TY - JOUR
T1 - Machine learning-based pulse characterization in figure-eight mode-locked lasers
AU - Kokhanovskiy, Alexey
AU - Bednyakova, Anastasia
AU - Kuprikov, Evgeny
AU - Ivanenko, Aleksey
AU - Dyatlov, Mikhail
AU - Lotkov, Daniil
AU - Kobtsev, Sergey
AU - Turitsyn, Sergey
N1 - 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:https://doi.org/10.1364/OL.44.003410. Systematic or multiple reproduction or distribution to multiple locations via electronic or other means is prohibited and is subject to penalties under law.
PY - 2019/7/1
Y1 - 2019/7/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85068268936&partnerID=8YFLogxK
UR - https://www.osapublishing.org/ol/abstract.cfm?uri=ol-44-13-3410
U2 - 10.1364/OL.44.003410
DO - 10.1364/OL.44.003410
M3 - Article
AN - SCOPUS:85068268936
SN - 0146-9592
VL - 44
SP - 3410
EP - 3413
JO - Optics Letters
JF - Optics Letters
IS - 13
ER -