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Photonics
Volume 10
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10.3390/photonics10111195
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Article

Reconstruction of Femtosecond Laser Pulses from FROG Traces by Convolutional Neural Networks

by
István Tóth
1,*,
Ana Maria Mihaela Gherman
1,
Katalin Kovács
1,
Wosik Cho
2,
Hyeok Yun
3 and
Valer Toşa
1
1
National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat Str., 400293 Cluj-Napoca, Romania
2
Center for Relativistic Laser Science, Institute for Basic Science, Gwangju 61005, Republic of Korea
3
Advanced Photonics Research Institute, Gwangju Institute of Science and Technology, Gwangju 61005, Republic of Korea
*
Author to whom correspondence should be addressed.
Photonics 2023, 10(11), 1195; https://doi.org/10.3390/photonics10111195
Submission received: 6 October 2023 / Revised: 20 October 2023 / Accepted: 24 October 2023 / Published: 26 October 2023
(This article belongs to the Special Issue Metrology at High-Power Laser Facilities: Primary and Secondary Laser-Driven Sources)
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Abstract

We report on the reconstruction of ultrashort laser pulses from computer-simulated and experimental second harmonic generation-frequency resolved optical gating (SHG-FROG) spectrograms. In order to retrieve the spectral amplitude and phase we use a convolutional neural network trained on simulated SHG-FROG spectrograms and the corresponding spectral-domain fields employed as labels for the network, which is a complex field encompassing the full information about the amplitude and phase. Our results show excellent retrieval capabilities of the neural network in case of the simulated pulses. Although trained only on computer generated data, the method shows promising results regarding experimentally measured pulses.
Keywords: ultra-short laser pulse; pulse reconstruction; frequency resolved optical gating; convolutional neural network; deep learning ultra-short laser pulse; pulse reconstruction; frequency resolved optical gating; convolutional neural network; deep learning

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MDPI and ACS Style

Tóth, I.; Gherman, A.M.M.; Kovács, K.; Cho, W.; Yun, H.; Toşa, V. Reconstruction of Femtosecond Laser Pulses from FROG Traces by Convolutional Neural Networks. Photonics 2023, 10, 1195. https://doi.org/10.3390/photonics10111195

AMA Style

Tóth I, Gherman AMM, Kovács K, Cho W, Yun H, Toşa V. Reconstruction of Femtosecond Laser Pulses from FROG Traces by Convolutional Neural Networks. Photonics. 2023; 10(11):1195. https://doi.org/10.3390/photonics10111195

Chicago/Turabian Style

Tóth, István, Ana Maria Mihaela Gherman, Katalin Kovács, Wosik Cho, Hyeok Yun, and Valer Toşa. 2023. "Reconstruction of Femtosecond Laser Pulses from FROG Traces by Convolutional Neural Networks" Photonics 10, no. 11: 1195. https://doi.org/10.3390/photonics10111195

APA Style

Tóth, I., Gherman, A. M. M., Kovács, K., Cho, W., Yun, H., & Toşa, V. (2023). Reconstruction of Femtosecond Laser Pulses from FROG Traces by Convolutional Neural Networks. Photonics, 10(11), 1195. https://doi.org/10.3390/photonics10111195

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