Personal website of Simon Birrer


I am actively developing and supporting software solutions to help collaborators and the community in general to advance in science. All software I am developing are publicly available, primary on my GitHub repository. I make a big effort in facilitating the distribution and use of the software through packaging, modular built up, documentation and example use cases.

Below you can find a list of packages I have developed or of which I am part of the developing team. If you have further questions, do not hesitate to get in touch with me! I am happy to support you, hand out analysis scripts and add features, if requested.


lenstronomy is a multi-purpose astropy affiliated package to model strong gravitational lenses. The software package is presented in Birrer & Amara 2018 and is based on Birrer et al 2015. lenstronomy finds application in 60+ scientific publications for e.g. measuring the expansion rate of the universe, quantifying lensing substructure to infer dark matter properties, or galaxy evolution studies.


Open source software development project to forward model the sky. I am a development team member.


Deeplenstronomy is a tool for simulating large datasets for applying deep learning to strong gravitational lensing. It works by wrapping the functionalities of lenstronomy in a convenient yaml-style interface, allowing users to embrace the astronomer part of their brain rather than their programmer part when generating training datasets.


Hierarchical analysis of strong lenses to measure the Hubble constant and galaxy density profiles. hierArc found its first application in Birrer et al 2020 and has been extended to e.g. incorporate lensed supernovae by Birrer et al. 2021.


PSF-r performs Point Spread Function reconstruction for astronomical ground- and space-based imaging data. It found application for James Webb Space Telescope and Hubble Space Telescope data analyses.

Strong lensing lecture notes

A set of interactive lecture notes about strong gravitational lensing in Jupyter notebook form.


Python Wrapper of the FASTELL fortran code by Rennan Barkana. It performs fast numerical integrals to compute deflection angle and lensing potential for smoothed elliptical power-law lens models.