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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. [ABSTRACT FROM AUTHOR]

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.