Stabilisation of transverse mode purity in a radially polarised Ho:YAG laser using machine learning
Stabilisation of transverse mode purity in a radially polarised Ho:YAG laser using machine learning
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DOI：
10.1007/s00340-022-07816-9
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发表时间：
2022-05
期刊：
影响因子：
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通讯作者：
T. L. Jefferson-Brain;M. Barber;A. Coupe;W. Clarkson;P. Shardlow
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作者：
T. L. Jefferson-Brain;M. Barber;A. Coupe;W. Clarkson;P. Shardlow
径向偏振固态激光器在材料加工应用中提供了有吸引力的改进，但选择和稳定适当的径向偏振模式比基模更具挑战性。在这里，我们展示了自动稳定的径向偏振Ho：YAG激光器，利用激光模式分析计算从卷积神经网络。神经网络预测的横向模态内容从单平面强度图像具有高精度的时间尺度上的几毫秒，允许实时自我调整的激光腔。径向偏振发射已被维持在30 W范围内的泵浦功率，与其他任意激光模式的稳定使用相同的神经网络也证明。
Radially polarised solid-state lasers offer attractive improvements in materials processing applications, but selection and stabilisation of the appropriate radially polarised mode is much more challenging than for the fundamental mode. Here, we demonstrate automated stabilisation of a radially polarised Ho:YAG laser by utilising laser mode analysis computed from a convolutional neural network. The neural network predicts the transverse modal content from single plane intensity images with high accuracy on timescales of a few milliseconds, permitting real-time self-adjustment of the laser cavity. Radially polarised emission has been maintained across a 30 W range of pump power, with the stabilisation of other arbitrary laser modes using the same neural network also demonstrated.