Paper
27 November 2023 Towards intelligent fiber laser design by using a feed-forward neural network
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Abstract
We demonstrated a high accuracy prediction of the fiber laser output parameters by using a feed-forward neural network. We explored both the gain and spectral filter parameters to test the prediction performance of the neural network and realized the mapping between cavity parameters and laser output performance. We also investigated how the number of hidden layers could influence the accuracy of prediction. Based on the results, the output spectrum and temporal pulse profiles can be predicted with high accuracy in various fiber laser designs. Our work paves the way to intelligent laser design with ultimate autonomy.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Xinyang Liu and Regina Gumenyuk "Towards intelligent fiber laser design by using a feed-forward neural network", Proc. SPIE 12760, Advanced Lasers, High-Power Lasers, and Applications XIV, 127600V (27 November 2023); https://doi.org/10.1117/12.2686809
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KEYWORDS
Neurons

Fiber lasers

Neural networks

Laser resonators

Optical filters

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