Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
