Correcting non-common path aberrations with deep learning and ERIS on VLT

R. Elliot Meyer; Matthias Tecza; Alvaro Menduina Fernandez; Niranjan Thatte

doi:10.1117/12.3019250

25 July 2024 Correcting non-common path aberrations with deep learning and ERIS on VLT

R. Elliot Meyer, Matthias Tecza, Alvaro Menduina Fernandez, Niranjan Thatte

Proceedings Volume 13101, Software and Cyberinfrastructure for Astronomy VIII; 131013I (2024) https://doi.org/10.1117/12.3019250
Event: SPIE Astronomical Telescopes + Instrumentation, 2024, Yokohama, Japan

Conference Poster

Abstract

The detection and characterization of Earth-like planets in the solar neighborhood is a key scientific goal for the European Southern Observatory’s upcoming Extremely Large Telescope (ELT). A major limitation in achieving the high contrast ratios, i.e. 10⁻⁸–10⁻⁹, at the small inner working angles necessary to conduct these observations is the presence of Non-Common Path Aberrations (NCPAs), which arise from optical path differences between the adaptive optics system and the science instrument. NCPA calibration is therefore critical for improving the performance of several current and planned instruments including ELT-PCS and ELT-HARMONI, a first light instrument for the ELT. We present the development of an alternative approach to NCPA calibration using a deep learning model. The model is trained on both simulated image slicer images and real calibration data obtained from the recently commissioned ERIS integral field spectrograph at the VLT.

Citation Download Citation

R. Elliot Meyer, Matthias Tecza, Alvaro Menduina Fernandez, and Niranjan Thatte "Correcting non-common path aberrations with deep learning and ERIS on VLT", Proc. SPIE 13101, Software and Cyberinfrastructure for Astronomy VIII, 131013I (25 July 2024); https://doi.org/10.1117/12.3019250

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