Towards 'smart lasers': self-optimisation of an ultrafast pulse source using a genetic algorithm

R. I. Woodward; Edmund J. R. Kelleher

doi:10.1038/srep37616

Towards 'smart lasers': self-optimisation of an ultrafast pulse source using a genetic algorithm

R. I. Woodward^*, Edmund J. R. Kelleher

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

116 Citations (Scopus)

32 Downloads (Pure)

Abstract

Short-pulse fibre lasers are a complex dynamical system possessing a broad space of operating states that can be accessed through control of cavity parameters. Determination of target regimes is a multi-parameter global optimisation problem. Here, we report the implementation of a genetic algorithm to intelligently locate optimum parameters for stable single-pulse mode-locking in a Figure-8 fibre laser, and fully automate the system turn-on procedure. Stable ultrashort pulses are repeatably achieved by employing a compound fitness function that monitors both temporal and spectral output properties of the laser. Our method of encoding photonics expertise into an algorithm and applying machine-learning principles paves the way to self-optimising 'smart' optical technologies.

Original language	English
Article number	37616
Pages (from-to)	1-9
Number of pages	9
Journal	Scientific Reports
Volume	6
DOIs	https://doi.org/10.1038/srep37616
Publication status	Published - 21 Nov 2016
Externally published	Yes

Bibliographical note

Copyright the Author(s) 2016. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

LOCKED FIBER LASER
MODE-LOCKING
LOOP MIRROR
EVOLUTIONARY ALGORITHM
SATURABLE ABSORBERS
NANOTUBE
GRAPHENE

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10.1038/srep37616Licence: CC BY

Publisher version (open access)Final published version, 1.05 MBLicence: CC BY

Cite this

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KW - NANOTUBE

KW - GRAPHENE

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Towards 'smart lasers': self-optimisation of an ultrafast pulse source using a genetic algorithm

Abstract

Bibliographical note

Keywords

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