30 October 2017 Electric field conjugation for ground-based high-contrast imaging: robustness study and tests with the Project 1640 coronagraph
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Abstract
The electric field conjugation (EFC) algorithm has shown promise for removing scattered starlight from high-contrast imaging measurements, both in numerical simulations and laboratory experiments. To prepare for the deployment of EFC using ground-based telescopes, we investigate the response of EFC to unaccounted for deviations from an ideal optical model. We explore the linear nature of the algorithm by assessing its response to a range of inaccuracies in the optical model generally present in real systems. We find that the algorithm is particularly sensitive to unresponsive deformable mirror (DM) actuators, misalignment of the Lyot stop, and misalignment of the focal plane mask. Vibrations and DM registration appear to be less of a concern compared to values expected at the telescope. We quantify how accurately one must model these core coronagraph components to ensure successful EFC corrections. We conclude that while the condition of the DM can limit contrast, EFC may still be used to improve the sensitivity of high-contrast imaging observations. Our results have informed the development of a full EFC implementation using the Project 1640 coronagraph at Palomar observatory. While focused on a specific instrument, our results are applicable to the many coronagraphs that may be interested in employing EFC.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
Christopher T. Matthews, Christopher T. Matthews, Justin R. Crepp, Justin R. Crepp, Gautam Vasisht, Gautam Vasisht, Eric Cady, Eric Cady, } "Electric field conjugation for ground-based high-contrast imaging: robustness study and tests with the Project 1640 coronagraph," Journal of Astronomical Telescopes, Instruments, and Systems 3(4), 045001 (30 October 2017). https://doi.org/10.1117/1.JATIS.3.4.045001 . Submission: Received: 20 January 2017; Accepted: 3 October 2017
Received: 20 January 2017; Accepted: 3 October 2017; Published: 30 October 2017
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