Deploys lenstronomy applications, examples and analysis scripts for lens modelling
Acompanies lenstronomy release version 1.8.0. lenstronomy is available through the pypi packaging index: >>> pip install lenstronomy --user If you are using the GitHub branch of lenstronomy, you may be a bit ahead of the notebooks. Get in touch with Simon Birrer (sibirrer@gmail.com) if you encounter problems.
We have made an extension module available here. You can find simple examle notebooks for various cases.
- Units, coordinate system and parameter definitions in lenstronomy
- FITS handling and extracting needed information from the data prior to modeling
- Modeling a simple Einstein ring
- Quadrupoly lensed quasar modelling
- Double lensed quasar modelling
- Time-delay cosmography
- Source reconstruction and deconvolution with Shapelets
- Solving the lens equation
- Multi-band fitting
- Measuring cosmic shear with Einstein rings
- Fitting of galaxy light profiles, like e.g. GALFIT
- Quasar-host galaxy decomposition
- Hiding and seeking a single subclump
- Mock generation of realistic images with substructure in the lens
- Mock simulation API with multi color models
- Catalogue data modeling of image positions, flux ratios and time delays
- Example of numerical ray-tracing and convolution options
- Simulated lenses with populations generated by SkyPy
You can join the lenstronomy mailing list by signing up on the google groups page.
The email list is meant to provide a communication platform between users and developers. You can ask questions, and suggest new features. New releases will be announced via this mailing list.
We also have a Slack channel for the community. Please send me an email such that I can add you to the channel.
If you encounter errors or problems with lenstronomy, please let us know!
We provide some examples where a real galaxy has been lensed and then been reconstructed by a shapelet basis set.
- HST quality data with perfect knowledge of the lens model
- HST quality with a clump hidden in the data
- Extremely large telescope quality data with a clump hidden in the data
The design concept of lenstronomy are reported in Birrer & Amara 2018. Please cite this paper whenever you publish results that made use of lenstronomy. Please also cite Birrer et al 2015 when you make use of the lenstronomy work-flow or the Shapelet source reconstruction. Please make sure to cite also the relevant work that was implemented in lenstronomy, as described in the release paper.