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arXiv · 2202.07801

Measuring Laser Beams with a Neural Network

Lucas R. Hofer·Milan Krstajić·Robert P. Smith
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Abstract

A deep neural network (NN) is used to simultaneously detect laser beams in images and measure their center coordinates, radii and angular orientations. A dataset of images containing simulated laser beams and a dataset of images with experimental laser beams, generated using a spatial light modulator, are used to train and evaluate the NN. After training on the simulated dataset the NN achieves beam parameter rootmean-square-errors (RMSEs) of less than 3.4% on the experimental dataset. Subsequent training on the experimental dataset causes the RMSEs to fall below 1.1%. The NN method can be used as a stand-alone measurement of the beam parameters or can compliment other beam profiling methods by providing an accurate region-of-interest.

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Lucas R. Hofer, Milan Krstajić, Robert P. Smith. 2022-02-16. Measuring Laser Beams with a Neural Network. https://doi.org/10.1364/ao.443531

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