a Python package dedicated to measuring time delays for strongly lensed and multiply-imaged SN. The package can simulate lensed SN, fit for each SN time delay, and propagate the results all the way through to cosmological constraints.
forward reconstruction of lenses and sources from strong lensing observations
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