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arXiv · 1904.00239

Hermite-Gaussian Mode Detection via Convolution Neural Networks

L. R. Hofer·L. W. Jones·J. L. Goedert·R. V. Dragone
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Abstract

Hermite-Gaussian (HG) laser modes are a complete set of solutions to the free-space paraxial wave equation in Cartesian coordinates and represent a close approximation to physically-realizable laser cavity modes. Additionally, HG modes can be mode-multiplexed to significantly increase the information capacity of optical communication systems due to their orthogonality. Since, both cavity tuning and optical communication applications benefit from a machine vision determination of HG modes, convolution neural networks were implemented to detect the lowest twenty-one unique HG modes with an accuracy greater than 99%. As the effectiveness of a CNN is dependent on the diversity of its training data, extensive simulated and experimental datasets were created for training, validation and testing.

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L. R. Hofer, L. W. Jones, J. L. Goedert, R. V. Dragone. 2019-03-30. Hermite-Gaussian Mode Detection via Convolution Neural Networks. https://doi.org/10.1364/josaa.36.000936

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