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Proceedings Paper

Control and stabilization of spatial mode quality in a radially polarized solid-state laser using machine learning (Conference Presentation)

Paper Abstract

The automated selection and stabilization of the transverse mode of a radially polarized Ho:YAG laser is reported. A convolutional neural network (CNN) was developed to analyze the modal composition of the laser output in real-time. Calculated error signals from the CNN are compared to the desired mode, allowing a PID control algorithm to dynamically optimize the position of an intracavity lens and therefore maintain desired modal content over pump power changes. This CNN based diagnostic system provides a fast method for selection and stabilization of transverse modes in order to advance radially polarized sources for applications such as laser processing.

Paper Details

Date Published: 10 March 2020
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Proc. SPIE 11259, Solid State Lasers XXIX: Technology and Devices, 112590F (10 March 2020);
Show Author Affiliations
Thomas L. Jefferson-Brain, Optoelectronics Research Ctr. (United Kingdom)
Matthew J. Barber, Optoelectronics Research Ctr. (United Kingdom)
Azaria D. Coupe, Univ. of Southampton (United Kingdom)
William A. Clarkson, Optoelectronics Research Ctr. (United Kingdom)
Peter C. Shardlow, Optoelectronics Research Ctr. (United Kingdom)


Published in SPIE Proceedings Vol. 11259:
Solid State Lasers XXIX: Technology and Devices
W. Andrew Clarkson; Ramesh K. Shori, Editor(s)

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