CATKit2-HCI: a collaborative framework for advancing high-contrast coronagraph testbeds

Rémi Soummer; Iva Laginja; Emiel H. Por; Raphaël Pourcelot; Sarah Steiger; Bryony Nickson; Alexis Lau; Pierre Baudoz; Clarissa Do Ó; Jules Fowler; Raphaël Galicher; Tyler D. Groff; Rebecca Jensen-Clem; Dimitri P. Mawet; Johan Mazoyer; Michael W. McElwain; Lane Meier; Axel Potier; Laurent A. Pueyo; Susan F. Redmond; Scott D. Will; Neil T. Zimmerman

arXiv · 2607.19921

CATKit2-HCI: a collaborative framework for advancing high-contrast coronagraph testbeds

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Abstract

High-contrast exoplanet imaging requires dedicated laboratory testbeds for the development and validation of coronagraph architectures, wavefront sensing and control methods, calibration strategies, and system-level observing concepts. These testbeds often share similar software needs, yet many tools are developed independently at each institution. The CATKit2-High-Contrast-Imaging collaboration, or CATKit2-HCI, addresses this gap by providing a shared software framework for reusable HCI infrastructure. Built on top of CATKit2, an open-source hardware control and synchronization framework originally developed for the High-contrast Imager for Complex Aperture Telescopes (HiCAT) testbed at the Space Telescope Science Institute, CATKit2-HCI provides the collaborative layer for HCI-specific algorithms, calibration tools, diagnostics, visualization, and performance metrics. The collaboration currently includes multiple coronagraph testbeds in the United States and Europe. Its goals are to reduce duplicated software development, improve code quality through shared review, enable more direct comparison of results across facilities, and facilitate the movement of students, postdoctoral researchers, and collaborators between laboratories. We describe the motivation, architecture, collaboration model, shared technical capabilities, and early cross-testbed examples of CATKit2-HCI as a framework for accelerating coronagraph technology development.

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Rémi Soummer, Iva Laginja, Emiel H. Por, Raphaël Pourcelot, Sarah Steiger, Bryony Nickson, Alexis Lau, Pierre Baudoz, Clarissa Do Ó, Jules Fowler, Raphaël Galicher, Tyler D. Groff, Rebecca Jensen-Clem, Dimitri P. Mawet, Johan Mazoyer, Michael W. McElwain, Lane Meier, Axel Potier, Laurent A. Pueyo, Susan F. Redmond, Scott D. Will, Neil T. Zimmerman. 2026-07-22. CATKit2-HCI: a collaborative framework for advancing high-contrast coronagraph testbeds. https://arxiv.org/abs/2607.19921

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