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Femtosecond laser processing with adaptive optics based on convolutional neural network

机译:基于卷积神经网络的自适应光学器件飞秒激光加工

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摘要

A wavefront aberration causes focal spot distortion leading to loss of resolution and efficiency in laser processing. Therefore, aberration compensation is important for ensuring sub-micron resolution in laser processing. In this paper, femtosecond laser processing with adaptive optics based on a convolutional neural network was demonstrated. The aberrations existing in the laser processing system were continuously predicted by the trained network with an update period of 36 ms and was compensated by a liquid crystal spatial light modulator. In the experiment, the neural network-based adaptive optics reduced the wavefront error in the laser processing system to most one-ninth. Furthermore, parallel laser processing by a computer-generated hologram displayed on the spatial light modulator was also demonstrated while dynamically compensating the aberrations in the system.
机译:波前像差导致焦点变形导致激光加工分辨率的损失和效率。 因此,像差补偿对于确保激光加工中的亚微米分辨率是重要的。 本文证实了基于卷积神经网络的自适应光学器件的飞秒激光加工。 通过训练的网络连续预测存在于激光处理系统中的像差,其更新周期为36ms,并通过液晶空间光调制器补偿。 在实验中,神经网络的自适应光学器件将激光处理系统中的波前误差减少到大多数一九。 此外,还通过在空间光调制器上显示的计算机产生全息图的平行激光处理在动态补偿系统中的像差时,也进行了说明。

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