Machine learning-based pulse characterization in figure-eight mode-locked lasers


By combining machine learning methods and the dispersive Fourier transform we demonstrate, to the best of our knowledge, for the first time the possibility to determine the temporal duration of picosecond-scale laser pulses using a nanosecond photodetector. A fiber figure of eight lasers with two amplifiers in a resonator was used to generate pulses with durations varying from 28 to 160 ps and spectral widths varied in the range of 0.75–12 nm. The average power of the pulses was in the range from 40 to 300 mW. The trained artificial neural network makes it possible to predict the pulse duration with the mean agreement of 95%. The proposed technique paves the way to creating compact and low-cost feedback for complex laser systems.

Publication DOI:
Divisions: College of Engineering & Physical Sciences > School of Informatics and Digital Engineering > Electrical and Electronic Engineering
College of Engineering & Physical Sciences > Aston Institute of Photonics Technology (AIPT)
College of Engineering & Physical Sciences
Additional Information: This paper was published in Optics Letters and is made available as an electronic reprint with the permission of OSA. The paper can be found at the following URL on the OSA website: Systematic or multiple reproduction or distribution to multiple locations via electronic or other means is prohibited and is subject to penalties under law.
Uncontrolled Keywords: Atomic and Molecular Physics, and Optics
Publication ISSN: 1539-4794
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://www.osa ... i=ol-44-13-3410 (Publisher URL)
PURE Output Type: Article
Published Date: 2019-07-01
Published Online Date: 2019-06-12
Accepted Date: 2019-06-11
Authors: Kokhanovskiy, Alexey
Bednyakova, Anastasia
Kuprikov, Evgeny
Ivanenko, Aleksey
Dyatlov, Mikhail
Lotkov, Daniil
Kobtsev, Sergey
Turitsyn, Sergey (ORCID Profile 0000-0003-0101-3834)



Version: Accepted Version

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