Using machine learning to explore the dynamics of complex laser systems

J. P. Toomey; A. Reid; L. McCalman; T. Malica; D. M. Kane

doi:10.1364/ACOFT.2016.JT4A.18

Using machine learning to explore the dynamics of complex laser systems

J. P. Toomey^*, A. Reid, L. McCalman, T. Malica, D. M. Kane

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

Abstract

Proof of principle study using a machine learning algorithm to actively sample the operating parameter space of a complex laser system, in real-time, to find the boundaries between differentiated dynamical regions efficiently.

Original language	English
Title of host publication	Photonics and Fiber Technology 2016 (ACOFT, BGPP, NP)
Subtitle of host publication	proceedings
Publisher	OSA - The Optical Society
Pages	1-2
Number of pages	2
ISBN (Print)	9781943580170
DOIs	https://doi.org/10.1364/ACOFT.2016.JT4A.18
Publication status	Published - 29 Aug 2016
Event	Australian Conference on Optical Fibre Technology, ACOFT 2016 - Sydney, Australia Duration: 5 Sept 2016 → 8 Sept 2016

Other

Other	Australian Conference on Optical Fibre Technology, ACOFT 2016
Country/Territory	Australia
City	Sydney
Period	5/09/16 → 8/09/16

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10.1364/ACOFT.2016.JT4A.18

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title = "Using machine learning to explore the dynamics of complex laser systems",

abstract = "Proof of principle study using a machine learning algorithm to actively sample the operating parameter space of a complex laser system, in real-time, to find the boundaries between differentiated dynamical regions efficiently.",

author = "Toomey, {J. P.} and A. Reid and L. McCalman and T. Malica and Kane, {D. M.}",

year = "2016",

month = aug,

day = "29",

doi = "10.1364/ACOFT.2016.JT4A.18",

language = "English",

isbn = "9781943580170",

pages = "1--2",

booktitle = "Photonics and Fiber Technology 2016 (ACOFT, BGPP, NP)",

publisher = "OSA - The Optical Society",

note = "Australian Conference on Optical Fibre Technology, ACOFT 2016 ; Conference date: 05-09-2016 Through 08-09-2016",

}

Toomey, JP, Reid, A, McCalman, L, Malica, T & Kane, DM 2016, Using machine learning to explore the dynamics of complex laser systems. in Photonics and Fiber Technology 2016 (ACOFT, BGPP, NP): proceedings., JT4A.18-1, OSA - The Optical Society, pp. 1-2, Australian Conference on Optical Fibre Technology, ACOFT 2016, Sydney, Australia, 5/09/16. https://doi.org/10.1364/ACOFT.2016.JT4A.18

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T1 - Using machine learning to explore the dynamics of complex laser systems

AU - Toomey, J. P.

AU - Reid, A.

AU - McCalman, L.

AU - Malica, T.

AU - Kane, D. M.

PY - 2016/8/29

Y1 - 2016/8/29

N2 - Proof of principle study using a machine learning algorithm to actively sample the operating parameter space of a complex laser system, in real-time, to find the boundaries between differentiated dynamical regions efficiently.

AB - Proof of principle study using a machine learning algorithm to actively sample the operating parameter space of a complex laser system, in real-time, to find the boundaries between differentiated dynamical regions efficiently.

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DO - 10.1364/ACOFT.2016.JT4A.18

M3 - Conference proceeding contribution

AN - SCOPUS:85019506609

SN - 9781943580170

SP - 1

EP - 2

BT - Photonics and Fiber Technology 2016 (ACOFT, BGPP, NP)

PB - OSA - The Optical Society

T2 - Australian Conference on Optical Fibre Technology, ACOFT 2016

Y2 - 5 September 2016 through 8 September 2016

ER -

Using machine learning to explore the dynamics of complex laser systems

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