AI-powered low-order focal plane wavefront sensing in infrared

Mojtaba Taheri; Mahdiyar Molahasani; Sam Ragland; Benoit Neichel; Peter Wizinowich

doi:10.1117/12.3020402

27 August 2024 AI-powered low-order focal plane wavefront sensing in infrared

Mojtaba Taheri, Mahdiyar Molahasani, Sam Ragland, Benoit Neichel, Peter Wizinowich

Author Affiliations +

Proceedings Volume 13097, Adaptive Optics Systems IX; 1309783 (2024) https://doi.org/10.1117/12.3020402
Event: SPIE Astronomical Telescopes + Instrumentation, 2024, Yokohama, Japan

Abstract

Adaptive optics (AO) systems are crucial for high-resolution astronomical observations by compensating for atmospheric turbulence. While laser guide stars (LGS) address high-order wavefront aberrations, natural guide stars (NGS) remain vital for low-order wavefront sensing (LOWFS). Conventional NGS-based methods like Shack-Hartmann sensors have limitations in field of view, sensitivity, and complexity. Focal plane wavefront sensing (FPWFS) offers advantages, including a wider field of view and enhanced signal-to-noise ratio, but accurately estimating low-order modes from distorted point spread functions (PSFs) remains challenging. We propose an AI-powered FPWFS method specifically for low-order mode estimation in infrared wavelengths. Our approach is trained on simulated data and validated on on-telescope data collected from the Keck I adaptive optic (K1AO) bench calibration source in K-band. By leveraging the enhanced signal-to-noise ratio in the infrared and the power of AI, our method overcomes the limitations of traditional LOWFS techniques.This study demonstrates the effectiveness of AI-based FPWFS for low-order wavefront sensing, paving the way for more compact, efficient, and high-performing AO systems for astronomical observations.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Mojtaba Taheri, Mahdiyar Molahasani, Sam Ragland, Benoit Neichel, and Peter Wizinowich "AI-powered low-order focal plane wavefront sensing in infrared", Proc. SPIE 13097, Adaptive Optics Systems IX, 1309783 (27 August 2024); https://doi.org/10.1117/12.3020402

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KEYWORDS

Data modeling

Wavefront sensors

Adaptive optics

Point spread functions

Computer simulations

Infrared sensors

Artificial intelligence

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