Norris Barnaby R M, Wei Jin, Betters Christopher H, Wong Alison, Leon-Saval Sergio G
Sydney Institute for Astronomy, School of Physics, University of Sydney, Physics Road, Sydney, NSW, 2006, Australia.
Sydney Astrophotonic Instrumentation Laboratories, University of Sydney, Physics Road, Sydney, NSW, 2006, Australia.
Nat Commun. 2020 Oct 21;11(1):5335. doi: 10.1038/s41467-020-19117-w.
Adaptive optics (AO) is critical in astronomy, optical communications and remote sensing to deal with the rapid blurring caused by the Earth's turbulent atmosphere. But current AO systems are limited by their wavefront sensors, which need to be in an optical plane non-common to the science image and are insensitive to certain wavefront-error modes. Here we present a wavefront sensor based on a photonic lantern fibre-mode-converter and deep learning, which can be placed at the same focal plane as the science image, and is optimal for single-mode fibre injection. By measuring the intensities of an array of single-mode outputs, both phase and amplitude information on the incident wavefront can be reconstructed. We demonstrate the concept with simulations and an experimental realisation wherein Zernike wavefront errors are recovered from focal-plane measurements to a precision of 5.1 × 10 π radians root-mean-squared-error.
自适应光学（AO）在天文学、光通信和遥感领域对于处理由地球湍流大气引起的快速模糊现象至关重要。但目前的AO系统受到其波前传感器的限制，这些传感器需要处于与科学图像不同的光学平面，并且对某些波前误差模式不敏感。在此，我们展示了一种基于光子灯笼光纤模式转换器和深度学习的波前传感器，它可以放置在与科学图像相同的焦平面，并且对于单模光纤注入是最优的。通过测量一系列单模输出的强度，可以重建入射波前的相位和幅度信息。我们通过模拟和实验实现验证了这一概念，其中从焦平面测量中恢复的泽尼克波前误差的均方根误差精度达到5.1×10⁻⁶弧度。
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