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

Control and stabilization of spatial mode quality in a radially polarized solid-state laser using machine learning
Control and stabilization of spatial mode quality in a radially polarized solid-state laser using machine learning
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.
0277-786X
SPIE
Jefferson-Brain, Thomas Lewis
8bce2a02-37a4-4277-a8cb-0c40bde57837
Barber, Matthew James
5682d70c-71a4-4875-a714-55704b8ac20c
Coupe, Azaria Deborah
a94ae3f1-b6ad-4f69-8765-335aedb780e9
Clarkson, William
3b060f63-a303-4fa5-ad50-95f166df1ba2
Shardlow, Peter
9ca17301-8ae7-4307-8bb9-371df461520c
Clarkson, W. Andrew
Shori, Ramesh K.
Jefferson-Brain, Thomas Lewis
8bce2a02-37a4-4277-a8cb-0c40bde57837
Barber, Matthew James
5682d70c-71a4-4875-a714-55704b8ac20c
Coupe, Azaria Deborah
a94ae3f1-b6ad-4f69-8765-335aedb780e9
Clarkson, William
3b060f63-a303-4fa5-ad50-95f166df1ba2
Shardlow, Peter
9ca17301-8ae7-4307-8bb9-371df461520c
Clarkson, W. Andrew
Shori, Ramesh K.

Jefferson-Brain, Thomas Lewis, Barber, Matthew James, Coupe, Azaria Deborah, Clarkson, William and Shardlow, Peter (2020) Control and stabilization of spatial mode quality in a radially polarized solid-state laser using machine learning. Clarkson, W. Andrew and Shori, Ramesh K. (eds.) In Solid State Lasers XXIX: Technology and Devices. vol. 11259, SPIE.. (doi:10.1117/12.2551145).

Record type: Conference or Workshop Item (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.

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More information

Published date: 10 March 2020
Venue - Dates: Photonics West, Moscone Center, United States, 2020-02-01 - 2020-02-06

Identifiers

Local EPrints ID: 443573
URI: http://eprints.soton.ac.uk/id/eprint/443573
ISSN: 0277-786X
PURE UUID: 05245d02-c965-4b01-8777-ab233d35e28b
ORCID for Thomas Lewis Jefferson-Brain: ORCID iD orcid.org/0000-0002-8838-5640
ORCID for Matthew James Barber: ORCID iD orcid.org/0000-0001-9768-6421
ORCID for Peter Shardlow: ORCID iD orcid.org/0000-0003-0459-0581

Catalogue record

Date deposited: 03 Sep 2020 01:46
Last modified: 23 Sep 2020 01:51

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