aplc_optimization: an apodized pupil Lyot coronagraph design survey toolkit

aplc_optimization is a Python software toolkit for exploring apodized pupil lyot coronagraph (APLC) solutions for abitrary telescope apertures. It’s object-orientated approach simplifies the interface for sampling large parameter spaces, and enables flexibility for implementing various mask architectures and symmetry cases.

Analysis results for HiCAT

Figure 1: Analysis results from a HiCAT design study.

The aplc_optimization toolkit was developed by the Segmented Coronagraph Design & Analysis (SCDA) research team at the Space Telescope Science Institute (STScI) with the support of the NASA Exoplanet Exploration Program (ExEP) and is privately hosted at github.com/spacetelescope/aplc_optimization.

Getting started with aplc_optimization


How to cite aplc_optimization

In addition to this documentation, the aplc_optmization toolkit is described in the following references. Users of aplc_optimization are encouraged to cite one of these.

If there is no appropriate place in the body of text to cite these proceedings, please include something along the lines of the following in your acknowledgements:

“This research made use if aplc_optimization, an object-orientated toolkit for performing Pupil Lyot coronagraph design surveys for segmented telescope apertures.”


Acknowledgements:

  • The Space Telescope Science Institute collaborators, in particular, the Segmented Coronagraph Design and Analysis (SCDA) team.

  • The aplc_optimization *package was created in support of the Segmented Coronagraph Design and Analysis (SCDA) study, funded by NASA’s Exoplanet Exploration Program (ExEP). The goal of this study is to develop viable coronagraph instrument concepts for a LUVOIR-type mission. The apodized pupil Lyot coronagraph (APLC) is one of several coronagraph design families that the SCDA study is assessing.