Turbulence is a complex and chaotic state of fluid motion. Atmospheric turbulence within the Earth’s atmosphere poses fundamental challenges for applications such as remote sensing, free-space optical communications and astronomical observation due to its rapid evolution across temporal and spatial scales. Conventional methods for studying atmospheric turbulence face hurdles in capturing the wide-field distribution of turbulence due to its transparency and anisoplanatism. Here we develop a light-field-based plug-and-play wide-field wavefront sensor (WWS), facilitating the direct observation of atmospheric turbulence over 1,100 arcsec at 30 Hz. The experimental measurements agreed with the von Kármán turbulence model, further verified using a differential image motion monitor. Attached to an 80 cm telescope, our WWS enables clear turbulence profiling of three layers below an altitude of 750 m and high-resolution aberration-corrected imaging without additional deformable mirrors. The WWS also enables prediction of the evolution of turbulence dynamics within 33 ms using a convolutional recurrent neural network with wide-field measurements, leading to more accurate pre-compensation of turbulence-induced errors during free-space optical communication. Wide-field sensing of dynamic turbulence wavefronts provides new opportunities for studying the evolution of turbulence in the broad field of atmospheric optics.

湍流是一种复杂而混乱的流体运动状态。地球大气层内的大气湍流由于其在时间和空间尺度上的快速演变，给遥感、自由空间光通信和天文观测等应用带来了根本性挑战。研究大气湍流的传统方法由于其透明度和各等面性而在捕获湍流的宽场分布方面面临障碍。在这里，我们开发了一种基于光场的即插即用宽场波前传感器（WWS），有助于直接观测 30 Hz 下超过 1,100 角秒的大气湍流。实验测量结果与冯·卡门湍流模型一致，并使用差分图像运动监视器进一步验证。连接到 80 厘米望远镜后，我们的 WWS 能够对高度低于 750 米的三层进行清晰的湍流剖面分析，并无需额外的可变形镜即可进行高分辨率像差校正成像。 WWS 还能够使用具有宽场测量的卷积循环神经网络来预测 33 毫秒内湍流动力学的演变，从而在自由空间光通信期间对湍流引起的误差进行更准确的预补偿。动态湍流波前的广域传感为研究大气光学广阔领域中的湍流演化提供了新的机会。