论文标题
全球焦点波侧传感器
An all-photonic focal-plane wavefront sensor
论文作者
论文摘要
自适应光学器件（AO）在天文学，光学通信和遥感中至关重要，以应对地球湍流氛围引起的快速模糊。但是当前的AO系统受其波前传感器的限制，该传感器需要在科学图像的光学平面中使用，并且对某些波前 - 误差模式不敏感。在这里，我们提出了一个基于光子灯笼纤维模式传感器和深度学习的波前传感器，该传感器可以将其放置在与科学图像相同的焦平面上，并且对于单模纤维注射是最佳的。通过测量单模输出阵列的强度，可以重建有关入射波前的相位和振幅信息。我们通过模拟和实验实现来演示该概念，其中Zernike波前误差从焦距测量值中恢复到$ 5.1 \ times10^{ - 3} \;π$ radians root-mean-mean-squared-error的精度。
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 $5.1\times10^{-3}\;π$ radians root-mean-squared-error.
