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Stabilisation of transverse mode purity in a radially polarised Ho:YAG laser using machine learning

Stabilisation of transverse mode purity in a radially polarised Ho:YAG laser using machine learning
Stabilisation of transverse mode purity in a radially polarised Ho:YAG laser using machine learning
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.
0946-2171
Jefferson-Brain, Thomas
8bce2a02-37a4-4277-a8cb-0c40bde57837
Barber, Matthew, James
5682d70c-71a4-4875-a714-55704b8ac20c
Coupe, Azaria
a94ae3f1-b6ad-4f69-8765-335aedb780e9
Clarkson, W.A.
3b060f63-a303-4fa5-ad50-95f166df1ba2
Shardlow, Peter
9ca17301-8ae7-4307-8bb9-371df461520c
Jefferson-Brain, Thomas
8bce2a02-37a4-4277-a8cb-0c40bde57837
Barber, Matthew, James
5682d70c-71a4-4875-a714-55704b8ac20c
Coupe, Azaria
a94ae3f1-b6ad-4f69-8765-335aedb780e9
Clarkson, W.A.
3b060f63-a303-4fa5-ad50-95f166df1ba2
Shardlow, Peter
9ca17301-8ae7-4307-8bb9-371df461520c

Jefferson-Brain, Thomas, Barber, Matthew, James, Coupe, Azaria, Clarkson, W.A. and Shardlow, Peter (2022) Stabilisation of transverse mode purity in a radially polarised Ho:YAG laser using machine learning. Applied Physics B, 128 (110). (doi:10.1007/s00340-022-07816-9).

Record type: Article

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.

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Accepted/In Press date: 6 April 2022
Published date: 28 May 2022

Identifiers

Local EPrints ID: 457870
URI: http://eprints.soton.ac.uk/id/eprint/457870
ISSN: 0946-2171
PURE UUID: 7b308079-b9df-4fab-9214-2628c4172217
ORCID for Thomas 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: 21 Jun 2022 18:04
Last modified: 22 Jun 2022 02:04

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Contributors

Author: Thomas Jefferson-Brain ORCID iD
Author: Azaria Coupe
Author: W.A. Clarkson
Author: Peter Shardlow ORCID iD

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