Angle‐based wavefront sensing has a rich historical background in measuring optical aberrations. The Shack–Hartmann wavefront sensor is widely employed in adaptive optics systems due to its high optical efficiency and high robustness. However, simultaneously achieving high sensitivity and large dynamic range is still challenging, limiting the performance of diagnosing fast‐changing turbulence. To overcome this limitation, angle‐based neuromorphic wave normal sensing, which serves as a differentiable framework developed on the asynchronous event modality is proposed. Herein, it is illustrated that the emerging computational neuromorphic imaging paradigm enables a direct perception of a high‐dimensional wave normal from the highly efficient temporal diversity measurement. To the best of available knowledge, the proposed scheme is the first to successfully surpass the spot‐overlapping issue caused by the curvature constraint in classical angle‐based wavefront sensing setups under challenging dynamic scenarios.

中文翻译：

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基于角度的神经形态波法线传感


基于角度的波前传感在测量光学像差方面具有丰富的历史背景。Shack-Hartmann 波前传感器因其高光学效率和高鲁棒性而广泛用于自适应光学系统。然而，同时实现高灵敏度和大动态范围仍然具有挑战性，这限制了诊断快速变化的湍流的性能。为了克服这一限制，提出了基于角度的神经形态波法线传感，作为在异步事件模态上开发的可微分框架。在此，说明了新兴的计算神经形态成像范式能够从高效的时间多样性测量中直接感知高维波正常。据现有知识，在具有挑战性的动力学情景下，所提出的方案首次成功超越了经典基于角度的波前传感装置中由曲率约束引起的光斑重叠问题。