APLC-Optimization: an apodized pupil Lyot coronagraph design survey toolkit

TL;DR

This paper introduces a software toolkit for designing apodized pupil Lyot coronagraphs, optimizing their components for various telescope architectures to improve high-contrast imaging capabilities.

Contribution

The paper presents a publicly available software package that combines high-contrast simulation with optimization algorithms to design APLC solutions for different telescope geometries.

Findings

Successfully applied to GPI and HiCAT telescope geometries.

Performed a design survey for a 6m off-axis space telescope.

Conducted wavefront error tolerancing analysis using PASTIS.

Abstract

We present a publicly available software package developed for exploring apodized pupil Lyot coronagraph (APLC) solutions for various telescope architectures. In particular, the package optimizes the apodizer component of the APLC for a given focal-plane mask and Lyot stop geometry to meet a set of constraints (contrast, bandwidth etc.) on the coronagraph intensity in a given focal-plane region (i.e. dark zone). The package combines a high-contrast imaging simulation package HCIPy with a third-party mathematical optimizer (Gurobi) to compute the linearly optimized binary mask that maximizes transmission. We provide examples of the application of this toolkit to several different telescope geometries, including the Gemini Planet Imager (GPI) and the High-contrast imager for Complex Aperture Telescopes (HiCAT) testbed. Finally, we summarize the results of a preliminary design survey for the case of a 6~m aperture off-axis space telescope, as recommended by the 2020 NASA Decadal Survey, exploring APLC solutions for different segment sizes. We then use the Pair-based Analytical model for Segmented Telescope Imaging from Space (PASTIS) to perform a segmented wavefront error tolerancing analysis on these solutions.